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SEEC: Sparsity-Aware Energy Efficient Clustering Protocol for Underwater Wireless Sensor Networks
Abstract
Many routing protocols are proposed regarding energy efficiency in underwater wireless sensor networks (UWSNs). We propose sparsity-aware energy efficient clustering (SEEC) protocol for UWSNs. SEEC specially search sparse regions of the network. We divide the network region into subregions of equal size and search sparse and dense regions of the network field with the help of sparsity search algorithm (SSA) and density search algorithm (DSA). SEEC improves network lifetime through sink mobility in sparse regions and clustering in dense regions of the network. SEEC also achieves network stability with optimal number of clusters formation in dense regions of the network where each dense region logically represents a static cluster. The division of the network region into subregions control routing hole problem in the UWSNs. SEEC minimizes network energy consumption with balanced scheme operations. Effectiveness of our proposed protocol is verified by simulation results.
... Thus, any node near the sink expends its energy faster than those positioned away from the sink node. Consuming energy rapidly also decreases the PDR [5,7]. ...
... Nodes closer to the sink devour their energy rapidly than nodes positioned away from the sink node because of the large load. Therefore, consuming energy rapidly also decreases the PDR [5,7]. • Third, these schemes use maximum transmission power to reduce network performance [5,6]. ...
... As a result, the use of cluster routing in time-sensitive applications is inadequate for UWSNs. Additionally, authors in [7] proposed sparsity-aware energy-efficient clustering (SEEC) strategy for UWSNs. SEEC specifically searches for sparse areas in the network. ...
Underwater acoustic sensor network (UASN) refers to a procedure that promotes a broad spectrum of aquatic applications. UASNs can be practically applied in seismic checking, ocean mine identification, resource exploration, pollution checking, and disaster avoidance. UASN confronts many difficulties and issues, such as low bandwidth, node movements, propagation delay, 3D arrangement, energy limitation, and high-cost production and arrangement costs caused by antagonistic underwater situations. Underwater wireless sensor networks (UWSNs) are considered a major issue being encountered in energy management because of the limited battery power of their nodes. Moreover, the harsh underwater environment requires vendors to design and deploy energy-hungry devices to fulfil the communication requirements and maintain an acceptable quality of service. Moreover, increased transmission power levels result in higher channel interference, thereby increasing packet loss. Considering the facts mentioned above, this research presents a controlled transmission power-based sparsity-aware energy-efficient clustering in UWSNs. The contributions of this technique is threefold. First, it uses the adaptive power control mechanism to utilize the sensor nodes’ battery and reduce channel interference effectively. Second, thresholds are defined to ensure successful communication. Third, clustering can be implemented in dense areas to decrease the repetitive transmission that ultimately affects the energy consumption of nodes and interference significantly. Additionally, mobile sinks are deployed to gather information locally to achieve the previously mentioned benefits. The suggested protocol is meticulously examined through extensive simulations and is validated through comparison with other advanced UWSN strategies. Findings show that the suggested protocol outperforms other procedures in terms of network lifetime and packet delivery ratio.
... AUV routing necessitates a great deal of planning. In [8], a tracking method based on the cloud-like model data association algorithm is introduced to track underwater various targets. In comparison, the use of AUVs can incur additional costs. ...
... The proposed scheme incorporates the mechanism of transmission power control strategy. Two algorithms are suggested, which is most appropriate for comparison with our proposed algorithm [8]: (1) Sparsity Search Algorithm (SSA) to find sparse regions and (2) Density Search Algorithm (DSA) to find dense regions in the network place. In addition, the cluster head nodes automatically decided by the network and dynamically according to 3 conditions are met [8]: ...
... Two algorithms are suggested, which is most appropriate for comparison with our proposed algorithm [8]: (1) Sparsity Search Algorithm (SSA) to find sparse regions and (2) Density Search Algorithm (DSA) to find dense regions in the network place. In addition, the cluster head nodes automatically decided by the network and dynamically according to 3 conditions are met [8]: ...
Energy-efficient management and highly reliable communication and transmission mechanisms are major issues in Underwater Wireless Sensor Networks (UWSN) due to the limited battery power of UWSN nodes within an harsh underwater environment. In this paper, we integrate the three main techniques that have been used for managing Transmission Power-based Sparsity-conscious Energy-Efficient Clustering (CTP-SEEC) in UWSNs. These incorporate the adaptive power control mechanism that converts to a suitable Transmission Power Level (TPL), and deploys collaboration mobile sinks or Autonomous Underwater Vehicles (AUVs) to gather information locally to achieve energy and data management efficiency (Security) in the WSN. The proposed protocol is rigorously evaluated through extensive simulations and is validated by comparing it with state-of-the-art UWSN protocols. The simulation results are based on the static environmental condition, which shows that the proposed protocol performs well in terms of network lifetime, packet delivery, and throughput.
... To tackle this issue many of the techniques are introduced to increase the node lifetime and to reduce energy consumption such as Minimum Energy Consumption with Unitary Space Time Modulation (MEC-USTM) [13], but it has no monitoring function to identify the fault node thus it attained very less packet delivery ratio. Sparsity-aware Energy Efficient Clustering (SEEC) [23], has two mobile sinks for data collection and achieved a high throughput ratio but it consumed more energy. Energy harvesting [24], it is the Collision Avoidance (CA) strategy to maximize the life time but it is applicable only for 10 to 230 sensor nodes. ...
... Irfan Azam et al [23] proposed SEEC, it has two mobile sinks for the data collection; it is defined as the topmost region and least region. Each data transmission the first mobile sink changes its position as uppermost region to least region but sink 2 always remains in the uppermost region. ...
... The efficiency of the proposed model is compared with existing works in terms of some important metrics such as packet delivery ratio, packet drop ratio, energy overhead, transmission ratio, throughput ratio, energy consumption, and node lifetime. In order to compare the performance of the proposed technology with other methods; some of the energy management techniques are adopted such as SEEC [23], Differential Unitary Space Time Modulation (MEC-USTM) [13], and Enhanced Energy Management scheme in Energy Harvesting Wireless Sensor Networks (EEM-EHWSN) [24]. 1 Merits Demerits Grey Wolf Optimization-Genetic Algorithm (GWO-GA) with load balancing [37] To control the energy consumption it distributes the traffic data to other nodes There is no early prediction of malicious activities so in some case the system is interrupted ...
Wireless Sensor Network (WSN) is used in many applications for different roles, such as monitoring, data transmitting, information gathering, and so on. However, managing energy in WSN is a critical task. To end this issue several clustering and heuristic strategies were constructed still, a suitable solution is not found. So the current research proposed a novel African Buffalo based Two Tier Data Dissemination (AB-TTDD) strategy to monitor the energy drained node in an earlier stage before the data transmission. The fitness function of African Buffalo model is utilized to recognize the harmful and energy drained nodes in an earlier stage. Furthermore, a novel Temporary Energy Mapping Algorithm (TEMA) is developed to maintain the route by creating the reference node instead of energy drained node. This novel proposed mechanism has reduced the packet flow ratio and power consumption in a high manner. At the same time, it enhanced the energy intensity of sensor hubs by mounting its lifetime and affording the reroute. Subsequently, the capability of the proposed strategy is validated with the recent research works and achieved better performance by reducing energy consumption and packet drop ratio.
... The network topology of UWSNs is dynamic i.e., the nodes' position keeps changing due to change in water current [5,6,11]. Furthermore, maintaining the network lifetime in UWSNs is challenging because the sensor nodes are powered by the batteries that cannot be replaced after underwater deployment. ...
... Among these protocols, clustering is reported as a best technique for load balancing in UWSNs where sensor nodes are arranged in multiple groups. These groups are headed by one sensor node known as a cluster head [6,[11][12][13]. Similarly, the use of a mobile sink has been observed as an efficient way of improving throughput [14,15]. ...
... In [11], authors employed two mobile sinks to gather data in sparse regions. The throughput of network is affected when both sinks take adjacent positions as they are covering the same sensor nodes [11,16]. ...
The unique characteristics of underwater environment such as long propagation delay, limited bandwidth, energy-constraint and non-uniform topology are big challenges in designing a routing protocol for underwater wireless sensor networks (UWSNs). In this paper, a novel routing scheme is proposed through which two mobile sinks are used for efficient collection of sensed data packets. Moreover, a new metric “Mobile Sink Utility Ratio (MUR)” is also introduced that helps in measuring the usage of mobile sink in the collection of data packets. The proposed scheme is rigorously evaluated and compared with current state-of-the-art routing protocols. The simulation of the proposed scheme shows promising results in terms of throughput, network lifetime, packet drop ratio and MUR.
... Moreover, hot-spot problem is created in multi-hop communication because sensor nodes near sinks deplete their energy very quickly [4] and die at the start of the network operation because of which area of interest remains unobserved. To cope with hot-spot problem, mobile sinks are used in many routing protocols [8], [9] for data collection from sensor nodes in there vicinity. Furthermore, in many existing protocols [36], [40]sensor nodes near to sink are frequently selected for data forwarding, due to which unbalanced load of transmission on these nodes creates energy holes in the network [37]. ...
... In the past, many energy efficient routing protocols like sparsity-aware energy efficient clustering (SEEC) [9], energy efficient depth based routing (EEDBR) [10], energy efficient and balanced energy consumption cluster based routing (EBECRP) [12] and balanced energy efficient circular (BEEC) [13] routing protocols have been proposed. In SEEC, network field is logically divided into 10 regions of same size. ...
... Each concentric circle is further sub-divided into 2 semi-coronas. After division of circular network field into 10 different size semicoronas, we apply sparsity search algorithm (SSA) and density search algorithm (DSA) as given in [9] to find regions contain less number of nodes and regions with high node density. We introduce sink mobility in low density regions to achieve energy efficiency by collecting data from sensor nodes at minimum distance while clustering technique is implemented in dense regions to overcome the unbalanced transmission load on sensor nodes in the network. ...
In this work, we present two routing protocols for circular underwater wireless sensor networks (UWSNs); circular sparsity-aware energy efficient clustering (CSEEC) and circular depth-based sparsity-aware energy efficient clustering (CDSEEC) with sink mobility. In CSEEC, we divide circular network area into 5 concentric circular regions. We deployed sensor nodes randomly and placed a static sink at the top of the circular underwater network region. We further sub-divided the 5 concentric circles into 10 regions. Then, we identified sparse and dense regions based on the number of nodes in each region. We used cluster based routing approach in dense network regions and introduced sink mobility in least node density region to achieve balanced energy consumption in the network. In CDSEEC, circular network area is divided into upper and lower semi-circles. Sensor nodes are random uniformly deployed in upper and lower semi-circles and a static sink is placed at the surface of the network region. In upper semi-circle, each sensor node send its sensed data to surface sink using depth information of sensor nodes to achieve energy efficiency by selecting forwarder node with minimum depth. In lower semi-circle, we implement cluster based routing approach in high node density regions and used sink mobility in least density network regions to achieve balanced energy consumption. In UWSNs, uneven distribution of sensor nodes and dynamic network topology creates void holes and high collision probability due to channel interference in dense networks. For avoiding void holes and reducing collision probability, we proposed a virtual chain based routing (VCBR) protocol for UWSNs. In VCBR, we build virtual chains between sensor nodes and sinks to avoid void holes. VCBR also minimizes collision probability which is due to channel interference in the network. The proposed VCBR protocol, introduces a mechanism to forward data packet through best suitable virtual chain to manage the energy resources of sensor nodes efficiently during data communication. The shortest virtual chain between source node and destination is calculated based on the location information of sensor nodes. Furthermore, we also exploit cooperative diversity by presenting two routing protocols (i.e., fixed adaptive cooperative virtual chain based routing (FACVCBR) and incremental adaptive cooperative virtual chain based routing (IACVCBR) to achieve data reliability and prolong network lifetime. In FACVCBR, source node broadcasts data to destination and two relays to achieve diversity which results in data reliability. In IACVCBR, retransmission of data packet is done incrementally to improve data reliability and successful delivery of data packets. In proposed FACVCBR and IACVCBR protocols, we introduce adaptive power control mechanism to utilize energy of sensor nodes in an efficient manner. We validate our propositions via simulations. The results verify that our proposed routing protocols outperform baseline protocols in terms of selected performance parameters.
... Though in case of mobile sink can go across all the network plus gather data from node straight There are various directing conventions is purposed towards adjust the vitality utilization then improve quantity of the system. In [5], the creators utilize bunching also multi-jumping strategy to expand the lifetime of the system. System is isolated into meager and thick areas anywhere jumbling and multi- bouncing is utilized as a part of thick locales and two portable sinks are utilized to assemble information in inadequate districts. ...
... DBR indicates greatest throughput than EEDBR in light of the fact that forwarder hubs send information parcels repetitively and take after different ways to reach sink(s). In [5], creators introduced sparsity-mindful vitality effective bunching steering convention (SEEC) to adjust the vitality utilization. Districts are isolated into thick and inadequate locales based on hubs. ...
... Many protocols are designed regarding energy efficiency for UWSNs. Different techniques are used in these protocols like clustering, multi-hopping and direct communication for the collection of data from sensor nodes [3][4]. Recent research shows that mobility of sink is more efficient in UWSNs for sake of data collection. ...
... Sparsity-aware Energy Efficient Clustering protocol for UWSNs is proposed in [3]. This protocol uses the clustering technique in dense region while in sparse region two mobile sinks are used for data collection. ...
Modeling of Underwater Wireless Sensor Networks (UWSNs) with a goal of maximum network lifetime and throughput with minimum energy consumption is a quite difficult task because of limited battery power and harsh underwater environment. Balanced Energy Efficient Rectangular routing protocol (BEER) covers the maximum network area with the mobility of sinks and collects the data from sensor nodes in their transmission range using direct transmission. Sink movement maximizes the throughput and balanced the energy consumption. Simulation results verify that our scheme performs outstanding in terms of network lifetime, stability period and throughput with minimum energy consumption.
... There are many routing protocols are purposed to balance the energy consumption and enhance throughput of the network. In [2], the authors use clustering and multi-hopping technique to prolong the lifetime of the network. Network is divided into sparse and dense regions where cluttering and multi-hopping is used in dense regions and two mobile sinks are used to gather data in sparse regions. ...
... In [2], the authors use clustering technique to balance the energy consumption in the network. Network field is divided into sparse and dense regions on the basis of nodes density. ...
Design of energy efficient underwater wireless sensor networks (UWSNs) routing protocol to prolong network lifetime is a challenging task because of limited battery life of sensor nodes. In this paper, we propose mobile energy efficient square routing protocol (MEES) to balance energy consumption of nodes in the network. Two mobile sinks are deployed at the farthest distance from each other. In order to cover the maximum network field, both mobile sinks move linearly on the predefine path in clockwise direction. Sensor nodes transmit data directly to the mobile sink whenever it comes in its transmission range. Simulation results validate that our propose scheme outperforms the compared schemes (SEEC, BEEC) in terms of network lifetime, throughput, and energy consumption.
... A UWSN node must simulate the transmission of the acoustic wave in order to send data to another node. A wide range of models, from the most straightforward ones founded on the theory of wide circulation to additional intricate and composite ones that established the physics of audio sound transmission, are published in the literature [47][48][49][50]. In this section, we will discuss many auditory broadcast replicas that, although offering different degrees of complexity and accuracy, reflect various approaches to the same problem. ...
Oceanographic data collection, disaster prevention, aided navigation, critical observation sub-missions, contaminant screening, and seaward scanning are just a few of the submissions that use underwater sensor hubs. Unmanned submerged vehicles (USVs) or autonomous acoustic underwater vehicles (AUVs) through sensors would similarly be able to explore unique underwater resources and gather data when utilized in conjunction with integrated screen operations. The most advanced technological method of oceanic observation is wireless information routing beneath the ocean or generally underwater. Water bottoms are typically observed using oceanographic sensors that collect data at certain ocean zones. Most research on UWSNs focuses on physical levels, even though the localization level, such as guiding processes, is a more recent zone. Analyzing the presenting metrics of the current direction conventions for UWSNs is crucial for considering additional enhancements in a procedure employing underwater wireless sensor networks for locating sensors (UWSNs). Due to their severely constrained propagation, radio frequency (RF) transmissions are inappropriate for underwater environments. This makes it difficult to maintain network connectivity and localization. This provided a plan for employing adequate reliability and improved communication and is used to locate the node exactly using a variety of methods. In order to minimize inaccuracies, specific techniques are utilized to calculate the distance to the destination. It has a variety of qualities, such as limited bandwidth, high latency, low energy, and a high error probability. Both nodes enable technical professionals stationed on land to communicate data from the chosen oceanic zones rapidly. This study investigates the significance, uses, network architecture, requirements, and difficulties of undersea sensors.
... The network configuration is examined by the sparse and dense area of the UWSN. These areas are examined using Density Search Algorithm (DSA) and Sparsity Search Algorithm (SSA) [45]. In this, the dense area is examined for clustering and the sparse area is examined for the initial placement of mobile sinks in the networks. ...
Underwater Wireless Sensor Networks (UWSN) has received more attention in exploring promising technologies for scientific data collection of underwater natural resources with maximum link reliability. For effective communication among the sensor nodes, reliable data delivery based routing protocols have been designed to avoid long-distance communication in large network areas. But the network-based protocols suffer from many constraints like limited distance-dependent bandwidth, defective channels and high delay. Furthermore, the supplied batteries have limited power and also data transmission cannot be exploited in the long-distance network areas due to the harsh underwater environment. Therefore, a clustering-based mobility pattern routing protocol is required to link long-distance communication over depth areas with less consumed energy and less delay. This paper proposed an energy-efficient Distributed Node Clustering Mobility Pattern Routing Protocol (DNC-MPRP) to reach the long-distance depth area for data transmission with less energy consumption and avoid inaccurate routing paths using mobility patterns in UWSN. This approach consists of several phases: network initialization, Cluster Head (CH) formation and data transmission. In DNC-MPRP, the network is partitioned into two dense areas for near and far distance communications. Then the network configuration initializes the rectangle mobility pattern which is used to reach the surface sink with less delay. Next, the CH formation initializes the cluster area in the large and common area to maintain energy in the collected member nodes. Lastly, the data transmission is adopted only when the coverage area is in the transmission range of the network field. Simulation result depicts that the DNC-MPRP approach would be evaluated in terms of Energy Consumption (EC), Packet Delivery Ratio (PDR), End to End Delay (E2ED) and Network Lifetime (NL) based on the variation of nodes, different transmission range, mobile sink, data rate and payload data with high PDR of 95%, high NL of 1200 s, low E2ED of 9.5 s and less EC than existing methods.
... In mobile WSN, the nodes are free to move independently [29]. However, if the movement of a node is low, then node can help to a serve longer as CH. ...
Wireless Sensor Network (WSN) is the future of next-generation’s communication and computational technology. Now WSN is being used to fulfill various application requirements like medical, engineering, industries, agriculture, etc. It is a resource-constrained network. Additionally, mobility in WSN causes serious issues related to QoS (Quality of Service) requirements like energy efficiency. In order to deal with this issue, in this paper, an Energy Efficient Weighted Clustering Algorithm (EE-WCA) has been proposed. The main aim of EE-WCA is to create a clustered network, which minimizes energy consumption and creates efficient regional Cluster Heads (CH). For this, three phases in clustering are defined. First, evaluating QoS requirements (i.e., buffer length, node displacement, battery level, connectivity, and SNR (signal to noise ratio)). Second, minimize the computational overhead of nodes to save energy using the weighted computation-based technique. This technique helps to regulate the application’s QoS requirements for the selection of CH. Finally, to distribute the resource consumption uniformly over the entire region of WSN, the CH updation process has been described. The experimental setup is prepared on the NS-2.35 simulator and the results are measured using 10 different sizes of network. The experimental observations on different performance factors, i.e. energy consumption, E2E(End to End) delay, throughput, packet delivery ratio, and packet drop ratio, confirm the enhanced performance of network with respect to a state-of-art WCA algorithm.
... A classic example of a cluster-based energy efficient UWSN is SEEC: Sparsity-aware energy efficient clustering protocol for underwater wireless sensor networks. SEEC was proposed by [15] to search sparse regions in the network. The network is divided into subregions of equal sizes. ...
Wireless Sensor Networks (WSNs) collect data and continuously monitor ambient data such as temperature, humidity and light. The continuous data transmission of energy constrained sensor nodes is a challenge to the lifetime and performance of WSNs. The type of deployment environment is also and the network topology also contributes to the depletion of nodes which threatens the lifetime and the also the performance of the network. To overcome these challenges, a number of approaches have been proposed and implemented. Of these approaches are routing, clustering, prediction, and duty cycling. Prediction approaches may be used to schedule the sleep periods of nodes to improve the lifetime. The chapter discusses WSN deployment environment, energy conservation techniques, mobility in WSN, prediction approaches and their applications in scheduling the sleep/wake-up periods of sensor nodes.
... Thus, for improving network lifetime along with stability and energy efficiency Azam et. al propose a unique scheme called SEEC [61]. ...
Water covers a greater part of the Earth's surface. However, little knowledge has been achieved regarding the underwater world as most parts of it remain unexplored. Oceans, including other water bodies, hold substantial natural resources and also the aquatic lives. These are mostly undiscovered and unknown due to the unsuited and hazardous underwater environments for the human. This inspires the unmanned exploration of these dicey environments. Neither unmanned exploration nor the distant real-time monitoring is possible without deploying Underwater Wireless Sensor Network (UWSN). Consequently, UWSN has drawn the interests of the researchers recently. This vast underwater world is possible to be monitored remotely from a distant location with much ease and less risk. The UWSN is required to be deployed over the volume of the water body to monitor and surveil. For vast water bodies like oceans, rivers and large lakes, data is collected from the different heights/depths of the water level which is then delivered to the surface sinks. Unlike terrestrial communication and radio waves, conventional mediums do not serve the purpose of underwater communication due to their high attenuation and low underwater-transmission range. Instead, an acoustic medium is able to transmit data in underwater more efficiently and reliably in comparison to other mediums. To transmit and relay the data reliably from the bottom of the sea to the sinks at the surface, multi-hop communication is utilized with different schemes. For seabed to surface sink communication, leading researchers proposed different routing protocols. The goal of these routing protocols is to make underwater communications more reliable, energy-efficient and delay efficient. This paper surveys the advancement of some of the routing protocols which eventually helps in finding the most efficient routing protocol and some recent applications for the UWSN. This work also summarizes the remaining challenging issues and the future trends of those considered routing protocols. This survey encourages further research efforts to improve the routing protocols of UWSN for enhanced underwater monitoring and exploration.
... Thus for improving network lifetime along with stability and energy efficiency Azam et. al proposes an unique scheme called SEEC [36]. ...
Water covers a greater part of the earth's surface. Even though we know very little about the underwater world as most parts of it remain unexplored. Oceans including other water bodies hold huge natural resources and also the aquatic lives. These are mostly unexplored and very few of those are known due to unsuited and hazardous environments for the human to explore. This vast underwater world can be monitored remotely from a distant location with much ease and less risk. To monitor water-bodies remotely in real-time, sensor networking has been playing a great role. It is needed to deploy a wireless sensor network over the volume which we want to surveil. For vast water bodies like oceans, rivers and large lakes, data is collected from the different heights of the water level which is sent to the surface sink. Unlike terrestrial communication, radio waves and other conventional mediums can't serve the purpose of underwater communication as they pose high attenuation and very reduced transmission range. Rather an acoustic medium can transmit data more efficiently and reliably in comparison to other mediums. To transmit data reliably from the bottom of the sea to the sinks at the surface, multi-hop communication is needed which must involve a certain scheme. For seabed to surface sink communication, leading researchers have proposed different routing protocols. The goal of these routing protocols is to make underwater communication more reliable, energy-efficient and delay efficient thus to improve the performance of the overall communication. This paper surveys the advancement and applications of the routing protocols which eventually helps in finding the most efficient routing protocol for the Underwater Wireless Sensor Network (UWSN).
... To explore the world below the water, the UWSNs arises [2]. The UWSNs gained more popularity in research demanding many oceanic applications since the people had worked more on land [1] [2] [9]. It is not suitable for humans because of its high pressure and harsh environment in deep ocean region. ...
Underwater Wireless Sensor Networks (UWSN) is one of the emerging technologies. Nowadays, it is more useful to monitor the watery bodies and underwater environment. Energy is one of the main issues in Underwater Wireless Sensor Nodes. Depends on the energy of each node in the network, the transmission rate varies. The nodes in the underwater networks had limited energy so it had to monitor the nodes effectively. In this work, the E-GEDAR protocol is used to analyze the data transmission rates and energy consumption as well as the efficiently. Simulation results show the significant improvement in the above parameters when compared with GEDAR protocol.
... Moreover, a hot-spot problem occurs in multi-hop communication because sensor nodes near sink deplete their energy very quickly [6] and these nodes die earlier, therefore the area of interest remains unobserved. To cope with the hot-spot problem, mobile sinks are used in many routing protocols [7] for data collection from sensor nodes in their vicinity. Furthermore, in existing protocols [8] sensor nodes near sink are often nominated for data sending, such unstable load of transmission on these nodes cause initial death of sensor nodes and produce energy holes in the network [9]. ...
Underwater Wireless Sensor Networks (UWSNs) have emerged as a remarkable interest for
scholars worldwide in terms of various applications such as monitoring offshore oil and gas reservoirs,
pollution, oceans for defense, and other applications such as tsunami. Terrestrial Wireless Sensor Networks (TWSN) and UWSNs share many characteristics apart from having different communication medium
and working environment as UWSNs face the challenges of low-bandwidth, long latency, and high bit error
rate. These have caused for UWSNs many problems such as low reliability, packet retransmission, and
high consumption of energy. To alleviate the aforementioned issues, many techniques have been proposed.
However, most of them merely consider the issue of hotspot which occurs due to the unbalanced transmission
of load on sensor nodes near the surface sink. In this article, we propose a multi-layer cluster-based Energy
Ef cient (MLCEE) protocol for UWSNs to address the issue of hotspot and energy consumption. There
are different stages in MLCEE, rst of which is the division of the whole network in layers, the second is
clustering of the nodes at same layers. In the last stage of transmission, the cluster head (CH) selects the
next hop among the CHs based on greater tness value, small Hopid and small layer number. To mitigate
the issue of hotspot, the rst layer remains un-clustered and any node in the rst layer transfers data to the
sink directly while cluster heads (CHs) are selected based on Bayesian Probability and residual energy. The
simulation results of the proposed technique, done using MATLAB, have revealed that MLCEE achieves
superior performance than the other techniques with regard to the network lifetime, energy consumption,
and data transmission amount.
... Moreover, a hot-spot problem occurs in multi-hop communication because sensor nodes near sink deplete their energy very quickly [6] and these nodes die earlier, therefore the area of interest remains unobserved. To cope with the hot-spot problem, mobile sinks are used in many routing protocols [7] for data collection from sensor nodes in their vicinity. Furthermore, in existing protocols [8] sensor nodes near sink are often nominated for data sending, such unstable load of transmission on these nodes cause initial death of sensor nodes and produce energy holes in the network [9]. ...
Underwater Wireless Sensor Networks (UWSNs) have emerged as a remarkable interest for scholars worldwide in terms of various applications such as monitoring offshore oil and gas reservoirs, pollution, oceans for defense, and other applications such as tsunami. Terrestrial Wireless Sensor Networks (TWSN) and UWSNs share many characteristics apart from having different communication medium and working environment as UWSNs face the challenges of low-bandwidth, long latency, and high bit error rate. These have caused for UWSNs many problems such as low reliability, packet retransmission, and high consumption of energy. To alleviate the aforementioned issues, many techniques have been proposed. However, most of them merely consider the issue of hotspot which occurs due to the unbalanced transmission of load on sensor nodes near the surface sink. In this article, we propose a multi-layer cluster-based Energy Efficient (MLCEE) protocol for UWSNs to address the issue of hotspot and energy consumption. There are different stages in MLCEE, first of which is the division of the whole network in layers, the second is clustering of the nodes at same layers. In the last stage of transmission, the cluster head (CH) selects the next hop among the CHs based on greater fitness value, small Hopid and small layer number. To mitigate the issue of hotspot, the first layer remains un-clustered and any node in the first layer transfers data to the sink directly while cluster heads (CHs) are selected based on Bayesian Probability and residual energy. The simulation results of the proposed technique, done using MATLAB, have revealed that MLCEE achieves superior performance than the other techniques with regard to the network lifetime, energy consumption, and data transmission amount.
... Sparsity-Aware energy efficient clustering protocol (SEEC) [4], is another recently proposed energy efficient routing protocol that divides the network based on the density of the sensor nodes. It uses cluttering and multihopping in dense regions and mobile sinks in sparse ones in order to maximize the network lifetime and efficiently use the battery budget. ...
In the past decade, researchers’ interest in Underwater Wireless Sensors Networks has rapidly increased. There are several challenges facing the lifetime of UWSNs due to the harsh characteristics of the underwater environment. Energy efficiency is one of the major challenges in UWSNs due to the limited battery budget of the sensor nodes. In this paper, we aim at tackling the energy sink-hole problem that especially hits nodes close to the sink when they run out of battery power before other sensors in the network. We prove that we can evenly distribute the transmission load among mobile sensor nodes by letting sensor nodes adjust their transmission ranges. In this paper, we suppose that sensor nodes may adjust their transmission power up to three levels. Consequently, we strive for deriving the optimal load weight for each possible transmission power level that leads to fair energy consumption among all underwater sensors while taking into account the underwater sensors mobility. Performance results show that energy sink-hole problem is overcame and hence the network lifetime is maximized.
... The network was partitioned into static clusters, and energy load was distributed evenly over high-power nodes, resulting in minimization of power consumption, and increased network lifetime. Another static clustering based sparsity-aware energy efficient clustering (SEEC) protocol is proposed in [19]. This protocol used sparsity and density search algorithms to classify sparse and dense regions. ...
... The network was partitioned into static clusters, and energy load was distributed evenly over high-power nodes, resulting in minimization of power consumption, and increased network lifetime. Another static clustering based sparsity-aware energy efficient clustering (SEEC) protocol is proposed in [26]. This protocol used sparsity and density search algorithms to classify sparse and dense regions. ...
In this paper, we propose a novel framework for performance optimization in Internet of Things (IoT)-based next-generation wireless sensor networks. In particular, a computationally-convenient system is presented to combat two major research problems in sensor networks. First is the conventionally-tackled resource optimization problem which triggers the drainage of battery at a faster rate within a network. Such drainage promotes inefficient resource usage thereby causing sudden death of the network. The second main bottleneck for such networks is that of data degradation. This is because the nodes in such networks communicate via a wireless channel, where the inevitable presence of noise corrupts the data making it unsuitable for practical applications. Therefore, we present a layer-adaptive method via 3-tier communication mechanism to ensure the efficient use of resources. This is supported with a mathematical coverage model that deals with the formation of coverage holes. We also present a transform-domain based robust algorithm to effectively remove the unwanted components from the data. Our proposed framework offers a handy algorithm that enjoys desirable complexity for real-time applications as shown by the extensive simulation results.
... In underwater environment the sensor nodes are normally considered as static yet it is additionally viewed as that it might move from 1 to 3 meters for each second as a result of the water stream [2].The sensors are dynamic and move as per the sea currents. Underwater is frequently viewed as an unforgiving domain where sensors tend to move from a particular point to an unexpected area [3]. The restriction of underwater circumstance is mainly because of battery source for sensors added to the fact that it is difficult to the batteries in the deep ocean. ...
Recently Underwater Wireless Sensor Networks (UWSNs) is now emerging as a important research area to explore underwater environments and its resource. Underwater wireless senor nodes are utilized for extensive variety of uses, for example, checking the marine condition for scientific to commercial investigation and coastline surveillance to underwater contamination observing, from water-based calamity preventions to water-based games facilitation. Due to the unstable underwater environment there is a need to increase the scalability and reduce the energy consumption. Connectivity and Coverage are the important properties that decide the proper detection and communication in UWSN. Many researchers have introduced the routing protocol which deals with mobility of node but the research investigation needs further advancement to model a powerful routing algorithm which control movement of the node. In this paper the literature survey on different routing protocol for mobile UWSN are discussed.
... Many routing protocols are proposed to achieve energy efficiency and balance the energy consumption in UWSNs. In [2], the authors used clustering and multi-hopping technique to prolong the lifetime of the network. The network is divided into sparse and dense regions where clustering and multi-hopping is used in dense regions and two mobile sinks are used to gather data in sparse regions. ...
Underwater Wireless Sensor Networks (UWSNs) have captured interest of many researchers with the desire to control the large portion of the world overspread by water. Energy efficiency is one of the major concerns in UWSNs due to the limited energy of the underwater sensor nodes. In order to enhance the network lifetime, efficient and reliable protocols must be presented while considering the underwater acoustic communication challenges like low bandwidth, longer propagation delays and limited battery life of sensor nodes. In this paper, we present Modified Geographic and Opportunistic Depth Adjustment based Routing (MGEDAR) protocol to minimize the energy hole problem in UWSNs. Our protocol works by adaptively adjusting the transmission range of sensor nodes in case of void holes. Each node selects its forwarder on the basis of a cost function. Simulation results showed that our proposed scheme improves network performance in terms of maximum throughput, minimum energy consumption and reduced void holes.
... The network was partitioned into static clusters and energy load was distributed evenly over high-power nodes, resulting in minimization of power consumption, and increased network lifetime. Another static clustering based sparsity-aware energy efficient clustering (SEEC) protocol is proposed in [29]. This protocol used sparsity and density search algorithms to classify sparse and dense regions. ...
In this paper, we combat the problem of performance optimization in wireless sensor networks. Specifically, a novel framework is proposed to handle two major research issues. Firstly, we optimize the utilization of resources available to various nodes at hand. This is achieved via proposed optimal network clustering enriched with layer-adaptive 3-tier communication mechanism to diminish energy holes. We also introduce a mathematical coverage model that helps us minimize the number of coverage holes. Secondly, we present a novel approach to recover the corrupted version of the data received over noisy wireless channels. A robust sparse-domain based recovery method equipped with specially developed averaging filter is used to take care of the unwanted noisy components added to the data samples. Our proposed framework provides a handy routing protocol that enjoys improved computation complexity and elongated network lifetime as demonstrated with the help of extensive simulation results.
... Therefore, it is required to devise new techniques for conscious utilization of nodes battery to improve the network lifespan. 8 This article (an extension of Azam et al. 9 ) introduces three energy-efficient routing protocols, sparsity-aware energy-efficient clustering (SEEC), 9 circular sparsityaware energy-efficient clustering (CSEEC), and circular depth-based sparsity-aware energy-efficient clustering (CDSEEC), to minimize the data load in the dense regions and to avoid energy hole creation in sparse regions of the network field. A d th value is used to minimize the number of hops between the source and the destination to conserve energy of the node. ...
In this paper, to monitor the fields with square and circular geometries, three energy-efficient routing protocols are proposed for underwater wireless sensor networks (UWSNs). First one is, sparsity-aware energy efficient clustering (SEEC), second one is, circular SEEC (CSEEC), and the third one is, circular depth based SEEC (CDSEEC) routing protocol. All three protocols are proposed to minimize the energy consumption of sparse regions. Whereas, sparsity search algorithm (SSA) is proposed to find sparse regions and density search algorithm (DSA) is used to find dense regions of the network field. Moreover, clustering is performed in dense regions to minimize redundant transmissions of a data packet. While, sinks mobility is exploited to collect data from sensor nodes with an objective of minimum energy consumption. A depth threshold (d th) value is also used to minimize number of hops between source and destination for less energy consumption. Simulation results show that our schemes perform better than their counterpart schemes (DBR, EEDBR) in terms of energy efficiency.
... In SEEC with the assist of Density Search Algorithm and Sparsity Search Algorithm, the region is divided into equal size of sub regions and search dense and sparse regions of the network field. SEEC achieved stability of network in dense region of the network with optimal number of cluster where a static cluster is represented by each dense region [11]. ...
Recent research has seen remarkable advancement in the field of Under Water Sensor Networks (UWSNs). Many different protocols are developed in the recent years in this domain. As these protocols can be categorized in a variety of ways according to the mechanisms and functionalities they follow, hence it becomes important to understand their principal working. In this research we have introduced three analysis methods; Clustering based, Localization based and Cooperation based routing by selecting some recent routing protocols in the field of UWSN and presented a comparative analysis according to the categories in which they lie. This research has been taken theoretically and is qualitative one. Also a detail analysis of their key advantages and flaws are also identified in this research.
... Digital Object Identifier 10.1109/JSYST.2017.2673759 energy efficient clustering protocol for reliable data delivery [11] . Although the main aim of these routing schemes is to provide reliable and efficient data delivery in harsh underwater environment and these routing schemes present design objectives for UWSN-based applications, most of the existing routing schemes generally ignore the impact of external interference on transmission reliability in harsh underwater environments and achieve some design objectives at the expense of others. ...
Quality-of-service (QoS) aware reliable data delivery is a challenging issue in underwater wireless sensor networks (UWSNs). This is due to impairments of the acoustic transmission caused by excessive noise, extremely long propagation delays, high bit error rate, low bandwidth capacity, multipath effects, and interference. To address these challenges, meet the commonly used UWSN performance indicators, and overcome the inefficiencies of the existing clustering-based routing schemes, a novel QoS aware evolutionary cluster based routing protocol (QERP) has been proposed for UWSN-based applications. The proposed protocol improves packet delivery ratio, and reduces average end-to-end delay and overall network energy consumption. Our comparative performance evaluations demonstrate that QERP is successful in achieving low network delay, high packet delivery ratio, and low energy consumption.
... In sparsity-aware energy efficient clustering routing protocol (SEEC) [6], purposed scheme clustering technique is used to balance the energy consumption. Regions are divided into dense and sparse regions on the basis of nodes. ...
Design of underwater wireless sensor networks (UWSNs) is difficult because of limited battery energy of sensor nodes. Low bandwidth and energy consumption are major problems that we face in UWSNs, due to dynamic behavior of water in underwater environment. In our scheme, circular field is divided into ten sub-regions and each region is divided into eight sectors. Two mobile sinks move to cover the maximum area of the network field. Mobile Sink1 (M s1) covered the first five regions of the network and remaining covered by Mobile Sink2 (M s2). Both mobile sinks move sector wise in clockwise direction. Due to the mobility of the sinks. We have verify the better performance through simulation results of Network lifetime, Stability and Instability period, Energy consumption and Throughput.
The Wireless Sensor Network (WSN) is an application-centric network, where the data is collected using sensor nodes and communicated to the server or base station to process raw data and to obtain the decisions. For this, it is essential to maintain efficiency and security to serve critical applications. To deal with this requirement, most of the existing techniques modify the routing techniques to secure the network from one or two attacks, but there are significantly fewer solutions that can face multiple kinds of attacks. Therefore, this paper proposed a data-driven and machine learning-based Energy Efficient and Secure Weighted Clustering Algorithm (EES-WCA). The EES-WCA is a combination of EE-WCA and machine learning-based centralized Intrusion detection system (IDS). This technique first creates network clusters, then, without disturbing the WSN routine activity, collect traffic samples on the base station. The base station consists of two machine learning models: Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) to classify the traffic data and identify the malicious nodes in the network. This technique is validated through the generated traffic from the NS2.35 simulator and is also examined in real-time scenarios. The experimental results demonstrate that both the variants of EES-WCA are useful and classify seven different kinds of patterns. According to the simulation results on validation test data, we found up to 90% detection accuracy. Additionally, in real-time scenarios, it replicates the performance by approximately 75%. The performance of EES-WCA in terms of network quality of services such as packet delivery rate, throughput, end to end delay, and energy consumption confirm the superiority of the EES-WCA algorithm.
Energy efficiency and security are considered as important issues in the design of pervasive wireless networks. Since the nodes in pervasive wireless networks are battery-operated, it becomes essential to develop an energy-efficient method to minimize energy consumption and prolong the network lifetime. This paper presents new energy-efficient and secure clustering based data transmission in pervasive wireless networks using red deer algorithm (RDA) based clustering technique with blockchain enabled secured data transmission, named as RDAC-BC. The proposed RDAC-BC technique undergoes node initialization and performs the clustering process using the RDAC technique. The clustering technique performs cluster head (CH) selection and cluster construction process is carried out. Once the CHs are chosen, blockchain enabled secure data transmission takes place among cluster members (CMs) as well as CHs. The application of RDAC and blockchain technology helps to achieve energy efficiency and security. The experimental validation of the RDAC-BC technique is assessed under several aspects and the results are compared with existing methods. The obtained results ensured that the RDAC-BC technique has shown superior results interms of energy, network lifetime, packet delivery ratio (PDR), and throughput.
In this paper, we propose a novel framework for performance optimization in Internet of Things (IoT)-based next-generation wireless sensor networks. In particular, a computationally-convenient system is presented to combat two major research problems in sensor networks. First is the conventionally-tackled resource optimization problem which triggers the drainage of battery at a faster rate within a network. Such drainage promotes inefficient resource usage thereby causing sudden death of the network. The second main bottleneck for such networks is the data degradation. This is because the nodes in such networks communicate via a wireless channel, where the inevitable presence of noise corrupts the data making it unsuitable for practical applications. Therefore, we present a layer-adaptive method via 3-tier communication mechanism to ensure the efficient use of resources. This is supported with a mathematical coverage model that deals with the formation of coverage holes. We also present a transform-domain based robust algorithm to effectively remove the unwanted components from the data. Our proposed framework offers a handy algorithm that enjoys desirable complexity for real-time applications as shown by the extensive simulation results.
Underwater sensor networks have been emerging an extraordinary concern of the scholarly world in term of various aspect of life like monitoring of
oil gas, pollution, and tsunami, ocean surveillance for defense strategies, seismic
monitoring, equipment monitoring etc. The sensor node consumes more energy and
load distribution suffer from imbalance at long distance. In this paper, we present
a Balanced Energy Efficient (BEE) algorithm to diminish the consumption of energy among different nodes of network. The BEE forms a model for the consumption of energy in view of residual energy to choose the ideal next-hop sensor node
for processing of data to destination node. In this scheme, the numbers of nodes
are uniformly positioned in a network field and the destination sink node is positioned at the top of water. This technique is appropriate for both networks like
dynamic and static. The anticipated scheme aims to balance the energy distribution
between different nodes of network field to extend the effort time of nodes associating with present techniques. Simulation results of the anticipated technique are
done to demonstrate the adequacy of BEE, which achieves superior results than the
illustrative techniques in view of energy consumption.
Underwater Wireless Sensor Networks (UWSNs) have captured interest of many researchers with the desire to control the large portion of the world overspread by water. Energy efficiency is one of the major concerns in UWSNs due to the limited energy of the underwater sensor nodes. In order to enhance the network lifetime, efficient and reliable protocols must be presented while considering the underwater acoustic communication challenges like low bandwidth, longer propagation delays and limited battery life of sensor nodes. In this paper, we present Modified Geographic and Opportunistic Depth Adjustment based Routing (MGEDAR) protocol to minimize the energy hole problem in UWSNs. Our protocol works by adaptively adjusting the transmission range of sensor nodes in case of void holes. Each node selects its forwarder on the basis of a cost function. Simulation results showed that our proposed scheme improves network performance in terms of maximum throughput, minimum energy consumption and reduced void holes.
Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in many domains. However, harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, etc. Node mobility and uneven distribution of sensor nodes create void holes in UWSNs. Avoiding void hole creation benefits in many ways: it is mandatory to avoid void hole creation for better coverage over an area, less energy consumption in the network and high throughput. In such conditions, minimization of void hole probability in locally sparse regions is focused in this paper. Two hop adaptive vector based forwarding (2hop-AHH-VBF) routing protocol selects forwarder based on two hop potential neighbor number information. Meeting the void holes during forwarding path is significantly reduced in this way. Moreover, successful transmissions guarantee reliable packet delivery and reduced energy tax. Simulation results verify that proposed scheme outperforms in packet delivery ratio and energy tax while compared with AHH-VBF.
Due to unique characteristics of underwater environment , it is difficult to achieve energy efficiency, high through-put and low bit error rate. Radio signals do not propagate well in underwater environment so acoustic signals are used for communication. Acoustic signals offer low bandwidth, high bit error rate, low throughput and high end-to-end delay. Data packets often loose their path which effect throughput. To increase throughput, we proposed two schemes i.e. Regional Sink Mobility (RSM) and Vertical Sink Mobility (VSM). Sensor node does not need to have information of all other nodes. It only needs information of nodes closer to it. In RSM, we divide whole network into three regions of equal size. There is a mobile sink in each region. Sensor nodes either send data packets directly to sink or through neighbors if sink is in transmission range of any neighbor. In VSM, complete field is divided into ten equal sized regions. There are three mobile sinks. Data transmission mechanism is same as of RSM. At the end, extensive simulations are performed to verify the effectiveness of proposed schemes.
Currently, wireless sensor networks (WSNs) are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC) algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO) is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO) and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP) hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i) selection of optimal number of subregions and further subregion parts, (ii) cluster head selection using ABC algorithm, and (iii) efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS). The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.
A node non-uniform deployment based on clustering algorithm for underwater sensor networks (UWSNs) is proposed in this study. This algorithm is proposed because optimizing network connectivity rate and network lifetime is difficult for the existing node non-uniform deployment algorithms under the premise of improving the network coverage rate for UWSNs. A high network connectivity rate is achieved by determining the heterogeneous communication ranges of nodes during node clustering. Moreover, the concept of aggregate contribution degree is defined, and the nodes with lower aggregate contribution degrees are used to substitute the dying nodes to decrease the total movement distance of nodes and prolong the network lifetime. Simulation results show that the proposed algorithm can achieve a better network coverage rate and network connectivity rate, as well as decrease the total movement distance of nodes and prolong the network lifetime.
Most applications of underwater wireless sensor networks (UWSNs) demand reliable data delivery over a longer period in an efficient and timely manner. However, the harsh and unpredictable underwater environment makes routing more challenging as compared to terrestrial WSNs. Most of the existing schemes deploy mobile sensors or a mobile sink (MS) to maximize data gathering. However, the relatively high deployment cost prevents their usage in most applications. Thus, this paper presents an autonomous underwater vehicle (AUV)-aided efficient data-gathering (AEDG) routing protocol for reliable data delivery in UWSNs. To prolong the network lifetime, AEDG employs an AUV for data collection from gateways and uses a shortest path tree (SPT) algorithm while associating sensor nodes with the gateways. The AEDG protocol also limits the number of associated nodes with the gateway nodes to minimize the network energy consumption and to prevent the gateways from overloading. Moreover, gateways are rotated with the passage of time to balance the energy consumption of the network. To prevent data loss, AEDG allows dynamic data collection at the AUV depending on the limited number of member nodes that are associated with each gateway. We also develop a sub-optimal elliptical trajectory of AUV by using a connected dominating set (CDS) to further facilitate network throughput maximization. The performance of the AEDG is validated via simulations, which demonstrate the effectiveness of AEDG in comparison to two existing UWSN routing protocols in terms of the selected performance metrics.
Clustering the Wireless Sensor Networks (WSNs) is the major issue which determines the lifetime of the network. The parameters chosen for clustering should be appropriate to form the clusters according to the need of the applications. Some of the well-known clustering techniques in WSN are designed only to reduce overall energy consumption in the network and increase the network lifetime. These algorithms achieve increased lifetime, but at the cost of overloading individual sensor nodes. Load balancing among the nodes in the network is also equally important in achieving increased lifetime. First Node Die (FND), Half Node Die (HND), and Last Node Die (LND) are the different metrics for analysing lifetime of the network. In this paper, a new clustering algorithm, Genetic Algorithm based Energy efficient Clustering Hierarchy (GAECH) algorithm, is proposed to increase FND, HND, and LND with a novel fitness function. The fitness function in GAECH forms well-balanced clusters considering the core parameters of a cluster, which again increases both the stability period and lifetime of the network. The experimental results also clearly indicate better performance of GAECH over other algorithms in all the necessary aspects.
In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node's energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network.
The existing coverage hole boundary detection methods cannot detect large-scale coverage hole boundary in wireless sensor network quickly and efficiently. Aiming at this problem, a boundary detection method for large-scale coverage holes in wireless sensor network based on minimum critical threshold constraint is proposed. Firstly, the optimization problem of minimum critical threshold is highlighted, and its formulaic description is constructed according to probabilistic sensing model. On the basis of this, the distributed gradient information is used to approximately solve the optimization problem. After that, local-scale rough boundary detection algorithm incorporating the minimum critical threshold and its iterative thinning algorithm are proposed according to blocking flow theory. The experimental results show that the proposed method has low computational complexity and network overhead when detecting large-scale coverage hole boundary in wireless sensor network.
Performance enhancement of Underwater Wireless Sensor Networks (UWSNs)
in terms of throughput maximization, energy conservation and Bit Error Rate (BER)
minimization is a potential research area. However, limited available bandwidth, high
propagation delay, highly dynamic network topology, and high error probability leads to
performance degradation in these networks. In this regard, many cooperative communication
protocols have been developed that either investigate the physical layer or the Medium
Access Control (MAC) layer, however, the network layer is still unexplored. More
specifically, cooperative routing has not yet been jointly considered with sink mobility.
Therefore, this paper aims to enhance the network reliability and efficiency via dominating
set based cooperative routing and sink mobility. The proposed work is validated via
simulations which show relatively improved performance of our proposed work in terms
the selected performance metrics.
With the rapid development of underwater acoustic modem technology, underwater acoustic sensor networks (UWASNs) have more applications in long-term monitoring of the deployment area. In the underwater environment, the sensors are costly with limited energy. And acoustic communication medium poses new challenges, including high path loss, low bandwidth, and high energy consumption. Therefore, designing transmission mechanism to decrease energy consumption and to optimize the lifetime of UWASN becomes a significant task. This paper proposes a balance transmission mechanism, and divides the data transmission process into two phases. In the routing set-up phase, an efficient routing algorithm based on the optimum transmission distance is present to optimize the energy consumption of the UWASN. And then, a data balance transmission algorithm is introduced in the stable data transmission phase. The algorithm determines one-hop or multihop data transmission of the node to underwater sink according to the current energy level of adjacent nodes. Furthermore, detailed theoretical analysis evaluates the optimum energy levels in the UWASNs with different scales. The simulation results prove the efficiency of the BTM.
Localizing machine-type communication (MTC) devices or sensors is becoming important because of the increasing popularity of machine-to-machine (M2M) communication networks for location-based applications. These include such as health monitoring, rescue operations, vehicle tracking, and wildfire monitoring. Moreover, efficient localization approaches for sensor-based MTC devices reduce the localization error and energy consumption of MTC devices. Because sensors are used as an integral part of M2M communication networks and have achieved popularity in underwater applications, research is being conducted on sensor localization in both underwater and terrestrial M2M networks. Major challenges in designing underwater localization techniques are the lack of good radio signal propagation in underwater, sensor mobility management, and ensuring network coverage in 3D underwater M2M networks. Similarly, predicting the mobility pattern of MTC devices, trading-off energy consumption and location accuracy pose great design challenges for terrestrial localization techniques. This article presents a comprehensive survey on the current state-of-the-art research on both terrestrial and underwater localization approaches for sensor-based MTC devices. It also classifies localization approaches based on several factors, identifies their limitations with potential solutions, and compares them. Copyright © 2015 John Wiley & Sons, Ltd.
We propose forwarding-function (íµí°¹ íµí°¹) based routing protocol for underwater sensor networks (UWSNs): improved adaptive mobility of courier nodes in threshold-optimized depth-based-routing (iAMCTD). Unlike existing depth-based acoustic protocols, the proposed protocol exploits network density for time-critical applications. In order to tackle flooding, path loss, and propagation latency, we calculate optimal holding time (íµí°» íµí±) and use routing metrics: localization-free signal-to-noise ratio (LSNR), signal quality index (SQI), energy cost function (ECF), and depth-dependent function (DDF). Our proposal provides on-demand routing by formulating hard threshold (íµí°» th), soft threshold (íµí± th), and prime energy limit (íµí±
prime). Simulation results verify effectiveness and efficiency of the proposed iAMCTD.
Recently, underwater wireless sensor networks (UWSNs) have attracted much research attention from both academia and industry, in order to explore the vast underwater environment. UWSNs have peculiar characteristics; that is, they have large propagation delay, high error rate, low bandwidth, and limited energy. Therefore, designing network/routing protocols for UWSNs is very challenging. Also, in UWSNs, improving the energy efficiency is one of the most important issues since the replacement of the batteries of underwater sensor nodes is very expensive due to the unpleasant underwater environment. In this paper, we therefore propose an energy efficient routing protocol, named (energy-efficient depth-based routing protocol) EEDBR for UWSNs. EEDBR utilizes the depth of sensor nodes for forwarding data packets. Furthermore, the residual energy of sensor nodes is also taken into account in order to improve the network lifetime. Based on the comprehensive simulation using NS2, we observe that EEDBR contributes to the performance improvements in terms of the network lifetime, energy consumption, and end-to-end delay. A previous version of this paper was accepted in AST-2011 conference.
Due to the significant advances of wireless sensor networks (WSNs), researchers are eager to use this technology in the subsea applications. Because of rapid absorption of high radio frequency in the water, acoustic waves are used as communication medium, which pose new challenges, including high propagation delay, high path loss, low bandwidth, and high-energy consumption. Because of these challenges and high movement of nodes by water flow, end-to-end routing methods used in most of existing routing protocols in WSNs are not applicable to underwater environments. Therefore, new routing protocols have been developed for underwater acoustic sensor networks (UWASNs) in which most of the routing protocols take advantage of greedy routing. Due to inapplicability of global positioning system (GPS) in underwater environments, finding location information of nodes is too costly. Therefore, based on a need for location information, we divided the existing greedy routing protocols into two distinctive categories, namely, location-based and location-free protocols. In addition, location-free category is divided into two subcategories based on method of collecting essential information for greedy routing, including beacon-based and pressure-based protocols. Furthermore, a number of famous routing protocols belonging to each category are reviewed, and their advantages and disadvantages are discussed. Finally, these protocols are compared with each other based on their features.
We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. We show that the behavior of such sensor networks becomes very unstable once the first node dies, especially in the presence of node heterogeneity. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogeneity. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.
Wireless sensor networks, whether terrestrial or underwater, usually contain hundreds or in some cases thousands of micro-sensor nodes, that are randomly and densely deployed. In this paper we propose a clustering algorithm based on the geographical location of the sensor nodes for a 3-D hierarchical network architecture called LCAD. An energy model has been proposed and used to analyze the performance of the algorithm.
Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area.In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the characteristics of the underwater channel are detailed. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed and a cross-layer approach to the integration of all communication functionalities is suggested. Furthermore, open research issues are discussed and possible solution approaches are outlined.
With the advancements of acoustic modem technology that supports better data rates with reliable communications, current research focuses on algorithms those can support such technology in a better way. During the last two decades, many protocols suggested in order to handle the adverse environment of underwater communications. This continued research results in improved performance as compare to initial communication systems. But still underwater issues like limited bandwidth, high propagation delays and 3-D topology as well as power constraints of the sensor nodes are challenges for the successful routings. A series of survey papers provide an excellent comparison of such algorithms and different networking challenges during the current decade, but still a lot left to investigate. In this paper we will explore the developments of some of the important routing algorithms, and a survey with different comparisons, those have been proposed for the partially connected underwater environments. In addition, at the end we will give some future directions, which can be helpful in order to construct the algorithms for such environments.
Underwater sensor networks are attracting increasing in-terest from researchers in terrestrial radio-based sensor net-works. There are important physical, technological, and eco-nomic di erences between terrestrial and underwater sensor networks. Previous surveys have provided thorough back-ground material in underwater communications, and an in-troduction to underwater networks. This has included detail on the physical characteristics of the channel [1], on under-water acoustic communications [2, 3, 4], and surveys of un-derwater acoustic networks [5, 6, 7, 8]. In this survey, we highlight a number of important practical issues that are not emphasized in the recent surveys of underwater networks, with an intended audience of researchers who are moving from radio-based terrestrial networks into underwater net-works. We focus on issues relevant to medium access control (MAC) protocols, which are an area of continuing work both
In this paper, architectures for two-dimensional and three -dimensional underwater sensor networks are discussed. A detailed overview on the current solutions for medium access control, network, and transport layer protocols are given and open research issues are dis- cussed.
In order to prolong the network lifetime, energy-efficient protocols should be designed to adapt the characteristic of wireless sensor networks. Clustering Algorithm is a kind of key technique used to reduce energy consumption, which can increase network scalability and lifetime. This paper studies the performance of clustering algorithm in saving energy for heterogeneous wireless sensor networks. A new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks is proposed and evaluated. In the new clustering scheme, cluster-heads are elected by a probability based on the ratio between residual energy of node and the average energy of network. The high initial and residual energy nodes will have more chances to be the cluster-heads than the low energy nodes. Simulational results show that the clustering scheme provides longer lifetime and higher throughput than the current important clustering protocols in heterogeneous environments.
The design of routing protocols for Underwater Acoustic Sensor Networks (UASNs) poses many challenges due to long propagation, high mobility, limited bandwidth, multi-path and Doppler effect. Because of the void-hole caused by the uneven distribution of nodes and sparse deployment, the selection of next hop forwarding nodes only based on the state of current node may result in the failure of forwarding in the local sparse region. In order to reduce the probability of encountering void holes in the sparse networks, in this paper we present weighting depth and forwarding area division DBR routing protocol, called WDFAD-DBR. The novelties of WDFAD-DBR lie in: firstly, next forwarding nodes are selected according to the weighting sum of depth difference of two hops, which considers not only the current depth but also the depth of expected next hop. In this way, the probability of meeting void holes is effectively reduced. Secondly, the mechanisms for forwarding area division and neighbor node prediction are designed to reduce the energy consumption caused by duplicated packets and neighbors' requests, respectively. Thirdly, we make theoretical analyses on routing performance in case of considering channel contending with respect to delivery ratio, energy consumption and average end-to-end delay. Finally we conduct extensive simulations using NS-3 simulator to verify the effectiveness and validity of WDFAD-DBR.
In this paper, we analyze performance of famous cluster based routing protocols and identify the factors affecting energy consumption in wireless sensor networks. From theoretical and experimental analysis, it is observed that communication distance and cluster node density are the major sources in the formation of energy and coverage holes. To overcome these deficiencies, we propose a new hybrid approach of static clustering and dynamic selection of cluster heads. We also conduct a comprehensive energy consumption analysis of our technique with selected existing ones. Simulation results show that the proposed technique is relatively better in terms of energy holes minimization and network lifetime prolongation.
In Wireless Sensor Networks (WSNs), Sensor nodes (nodes) are equipped with limited energy source. Therefore, efficient energy utilization of nodes has become a hot research area in WSNs. In this paper, we introduce a new routing technique for WSNs in which, we solve the problem of unbalanced energy utilization, which causes energy and coverage holes in WSNs. Deployment area is divided into subareas; each subarea logically represents a static cluster. Dividing network field into subfields helps to control coverage hole problem whereas, static clustering helps to avoid energy hole problem. Mathematical formulation of the proposed work is provided to analyse and verify our technique. Simulation results show that our technique balances energy utilization of the network.
The performance of Underwater Sensor Networks (UWSNs) can be severely affected by the dynamics of underwater environment. A surface sink is usually deployed at a pre-specified location to maximize one or more performance metrics. However, when the network is dynamic, a redeployment of surface sink should be considered to reduce the effect of mobility on the network performance. Redeployment can be done periodically, at times based on a mobility prediction models, or adaptively based on performance degradation. Unnecessary redeployment can result from using the periodic or prediction based redeployment. In this paper we present an adaptive dynamic sink redeployment strategy that enforces redeployment only if a reduction in energy consumption is guaranteed. The redeployment decision is based on routing information collected at the surface sink throughout network operation. We use a location unaware routing protocol “adaptive power controlled routing protocol” as the underlying routing strategy. When the mobility of the network is not severe, nodes tend to use a fixed power level to communicate with neighboring nodes or surface sink. However, if more nodes are switching to use higher power levels for communication and the energy consumption is increased a sink redeployment procedure is started. Surface sink then triggers localization and finds the optimal new location of surface sink to minimize total energy consumption. Simulation results show that adaptive sink redeployment achieves a considerable reduction in energy consumption.
The energy efficiency is an important issue for employ distributed wireless sensor networks in smart space and extreme environments. The cluster-based communication protocols play a considerable role for energy saving in hierarchical wireless sensor networks. In most of traditional clustering algorithms, a cluster head (CH) simultaneously serves as a relay sensor node to transmit its cluster/other clusters data packet(s) to the data sink. As a result, each node would have CH role as many as relay role during network lifetime. In our view, this is inefficient from an energy efficiency perspective because in lots of cases, a node due to its position in the network comparatively is more proper to work as a CH and/a relay. This paper proposes a new distributed algorithm named scalable energy efficient clustering hierarchy (SEECH), which selects CHs and relays separately and based on nodes eligibilities. In this way, high and low degree nodes are, respectively, employed as CHs and relays. In only a few past researches, CHs and relays are different, but their goal was mainly mitigation of CHs energy burden which is intrinsically satisfied by the proposed mechanism. To consider uniformity of CHs to balance clusters, SEECH uses a new distance-based algorithm. Comparisons with LEACH and TCAC protocols show obvious better performance of SEECH in term of lifetime. To evaluate the scalability of SEECH strategy, simulations are conducted in three different network size scenarios.
Regarding energy efficiency in Wireless Sensor Net-works (WSNs), routing protocols are engaged in a playful manner suggesting a consciousness of high value. In this research work, we present Away Cluster Heads with Adaptive Clustering Habit ((ACH) 2) scheme for WSNs. Our proposed scheme increases the stability period, network lifetime and throughput of the WSN. The beauty of our proposed scheme is its away Cluster Heads (CHs) formation, and free association mechanisms. The (ACH) 2 controls the CHs' election and selection in such a way that uniform load on CHs is ensured. On the other hand, free association mechanism removes back transmissions. Thus, the scheme operations minimize the over all energy consumption of the network. In subject to throughput maximization, a linear programming based mathematical formulation is carried out in which the induced subproblem of bandwidth allocation is solved by mixed-bias resource allocation scheme. We implement (ACH) 2 scheme, by varying node density and initial energy of nodes in homogeneous, heterogeneous, reactive and proactive simulation environments. Results justify its applicability.
Recent advances in micromanufacturing technology have enabled the development of low-cost, low-power, multifunctional sensor nodes for wireless communication. Diverse sensing applications have also become a reality as a result. These include environmental monitoring, intrusion detection, battlefield surveillance, and so on. In a wireless sensor network (WSN), how to conserve the limited power resources of sensors to extend the network lifetime of the WSN as long as possible while performing the sensing and sensed data reporting tasks, is the most critical issue in the network design. In a WSN, sensor nodes deliver sensed data back to the sink via multihopping. The sensor nodes near the sink will generally consume more battery power than others; consequently, these nodes will quickly drain out their battery energy and shorten the network lifetime of the WSN. Sink relocation is an efficient network lifetime extension method, which avoids consuming too much battery energy for a specific group of sensor nodes. In this paper, we propose a moving strategy called energy-aware sink relocation (EASR) for mobile sinks in WSNs. The proposed mechanism uses information related to the residual battery energy of sensor nodes to adaptively adjust the transmission range of sensor nodes and the relocating scheme for the sink. Some theoretical and numerical analyze are given to show that the EASR method can extend the network lifetime of the WSN significantly.
Based on LEACH algorithm, we propose an improved HMR-LEACH algorithm (Hierarchical Multi-path Routing-LEACH), which improves election of cluster head and adopts multi-hop algorithm instead of one hop to transmission data. When chooses transmission path, HMR-LEACH algorithm takes energy and distance into account and assigns a probability to each transmitting path by weight. Simulation result indicates that HMR-LEACH outperforms the LEACH algorithm and prolongs the life of the network dramatically.
Wireless sensor networks (WSNs) are composed of a large number of inexpensive power-constrained wireless sensor nodes, which detect and monitor physical parameters around them through self-organization. Utilizing clustering algorithms to form a hierarchical network topology is a common method of implementing network management and data aggregation in WSNs. Assuming that the residual energy of nodes follows the random distribution, we propose a load-balanced clustering algorithm for WSNs on the basis of their distance and density distribution, making it essentially different from the previous clustering algorithms. Simulated tests indicate that the new algorithm can build more balanceable clustering structure and enhance the network life cycle.
Compared to land-based sensor networks, Underwater Acoustic Sensor Networks have several new challenges, such as dynamic topology, limited network lifetime. To achieve long network lifetime, existing researches use clustering method to assure energy-efficiency. However, nodes far away from sink are easily to exhaust energy due to directly communication with sink. Besides, in HEED protocol, the nodes must be location-aware in order to communicate with the sink node. However, GPS radio receivers cannot function properly in underwater situation. Moreover, in industry, homogenous nodes with identical hardware are more welcomed concerning manufacture efforts and costs. In this paper, we provide a new homogeneous, dynamic topology adaptive, multi-hop routing protocol LUM-HEED (Location Unaware Multi-hop based on HEED) which suits for the real underwater situation and is more convenient and economic in industry application. Simulation results show that this protocol can prolong network lifetime and balance network traffic.
The design of routing protocols for Underwater Wireless Sensor Networks (UWSNs) poses many challenges due to the intrinsic
properties of underwater environments. In this paper we present DUCS (Distributed Underwater Clustering Scheme), a new GPS-free
routing protocol that does not use flooding techniques, minimizes the proactive routing message exchange and uses data aggregation
to eliminate redundant information. Besides, DUCS assumes random node mobility and compensates the high propagation delays
of the underwater medium using a continually adjusted timing advance combined with guard time values to minimize data loss.
The theoretical and simulation studies carried out demonstrate its effectiveness.
KeywordsAcoustic communications–Routing–Energy efficiency–Underwater networking
In this paper, we study the node clustering problem in underwater sensor networks (UWSNs). We formulate the problem into a cluster-centric cost-based optimization problem with an objective to improve the energy efficiency and prolong the lifetime of the network. For this purpose, a cost metric is defined for a potential cluster, which takes into account three important parameters that are relevant to the energy status of the cluster, including (1) the total energy consumption of the cluster members for sending data to the cluster head; (2) the residual energy of the cluster head and its cluster members; and (3) the relative location between the cluster head and the underwater sink (uw-sink). To solve the formulated problem, a novel distributed clustering protocol called minimum-cost clustering protocol (MCCP) is proposed, which selects a set of non-overlapping clusters from all potential clusters based on the cost metric assigned to each potential cluster and attempts to minimize the overall cost of the selected clusters. MCCP can adapt geographical cluster head distribution to the traffic pattern in the network and thus avoid the formation of hot spots around the uw-sink. It can also balance the traffic load between cluster heads and cluster members through periodical re-clustering the sensor nodes in the network. Simulation results show that MCCP significantly improves the energy efficiency and the lifetime of a UWSN as compared with the well-known HEED protocol.
Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
The clustering Algorithm is a kind of key technique used to reduce energy consumption. It can increase the scalability and lifetime of the network. Energy-efficient clustering protocols should be designed for the characteristic of heterogeneous wireless sensor networks. We propose and evaluate a new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks, which is called DEEC. In DEEC, the cluster-heads are elected by a probability based on the ratio between residual energy of each node and the average energy of the network. The epochs of being cluster-heads for nodes are different according to their initial and residual energy. The nodes with high initial and residual energy will have more chances to be the cluster-heads than the nodes with low energy. Finally, the simulation results show that DEEC achieves longer lifetime and more effective messages than current important clustering protocols in heterogeneous environments.
Providing scalable and ecient routing services in underwater sensor net- works (UWSNs) is very challenging due to the unique characteristics of UWSNs. Firstly, UWSNs often employ acoustic channels for communications because radio signals do not work well in water. Compared with radio-frequency channels, acous- tic channels feature much lower bandwidths and several orders of magnitudes longer propagation delays. Secondly, UWSNs usually have very dynamic topology as sen- sors move passively with water currents. Some routing protocols have been proposed to address the challenging problem in UWSNs. However, most of them assume that the full-dimensional location information of all sensor nodes in a network is known in prior through a localization process, which is yet another challenging issue to be solved in UWSNs. In this paper, we propose a depth-based routing (DBR) protocol. DBR does not require full-dimensional location information of sensor nodes. Instead, it needs only local depth information, which can be easily obtained with an inex- pensive depth sensor that can be equipped in every underwater sensor node. A key advantage of our protocol is that it can handle network dynamics eciently with- out the assistance of a localization service. Moreover, our routing protocol can take advantage of a multiple-sink underwater sensor network architecture without intro- ducing extra cost. We conduct extensive simulations. The results show that DBR can achieve very high packet delivery ratios (at least 95%) for dense networks with only small communication cost.
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