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Energy Consumption Model for Density Controlled Divide-and-Rule Scheme for Energy Efficient Routing in Wireless Sensor Networks
Abstract
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 phenomena of quick energy consumption of a sensor node due to unbalanced load of data forwarding is called energy hole. The energy hole problem causes death of a sensor node earlier than other nodes which creates a coverage hole due to which the area of this sensor node remains unobserved or un-sensed [11]. In addition, underwater sensor nodes are large in size so, sensor nodes are deployed with the help of ships, which is costly. ...
... Latif, Kamran,et al., presented a clustering technique at routing layer for terrestrial wireless sensor networks called density controlled divide-and-rule (DDR) [11]. DDR have constant number of CHs in each round and it is based on static clustering.In DDR, the network field is divided into logical segments in order to reduce communication distance between sensor node to CH and between CH to sink(s). ...
... The value of W is calculated from total width of the network field. Equation (11) calculates the value of W . In equation (12), we calculate the value of B from breadth of the network field. ...
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.
... A group of sensor nodes is termed as a cluster and each cluster is having a cluster head (CH). A CH is chosen on the basis of many different parameters like its proximity to all the other nodes of the cluster, its residual energy, distance from the BS, and many more [3]. In a cluster, each and every node senses the data. ...
... Than these squares further divided into subparts. To further divide the network we take top right and bottom right corners of inner square as reference point and by adding d in x-coordinate of the upper right corner ݔ( ଷ + ݀, ݕ ଷ ) and y-coordinates of bottom right corner ݔ( ଷ , ݕ ଷ + ݀), we get new region S1.Similarly new regions are created using co-ordinates of concentric squares[3]. ...
... This is due to the fact that nodes in a certain region can communicate only with the cluster heads of their own regions, though the cluster heads of the neighbouring regions might be closer to the node transmitting. Density controlled Divide-and-Rule (DDR) is proposed in [41]. It is similar to the scheme in [40] in certain aspects. ...
... Since physical medium is not always ideal, routing protocols capable of reducing the energy consumption of a network are required. Among various approaches of reducing the energy consumption, deployment of the network also plays a very important role [41]. Deploying all the nodes in a manner such that minimum computation is required of the routing protocol along with a minimal delay and less energy consumption can be helpful. ...
Wireless sensor networks (WSNs) have found numerous applications in control and monitoring field. Advancements in the field of electronics has made wireless sensors economical enough to be widely used. Wireless sensor networks have found wide applications in defense, agriculture, seismic monitoring, health sector, urban area monitoring etc. The battery life of nodes in such networks is a constraint. Routing algorithms chosen for WSNs should make sure that energy consumption of nodes is minimized. Geographic routing is one of the options. It can be used in large scale networks owing to its low energy consumption properties. It also gives low overhead. Geographic routing comes with an inherent defect of location errors. Location errors impair the performance of geographic routing.
Underwater sensor networks (UWSNs) is a widely studied area. It has catalyzed the underwater exploration to numerous folds owing to its ease of deployment and maintenance compared to its wired competitor. Due to nature of the underwater environment and medium of communication, achieving energy and data efficiency in UWSNs is a challenge. To solve this problem, routing protocols tailored to be energy and data efficient are required.
In this thesis two geographic protocols are presented. One for the terrestrial wireless sensor networks and the other for underwater wireless sensor networks namely Enhanced Energy Conditioned Mean Square Error Algorithm (E-ECMSE) and GEOgraphic routing with Depth Adjustment-based topology control for communication Recovery over void regions both of them decrease energy consumption in WSNs.
... The dual CH selection mechanism was used and enhanced the performance of the network system. In Latif et al., 2016, in a large network area, the authors proposed a routing strategy to reduce node energy usage inside the network. The protocol self-adjusts the node's power for a small distant node within the area and improves the system's performance. ...
With enormous evolution in Microelectronics, Wireless Sensor Networks (WSNs) have played a vital role in every aspect of daily life. Technological advancement has led to new ways of thinking and of developing infrastructure for sensing, monitoring, and computational tasks. The sensor network constitutes multiple sensor nodes for monitoring, tracking, and surveillance of remote objects in the network area. Battery replacement and recharging are almost impossible; therefore, the aim is to develop an efficient routing protocol for the sensor network. The Fuzzy Based Cluster Head Selection (FBCHS) protocol is proposed, which partitions the network into several regions based on node energy levels. The proposed protocol uses an artificial intelligence technique to select the Cluster Head (CH) based on maximum node Residual Energy (RE) and minimum distance. The transmission of data to the Base Station (BS) is accomplished via static clustering and the hybrid routing technique. The simulation results of the FBCHS protocol are com- pared to the SEP protocol and show improvement in the stability period and improved overall performance of the network.
... Therefore, domestic and aboard scholars have intensely studied to settle this problem. Latif et al. [4] improved LEACH protocol and designed a centralized clustering protocol LEACH-C, which solved the problem of LEACH randomly selecting CHs, but the single-hop communication between the CHs and BS would accelerate the EC of the CHs, leading to their premature death, thereby shortening the network lifetime. Zhang [5] designed a K-means based uniform clustering routing algorithm, where the nodes could select the CHs according to their position and remaining energy. ...
Faced with the problems of unbalanced energy consumption (EC) and short lifetime of nodes in Wireless Sensor Networks (WSN), a Low Energy Adaptive Clustering Hierarchy (LEACH) clustering routing protocol based on energy balance, namely LEACH-EB (LEACH Based on Energy Balance) protocol was proposed. At the initial selection stage, the nodes which are close to the base station (BS) with great remaining energy and many neighbor nodes are selected as the cluster heads (CHs); then, the non-CH nodes enter the clusters which have the least costs based on the strength and remaining energy of the communication signals between themselves and different CHs. At the data transmission stage, if the CH which sends the information is one hop away from BS, the CH needs to select a neighbor CH with the largest forwarding probability as the next hop relay node based on the remaining energy of each neighbor CH, the number of nodes in the cluster, and the distance from BS. The selected neighbor CH continues to determine the next hop in the above manner until the data is successfully sent to BS. Simulation tests show that LEACH-EB protocol can receive more data and extend the network life cycle by 60%, 43.1%, and 13.36% compared with LEACH, LEACH-C, and FIGWO, respectively.
... [1]. Moreover, it helps to split the network region into sub-areas, which happens if other portions of the network field are not accessible to sensor nodes [2]. The best usage can be made of a WSN in remote places where human activity is difficult. ...
Over recent decades, both scientific and commercial societies have been seeing the progress of wireless sensor networks (WSNs). Clustering is the most common form of growing WSN lifetime. The optimal number of cluster heads (CHs) & structure of clusters are the main problems in clustering techniques. The paper focuses on an efficient CH preference mechanism that rotates CH between nodes amid a greater energy level than others. Original energy, residual energy as well as the optimum value of CHs is assumed to be used by the algo for the choice of the next category of IoT-capable network cluster heads including ecosystem control, smart cities, or devices. The updated version of K-medium algo k-means++. Meanwhile, Simulated Annealing is implemented as the shortest path tree for mobile nodes which is constructed to establish the connection between the nodes for finding the shortest and secure path for data transmission hence resulting in faster data sending and receiving process. Keywords: WSN, CH selection, Residual energy (RE), Network Lifetime, Energy-efficient (EE)
... Energy consumption model for density controlled divide-and-rule scheme for energy efficient routing is introduced by K. Latif et al. [14]. In this protocol, self-adjustment of node power on the basis of transmission range is small. ...
Nowadays, the energy consumption has become one of the major constraints for the sensor nodes having a finite energy source in the design of Wireless sensor networks (WSNs). In this paper, a new routing concept using divide-and-rule sectorization (DRS) scheme has been proposed to curtail the energy efficiency issues in WSNs. In this scheme, each forwarder node is dynamically selected for WSNs which balances the energy consumption among the sensor nodes significantly. The network area is divided into subareas to reduce the unbalance loading condition, and each subarea known as the segment, efficiently decrease the energy hole creation problem of the network. Moreover, the analytical analysis of the energy consumption for the proposed scheme has also been presented. The simulation results confirm that the proposed DRS scheme has better enduring stability, prolonging network lifetime, and minimized energy consumption as compared to available state-of-the-arts.
... In GIR, we introduce the concept of virtual currency, and the buyer and seller nodes went through multiple rounds of bargaining games [43] to bring their respective interests to Nash equilibrium [44]. We use the link degree of the node, the energy [45] of the node and the attribute of the message as the influence factors of the message pricing, so that we can find the relay node that is most suitable as the relay message in the communication range of the buyer node. By comparing with Epidemic, EPSR, MINEIRO and ICRP, we found that under the same conditions, the delivery rate of GIR is 7% higher than ICRP, 13% higher than Epidemic, and the average delay is lower than EPSR, MINEIRO and ICRP. ...
A large number of routing algorithms in Opportunistic Networks are based on the assumption that nodes are free to help other nodes forward messages. However, when the Opportunistic Network is applied to an urban environment, the nodes will have certain social attributes. In many cases, a node can decide whether to execute the routing policy or not. Due to the limited resources and poor social relationships, nodes may be unwilling to forward messages from other nodes and have strong motivation to implement selfish policies. As a result, increased network latency reduces message delivery rates and affects the overall network performance. In order to solve this problem, we propose a perceptual routing protocol to promote node cooperation from the perspective of game theory. Specifically, We introduce the concept of virtual currency and construct a price function, and nodes can obtain a certain virtual currency through cooperation. In the process of message forwarding, we consider the change of link degree and energy of node (the energy exists in the form of electricity in this article), and use them as factors of the trading node quotation. The trading node finally makes it through the multiple rounds of bargaining games, so that the proposed game between both sides reaches the Nash equilibrium. Experiments show that the algorithm outperforms Epidemic, EPSR, MINEIRO and ICRP algorithms in terms of delivery rate, average latency and energy consumption. According to the simulation experiments, the average delivery ratio of GIR algorithm is 0.68, which is 13% higher than that of the epidemic algorithm. In terms of average delay, 7% is better than ICRP algorithm.
... The LEACH-C algorithm proposed in reference [18] is based on the improved LEACH algorithm. The algorithm adds a control mechanism in the cluster head election, so that the nodes of the elected cluster head not only rely on the probability function, but also ensure that the cluster heads are more reasonably dispersed throughout the network. ...
Low-energy adaptive clustering routing protocol is a low-power adaptive hierarchical routing protocol designed for IoT, which has the function of extending network life time. In order to balance the energy consumption of wireless sensor network nodes and extend the life cycle of the whole network, the cluster heads are randomly selected in the classical clustering LEACH algorithm of the wireless sensor network of the Internet of Things, and the residual energy, node position and node density of the nodes are not considered. The problem is solved by the research of LEACH protocol, the selection of cluster head and the communication mechanism between cluster head and Sink. An improved clustering routing algorithm of LEACH protocol is proposed. The simulation experiment proves that the improved LEACH algorithm has more energy consumption than the comparison algorithm, the lowest power consumption of the cluster head node, and better network connectivity and reliability.
... Coverage holes increase the energy consumption and degrade the network operational life time. In [2], authors work for terrestrial WSNs by reducing the coverage hole problem. In this work, divide-and-concur-rule is used in proposed scheme. ...
Wireless Sensor Networks (WSNs) are facing different challenges in the routing procedure. Cost efficiency, low energy consumption and reliable data communication between nodes are the major challenges in the field of WSNs. During the transmission process of nodes, energy is also lost due to void holes. In the WSNs, location error and battery consumption are inevitable, while the loss of data packets and the maximum usage of energy degrade the performance of the network, significantly. Different energy conservation methods are used in different routing protocols. In this paper, two routing protocols are proposed for maximum stability of the network by avoiding void holes. Furthermore, the proposed protocols are compared with the state-of-art protocols to show their productiveness. A major part of the energy is consumed due to the creation of void holes and imbalance network deployment. In this work, the concept of location error is also introduced for improving the efficiency of our work. Simulations are performed in order to check the effectiveness of our proposed schemes and results show that our proposed routing schemes outperform the comparing ones.
... However, sleep and wake is unsuitable for time critical data. Density controlled Divide and rule scheme for sensor network with tired architecture (Latif et al., 2016) cannot be extended since it has been implemented with static clustering as the architecture is unappreciable for sensors with mobility. ...
In this research, the focus lies on estimating the network lifetime in wireless sensor networks with the aid of directional antenna. Two protocols are being proposed the (NLKM) network lifetime with Kaplan-Meier and (NLNPM) network lifetime with non-parametric model. In NLKM estimates where a control packet calculates all the sensor residual energy and decides whether to transmit or not based the residual energy. The directional antenna is used to avoid forwarding of packets in all direction and focus on the direction towards the destination and increasing its communication range based on dead nodes. In the second protocol NLNPM is similar to the operation where the residual energy is calculated with two thresholds dead and almost dead. This NLNPM-based protocol with censoring there by overcomes the limitation of empirical distribution of Kaplan-Meier analysis. Both protocols were simulated in ns2 simulator and compared for network lifetime. Reference to this paper should be made as follows: Saravanan, G. and Rangachar, M.J.S. (2018) 'Network lifetime estimation of wireless sensor networks using communication protocols with non-parametric models', Int.
... Routing is considered based on location rather than considering the residual energy of CH. Density controlled divide and rule scheme for energy efficient routing in wireless sensor networks (DDR) [11] is another clustering scheme which divides the geographic area into equidistant concentric squares and are subdivided into four equal rectangles. It suffers with the problem of uneven cluster size and data dissemination issue. ...
Wireless sensor networks (WSNs) have become essential and useful in wide variety real time applications. Since the nodes in a sensor network are limited by energy, prolonging the life time of the network is a major challenge in the design of WSN. Radio transmission requires more power and the limited energy of nodes should be conserved while communication or message passing. The effective way to accomplish this is through clustering techniques. This paper proposes a track sector tree based clustering scheme (TSTCS) which considers the network region as concentric circles with tracks and sectors. Tree structured clusters are formed and communication between sink and CH is performed with optimal energy cost. It also provides local remedy for energy suffering cluster heads by substitution technique. Extensive simulations are done and the performance of TSTCS is compared with the latest clustering algorithms for WSN.
... There are several reasons to apply clustering techniques in WSNs such as increased scalability, less load, less energy consumption, latency reduction, collision avoidance, guarantee of connectivity, fault tolerance, load balancing, energy hole avoidance and increasing network lifetime [1]. In addition, dividing the network area into subareas helps control the coverage hole problem [2], which appears whenever some parts of the network areas are not covered by any sensor nodes. protocol in order to determine the optimal cluster size by minimizing the distance between member nodes and CHs and decreasing the energy consumption of the network. ...
Network lifetime and energy efficiency are crucial performance metrics used to evaluate
wireless sensor networks (WSNs). Decreasing and balancing the energy consumption of nodes can be
employed to increase network lifetime. In cluster-based WSNs, one objective of applying clustering
is to decrease the energy consumption of the network. In fact, the clustering technique will be
considered effective if the energy consumed by sensor nodes decreases after applying clustering,
however, this aim will not be achieved if the cluster size is not properly chosen. Therefore, in this
paper, the energy consumption of nodes, before clustering, is considered to determine the optimal
cluster size. A two-stage Genetic Algorithm (GA) is employed to determine the optimal interval of
cluster size and derive the exact value from the interval. Furthermore, the energy hole is an inherent
problem which leads to a remarkable decrease in the network’s lifespan. This problem stems from
the asynchronous energy depletion of nodes located in different layers of the network. For this
reason, we propose Circular Motion of Mobile-Sink with Varied Velocity Algorithm (CM2SV2) to
balance the energy consumption ratio of cluster heads (CH). According to the results, these strategies
could largely increase the network’s lifetime by decreasing the energy consumption of sensors and
balancing the energy consumption among CHs.
... Thus, nearer sensor nodes consume more energy and die at a faster rate as compared to distant ones. Latif et al. (2016) presented a new technique based on static clustering with the constant number of CHs in each round for WSNs, namely DDR. DDR technique divides network field into segments to avoid energy hole problem. ...
Wireless sensors networks (WSNs) are realised as one of the most promising networking types that bridge the gap between the cyber and the things. Designing of routing protocols for WSNs is a challenging issue since sensors are mostly limited in energy and data processing. In this paper, we present a new routing technique for hierarchical routing protocols to enhance energy efficiency in WSNs, namely Routing-Gi. This technique divides network area into the inner grid and clustered grids. In an inner grid, the nodes transmit directly data to the base station (BS), whereas, in clustered grid, the nodes are organised into micro-grids and thus each node transmits data to the BS through it respective cluster head. in this case, the micro-grids help to avoid unbalanced energy consumption in WSNs. Thus, the workload is evenly distributed on nodes causing the efficient energy of network to enhance. The simulation results prove the effectiveness of our technique.
... Authors in [17], proposed a divide-and-rule scheme which reduces the coverage holes problem in terrestrial WSN. This scheme operates in 3-tier communication architecture. ...
In this paper, we propose an algorithm to alleviate coverage hole problem using geographic routing strategy for wireless sensor networks (WSNs). In order to accomplish desired results, an optimal number of forwarder nodes is computed along with the selection of path that has minimum energy consumption. Moreover, at each hop residual energy of a sensor is calculated and knowledge up-to one hop neighbors of forwarder node that ensures the avoidance of energy hole problem. Simulations are conducted to validate that our claim of outperforming compared existing schemes in terms of packet delivery ratio (PDR) and energy dissipation of the network nodes.
... Thus, nearer sensor nodes consume more energy and die at a faster rate as compared to distant ones. Latif et al. (2016) presented a new technique based on static clustering with the constant number of CHs in each round for WSNs, namely DDR. DDR technique divides network field into segments to avoid energy hole problem. ...
Abstract: Wireless Sensors Networks (WSNs) have been realized as one of the most
promising networking types that bridge the gap between the cyber and the things.
Designing routing protocols for WSNs is a challenging issue since sensors are mostly
limited in their energy level, data processing, and sensing ability. In this paper, we present
the new routing technique for hierarchical routing protocols to enhance network lifetime
and energy e�ciency in WSNs, namely Routing-Gi technique. This technique divides
network area into the inner grid and clustered grids. The nodes in inner grid transmit
directly data to base station (BS), whereas, in clustered grid, the nodes are organised into
micro-grids and thus each node transmits data to the BS through it respective cluster
head (CH). In this case, the workload on CHs is decreased. Thus, CHs consume less
energy causing the residual energy of network to increase. The simulation results show
that this newly proposed protocols are e�cient than other existing protocols.
Clustering is an efficient technique to organize network resources efficiently and, in wireless sensor Networks (WSNs) communications it is used to group sensors with similar characteristics managed by a selected sensor called a Cluster Head (CH). Thus, this paper presents a new approach, namely Energy-Aware Clustering and Efficient Cluster Head Selection (EAC-ECHS) to optimize the performances of WSNs in terms of the network lifetime and enhance energy consumption. In EAC-ECHS, the sensor network is divided into an inter grid and fair clustered Grids. Furthermore, for each clustered Grid, the CH selection is based on the residual energy of sensor, distance to neighbors, and distance to the base station. Simulation experiments have been conducted to examine the performance of EAC-ECHS and previous approaches, and the results demonstrate that EAC-ECHS approach achieves the design objectives in terms energy consumption, network lifetime, and packet delivery ratio.
The high energy density of solar makes outdoor application of wireless sensor networks (WSNs) possible. In recent years, some advanced technologies have emerged in solar WSNs. However, there are still some problems: (1) existing energy prediction algorithms are difficult to deploy in scenarios with many small nodes in different locations; (2) how and when to adjust network topology. To solve the two problems, this paper proposes a solar WSN adaptation framework (SWAF). SWAF includes the proposed shadow judgment method (SJM) based on geographic and geometric theories and the solar-aware routing strategy (SAR) based on integer programming. SJM is a key adaptation algorithm that facilitates the integration of existing prediction techniques and enables the solar WSN to be deployed in practice. SAR is modeled with the goal of reducing node mortality. The AKS-based algorithm is introduced to cope with the expansion of network scales. Experimental results show that SJM can improve the accuracy by 20%-50%. The further introduction of SAR can prolong network lifetime by 12%-35%.
Energy provisioning plays a key role in the sustainable operations of Wireless Sensor Networks (WSNs). Recent efforts deploy multi-source energy harvesting sensors to utilize ambient energy. Meanwhile, wireless charging is a reliable energy source not affected by spatial-temporal ambient dynamics. This article integrates multiple energy provisioning strategies and adaptive adjustment to accomplish self-sustainability under complex weather conditions. We design and optimize a three-tier framework with the first two tiers focusing on the planning problems of sensors with various types and distributed energy storage powered by environmental energy. Then we schedule the Mobile Chargers (MC) between different charging activities and propose an efficient, 4-factor approximation algorithm. Finally, we adaptively adjust the algorithms to capture real-time energy profiles and jointly optimize those correlated modules. Our extensive simulations demonstrate significant improvement of network lifetime ( ), increase of harvested energy (15%), reduction of network cost (30%), and the charging capability of MC by 100%.
This article focuses on the most common application scenarios for data collection and uploading in WSN (Wireless Sensor Networks). First, we measure the energy consumption of widely used hardware. According to the characteristics of transmission energy consumption, a MIP (mixed integer programming) model called FAT-WSN (fragmentation aggregation transmission WSN) is proposed to minimize the number of data fragments. Moreover, we propose an iterative solution for this MIP problem with elasticity and low complexity. The main optimization method for this model is to adjust topology and traffic distribution. It focuses on optimizing the number of data transfers without modifying any data and without introducing a compression calculation burden. Finally, simulation and small-scale real node verifications are performed for the FAT-WSN scheme. The experimental results show that FAT-WSN can effectively reduce the number of data transmission and reception, thereby reducing energy consumption and improving network life. Compared with the MinST model, JGDC (Jointly Gaussian Distributed Compress) model and AMREST (Approximately Maximum min-Residual Energy Steiner Tree) model, the network life can be increased by 10%-30% without extending the calculation time.
Reducing the energy consumption of the wireless sensor network is an effective way to extend the lifetime of the wireless sensor network. This paper proposes a real-time routing protocol RRPBLC that combines location information and clustering technology. By dividing the monitoring area into cells, each cell is composed of a cluster, and the method of mixing cluster head elections and dynamically adjusting the forwarding transmission rate is adopted. The simulation results show that the clustering algorithm and cluster head election algorithm designed in this paper have good performance in balancing node load, which not only avoids the problem of “hot zone”, but also makes the node energy consumption uniform. At the same time, the performance of the algorithm in response to network performance degradation caused by node failure is also outstanding, even if 50% of nodes fail. The algorithm can still guarantee reliable monitoring data from the network, so it can greatly extend the network life cycle. The protocol not only can achieve energy balance of the network, extend the life cycle of the network, and has better real-time performance.
Insulation condition monitoring is essential for the safety of our distribution power gird. However, the traditional monitoring solution is hardly applied due to the concerns arise from natures of distribution grid, such as complex feeder networks, massive operation site and high economic benefit. In this paper, a wireless sensing network based on IoT technology is demonstrated for insulation condition perception. First of all, the general framework of the wireless sensing network is designed with considerations on extendibility and accessibility. Next, it goes into detail about the technical requirements of the essential units of the sensing network including sensor node, power management and data communication. With this concept, two practical cases of IoT-based partial discharge sensing networks realized on the switchgear cabinet and power cable are presented with details involving the design of TEV and HFCT sensor nodes, the energy consumption, Lora/NB-IoT-based network structures and data usage strategies. This IoT-based insulation condition monitoring is proven to be applicable for the distribution grid and expected to be references for more possible IoT applications.
Due to limited power supplies, the sensor nodes exhaust their energy eventually. Accordingly, data transmission mechanisms between nodes and their destinations need to be designed based on energy efficiency. Most of the existing cluster based schemes adopt direct data transmission manner for intra-cluster communication, which leads to the unbalanced energy consumption of, Nodes (MN) and results in coverage holes in the network. Several Mobile Sink (MS) based schemes focus exclusively on optimizing the sojourn locations of MS to balance the energy consumption among sensor nodes. However, in most of them, MS stays at only one location within a cluster which leads to the unbalanced energy consumption of MNs. Furthermore, the time limitation for balancing the energy consumption of nodes has not been considered in previous schemes, which results in reduced the network performance. In this paper, Energy-Efficient Intra-cluster Routing (EIR) algorithm is proposed to balance the energy consumption of MNs during a limited time, which leads to enhancing the coverage time of the network. In the proposed scheme, upon arriving the MS to a cluster, the optimal sojourn locations is determined with respect to allocated sojourn time to the cluster in such a way that moving the MS along these locations leads to balancing energy consumption among MNs. Based on simulation results, EIR remarkably increases the network performance in terms of different performance evaluation metrics.
Wireless sensor networks have been widely used in target monitoring application. It is often assumed in a typical target coverage algorithm that the environment is known, and each target is covered by only one node. However, these algorithms are not scalable. In fact, one target may need to be covered by more than one node, which is the K-coverage problem. Aiming at the application of target monitoring in wireless sensor network, a K-coverage model— kernal matrix based genetic algorithm (KMGA) based on the genetic algorithm—is proposed. The KMGA model ensures that each target is covered by multiple sensors simultaneously. First, multiple Covers are generated as much as possible through genetic algorithm, and then, while coverage requirements are ensured, coverage between Covers is switched based on remaining energies of nodes so as to extend the network life. Experimental data show that the proposed KMGA model can effectively extend the network lifetime and ensure coverage rate.
Due to limited energy resources, energy balancing becomes an appealing requirement/ challenge in Underwater Wireless Sensor Networks (UWSNs). In this paper, we present a Balanced Load Distribution (BLOAD) scheme to avoid energy holes created due to unbalanced energy consumption in UWSNs. Our proposed scheme prolongs the stability period and lifetime of the UWSNs. In BLOAD scheme, data (generated plus received) of underwater sensor nodes is divided into fractions. The transmission range of each sensor node is logically adjusted for evenly distributing the data fractions among the next hop neighbor nodes. Another distinct feature of BLOAD scheme is that each sensor node in the network sends a fraction of data directly to the sink by adjusting its transmission range and continuously reports data to the sink till its death even if an energy hole is created in its next hop region. We implement the BLOAD scheme, by varying the fractions of data using adjustable transmission ranges in homogeneous and heterogeneous simulation environments. Simulation results show that the BLOAD scheme outperforms the selected existing schemes in terms of stability period and network lifetime.
Wireless Sensor Networks (WSNs) have found numerous applications in control and monitoring fields. Advancements in the field of electronics have made wireless sensors economical enough to be widely used. WSNs have found wide applications in defence, agriculture, seismic monitoring, health sector, urban area monitoring, etc. The battery life of nodes in such networks is a constraint. Routing algorithms chosen for WSNs should make sure that energy consumption of nodes is minimized. Geographic routing is one of the options. It can be used in large scale networks owing to its low energy consumption properties. It also gives low overhead. Geographic routing comes with an inherent defect of location errors. Location errors impair the performance of geographic routing. In this paper a protocol Enhanced Energy Conditioned Mean Square Error Algorithm (E-ECMSE) is proposed that copes with the location errors of geographic routing and hence shows a fair increase in the packet delivery ratio of the network and a decrease in the energy consumption. The number of hops in the network are controlled which directly reduce the energy consumption.
Underwater Wireless Sensor Networks (UWSNs) consist of sensor nodes deployed to sense underwater environment. Sensor nodes gather the required information and report it to sink through a predefined routing path. Research community is getting interest in UWSNs due to its emerging applications such as costal surveillance for defense strategies, disaster monitoring, oil and mineral extractions, pollution monitoring etc. UWSNs are used for monitoring environments where humans access is quite impossible. However, UWSNs work for a limited time because battery power provided to sensor nodes are difficult to replace or recharge due to harsh underwater environment. Therefore, an energy efficient routing protocol is required to make these networks able to work for longtime. This research work aims to provide energy efficient routing schemes to reduce energy consumption of sensor nodes. Energy consumption is reduced by dividing network field into subregions and using clustering technique in dense regions of network. Cluster head node in each dense region is selected in each transmission round to locally gather data from sensor nodes. Each cluster head forwards compressed data to sink using multi-hop routing technique to save energy. Mobile sinks are used to gather data in sparse regions where nodes are not able to forward data because of limited transmission range. In addition, an energy minimization technique is proposed to prolong network lifetime for UWSNs de- signed for continuous monitoring applications. Apart from this, we propose a routing scheme to avoid energy holes in UWSNs. Energy holes are formed due to unbalanced load mostly on sensor nodes near to sink. A balanced load distribution scheme is proposed to overcome the energy hole problem in UWSNs. Extensive simulations are performed by considering different node deployment like uniform and random in homogeneous and heterogeneous environments. The results show that our proposed protocols perform better in terms of stability, energy efficiency and network lifetime.
Random mobility and energy constraint are two main factors affecting system performance in mobile sensor networks, which cause many difficulties to system design. It is necessary to develop high-efficiency algorithms and protocols for mobile sensor networks to adapt to dynamic network environment and energy limitation. In this paper, a new clustering algorithm based on residual energy difference ratio is presented to improve system performance. Firstly, it is an energy-efficient algorithm. The residual energy of sensor nodes and average residual energy of system are considered in the residual energy difference ratio, which effectively avoid the nodes with low residual energy being selected as cluster heads. An energy-optimal scheme is used in cluster formation phase to minimize energy consumption. Secondly, it is a dynamic algorithm. The system dynamically clusters the sensor nodes according to the data transmission delays. It makes the whole system adapt to the random mobility of sensor nodes. The NS2 software is used to simulate the new clustering algorithm. The simulation experiments can verify the validity of the proposed theory.
Wireless Sensor Networks (WSNs) can benefit from ad hoc networking technology characterized by multihop wireless connectivity and infrastructure less framework. These features make them suitable for next-generation networks to support several applications such M2M applications for smart cities and public safety scenarios. Pivotal design requirements for these scenarios are energy efficiency, since many of these devices will be battery powered placing a fundamental limit on network, and specifically node lifetime. Moreover, the way in which traffic is managed also influences network lifetime, since there is a high probability for some nodes to become overloaded by packet forwarding operations in order to support neighbour data exchange. These issues imply the need for energy efficient and load balanced routing approaches that can manage the network load and not only provide reduced energy consumption on the network but also prolong the network lifetime providing robust and continuous. This work proposes a new energy efficient and traffic balancing routing approach that can provide a weighted and flexible trade-off between energy consumption and load dispersion. Simulation results show that the proposed protocol achieves high energy efficiency, decreases the percentage of failed nodes due to lack of battery power, and extends the lifespan of the network.
A key challenge in the success of wireless sensor networks deployment is to consider the imperfections associated with sensor readings. Existing sensor coverage models such as the binary model and the probabilistic model may not be realistic in many cases and remain limited. Based on the transferable belief model, this letter defines an evidence-based sensor coverage model that reflects reality well and can be easily extended to include deployment-related issues, such as sensor reliability. As an example of application, we devise an evidence-based detection coverage model. Experimental results based on both synthetic data sets and data traces collected in a real experiment for vehicle detection are provided to demonstrate the benefits of the evidence-based sensor coverage model over state-of-the-art coverage models.
The use of mobile sensors is of great relevance to monitor hazardous applications where sensors cannot be deployed manually. Traditional algorithms primarily aim at maximizing network coverage rate, which leads to the creation of the "energy hole" in the region near the sink node. In this article, we are addressing the problem of redistributing mobile sensor nodes over an unattended target area. Driven by energy efficiency considerations, a pixel-based transmission scheme is developed to reduce extra overhead caused by frequent sensing and decision making. We derive the optimal node distribution and provide a theoretical explanation of balanced energy depletion for corona-based sensor network. In addition, we demonstrate that it can be extended to deal with uneven energy depletion due to the many-to-one communications in multi-hop wireless sensor networks. Applying the optimal condition, we then propose a novel sensor redistribution algorithm to completely eliminate the energy hole problem in mobile sensor network. Extensive simulation results verify that the proposed solution outperforms others in terms of coverage rate, average moving distance, residual energy, and total energy consumption.
Routing in sensor networks is very challenging compared to contemporary communication and wireless ad-hoc networks. This is attributed to several characteristics that distinguish them from such networks. Transmitting data from every sensor node within the deployment region might result in significant and unnecessary redundancy in data and incur avoidable energy and traffic expenditure; thus, a routing protocol which is able to select a set of sensor nodes and utilise data aggregation during the relaying of data is of great importance. Furthermore, timely delivery of data is required in many applications of Wireless Sensor Networks (WSNs), such as real-time target tracking in battle environments, emergent event triggering in monitoring applications impose the need of efficient routing protocol. In this paper, we propose a data routing scheme which ensures increased network lifetime by exploiting energy efficiently, supporting reliability, fast delivery of delay-sensitive data and achieving low-cost sensor design. Simulation results demonstrate that, the proposed routing scheme outperforms related existing approaches in terms of all the evaluation metrics such as packet delivery ratio, energy efficiency and timely delivery of data.
One of the major challenges in design of wireless sensor networks (WSNs) is to reduce energy consumption of sensor nodes to prolong lifetime of finite capacity batteries. In this paper, we propose energy-efficient adaptive scheme for transmission (EAST) in WSNs. EAST is an IEEE 802.15.4 standard compliant. In this scheme, open-looping feedback process is used for temperature-aware link quality estimation and compensation, wherea closed-loop feedback process helps to divide network into three logical regions to minimize overhead of control packets. Threshold on transmitter power loss () and current number of nodes (()) in each region help to adapt transmit power level () according to link quality changes due to temperature variation. Evaluation of the proposed scheme is done by considering
mobile sensor nodes and reference node both static and mobile. Simulation results show that the proposed scheme effectively adapts transmission to changing link quality with less control packets overhead and energy consumption as compared to classical approach with single region in which maximum transmitter assigned to compensate temperature variation.
Research on wireless sensor networks has recently received much attention as they offer an advantage of monitoring various kinds of environment by sensing physical phenomenon. Among various issues, energy consumption is one of the most important criteria for routing protocol in wireless sensor networks (WSNs). This paper introduces an energy efficient clustering algorithm for mobile sensor network based on the LEACH protocol. The proposed protocol adds feature to LEACH to support for mobile nodes and also reduces the consumption of the network resource in each round. The proposed protocol is simulated and the results show a significant reduction in network energy consumption compared to LEACH.
Wireless Sensor Networks lifetime mainly depends on energy saving efficiency. In this paper, we propose an energy-efficient self-stabilizing topology control protocol for WSN. We reduce the transmission power of each node so as to maintain network connectivity while saving maximum energy. Besides, we propose an approximation algorithm for minimum weighted connected dominating set that builds a virtual backbone formed by sensors with maximum energy. This backbone is used for efficient routing purpose. Through our simulation results, we show the efficiency of our proposed algorithm.
Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.
Cluster based routing technique is most popular routing technique in Wireless Sensor Networks (WSNs). Due to varying need of WSN applications efficient energy utilization in routing protocols is still a potential area of research. In this research work we introduced a new energy efficient cluster based routing technique. In this technique we tried to overcome the problem of coverage hole and energy hole. In our technique we controlled these problems by introducing density controlled uniform distribution of nodes and fixing optimum number of Cluster Heads (CHs) in each round. Finally we verified our technique by experimental results of MATLAB simulations.
Wireless Sensor Networks lifetime mainly depends on energy saving efficiency. In this paper, we propose an energy-efficient self-stabilizing topology control protocol for WSN. We reduce the transmission power of each node so as to maintain network connectivity while saving maximum energy. Besides, we propose an approximation algorithm for minimum weighted connected dominating set that builds a virtual backbone formed by sensors with maximum energy. This backbone is used for efficient routing purpose. We proved the algorithm correctness and through our simulation results, we showed the efficiency of our proposed solution.
Cluster based routing technique is most popular routing technique in Wireless Sensor Networks (WSNs). Due to varying need of WSN applications efficient energy utilization in routing protocols is still a potential area of research. In this research work we introduced a new energy efficient cluster based routing technique. In this technique we tried to overcome the problem of coverage hole and energy hole. In our technique we controlled these problems by introducing density controlled uniform distribution of nodes and fixing optimum number of Cluster Heads (CHs) in each round. Finally we verified our technique by experimental results of MATLAB simulations.
Cluster-based routing protocol is always a hot research area in wireless sensor networks. Classical LEACH protocol has many advantages in energy efficiency, data aggregation and so on, so it is widely used until now. In this paper, based on the LEACH protocol, we propose a new distance-based clustering routing protocol, LEACH-SC (LEACH-selective cluster). In LEACH-SC, a new method is used to choose cluster heads, i.e. an ordinary node A will choose a clusterhead which is the closest to the center point between A and the sink. The simulation results show that compared with LEACH, LEACH-SC protocol can greatly reduce the overall network energy consumption, balance the energy consumption among the sensors and extend the lifetime of the network.
In this paper, we propose Regional Energy Efficient Cluster Heads based on
Maximum Energy (REECH-ME) Routing Protocol for Wireless Sensor Networks (WSNs)
. The main purpose of this protocol is to improve the network lifetime and
particularly the stability period of the network. In REECH-ME, the node with
the maximum energy in a region becomes Cluster Head (CH) of that region for
that particular round and the number of the cluster heads in each round remains
the same. Our technique outperforms LEACH which uses probabilistic approach for
the selection of CHs. We also implement the Uniform Random Distribution Model
to find the packet drop to make this protocol more practical. We also calculate
the confidence interval of all our results which helps us to visualize the
possible deviation of our graphs from the mean value.
Clustering algorithms play an important role in design and deployment of in wireless sensor networks (WSNs). We apply here a general clustering algorithm namely FFUCA (Fast and Flexible Unsupervised Clustering Algorithm) on WSNs. This application shows that FFUCA provides rapidly a strong organizational structure of nodes. We compare its built structures with those of the common algorithm LEACH to validate our approach. We aim to provide an optimal structure regarding energy consumption but with a low computational complexity.
Energy conservation is one of the most important design considerations for battery powered wireless sensors networks (WSNET). Energy constraint in WSNETs limits the total amount of sensed data (data capacity) received by the sink. The data capacity of WSNETs is significantly affected by deployment of sensors and the sink. A major issue, which has not been adequately addressed so far, is the question of how node deployment governs the data capacity and how to improve the total data capacity of WSNETs by using non-uniform sensor deployment strategies. In this paper, we discuss this problem by analyzing the commonly used static model of sensors networks. In the static model, we find that after the lifetime of a sensor network is over, there is a great amount of energy left unused, which can be up to 90% of the total initial energy. This energy waste implies that the potential data capacity can be much larger than the capacity achieved in the static model. To increase the total data capacity, we propose two strategies: a non-uniform energy distribution model and a new routing protocol with a mobile sink. For large and dense WSNETs, both of these strategies can increase the total data capacity by an order of magnitude.
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.
lo calization algorithm, well suitable for large-scale sensor networks with complex shapes and non-uniform nodal distribution. In contrast to current state-of-art connectivity-bas ed localization methods, the proposed algorithm is fully distributed, where each node only needs the information of its neighbors, without cumbersome partitioning and merging process. The algorithm is highly scalable, with limited error propagation and linear computation and communication cost with respect to the size of the network. Moreover, the algorithm is theoretically guaranteed and numerically stable. Extensive simulations and comparison with other methods under various representative network settings are carried out, showing superior performance of the proposed algorithm.
Cluster based wireless sensor networks have been widely used due to the good performance. However, in so many cluster based protocols, because of the complexity of the problem, theoretical analysis and optimization remain difficult to develop. This paper studies the performance optimization of four protocols theoretically. They are LEACH (Low Energy Adaptive Clustering Hierarchy), MLEACH (Multi-hop LEACH), HEED (Hybrid Energy-Efficient Distributed Clustering Approach), and UCR (Unequal Cluster based Routing). The maximum FIRST node DIED TIME (FDT) and the maximum ALL node DIED TIME (ADT) are obtained for the first time in this paper, as well as the optimal parameters which maximize the network lifetime. Different from previous analysis of network lifetime, this paper analyzes the node energy consumption in different regions through the differential analysis method. Thus, the optimal parameters which maximize the lifetime can be obtained and the detailed energy consumption in different regions at different time can be also obtained. Moreover, we can obtain the time and space evolution of the network, from a steady state (without any death) to a non-steady state (with some death of nodes), and then to the final situation (all nodes die). Therefore, we are fully aware of the network status from spatial and temporal analysis. Additionally, the correctness of the theoretical analysis in this paper is proved by the Omnet++ experiment results. This conclusion can be an effective guideline for the deployment and optimization of cluster based networks.
In this paper we present an energy efficient priority based MAC protocol for Wireless Sensor Networks (WSNs). We abbreviate it as PRIMA. The PRIMA protocol consists of two phases; a clustering phase and a channel access phase. Clustering the senor network makes the MAC protocol to handle well network scalability issues. The channel access is composed of a hybrid mode of TDMA and CSMA. CSMA mode is used to communicate control messages, while data messages are assigned TDMA slots. Doing so, minimizes packet collisions and consequently minimizing energy consumption. Our PRIMA protocol forces the nodes that have no data to send to go early into a sleep state to save energy, this minimizes the idle listening periods which is considered as a main source of the energy consumption in sensor networks. The PRIMA protocol provides Quality of Service (QoS) by employing a queueing model to classify the traffic depending on its importance into four different queues. Higher priority queues have absolute preferential treatment over low priority queues. Through simulations and analytical analysis, we evaluate the performance of our proposed MAC protocol and compare it against the Q-MAC protocol. Results have shown that our protocol outperforms Q-MAC in terms of energy consumption, packet delivery ratio and average packet delay.
Real-time wireless link reliability estimation is a fundamental building block for self-organization of multihop sensor networks. Observed connectivity at low-power is more chaotic and unpredictable than in wireless LANs, and available resources are severely constrained. We seek estimators that react quickly to large changes, yet are stable, have a small memory footprint and are simple to compute. We create a simple model that generates link loss characteristics similar to empirical traces collected under different contexts. With this model, we simulate a variety of estimators, and uses the simple exponentially weighted moving average (EWMA) estimator, as a basis for comparison. We find that recently propose flip-flop estimators are not superior. However, our cascaded EWMA on windowed averaging is very effective
The paper presents a new cluster based routing algorithm that exploits the redundancy properties of the sensor networks in order to address the traditional problem of load balancing and energy efficiency in the WSNs.The algorithm makes use of the nodes in a sensor network of which area coverage is covered by the neighbours of the nodes and mark them as temporary cluster heads. The algorithm then forms two layers of multi hop communication. The bottom layer which involves intra cluster communication and the top layer which involves inter cluster communication involving the temporary cluster heads. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing and is also more efficient in terms of energy consumption from Leach and the enhanced version of Leach.
Code-division multi-access (CDMA) techniques allow many users to transmit simultaneously in the same band without substantial interference by using approximately orthogonal (low cross-correlation) spread-spectrum waveforms. Two-phase algorithms have been devised to assign and reassign spread-spectrum codes to transmitters, to receivers and to pairs of stations in a large dynamic packet radio network in polynomial times. The purpose of the code assignments is to spatially reuse spreading codes to reduce the possibility of packet collisions and to react dynamically to topological changes. These two-phase algorithms minimize the time complexity in the first phase and minimize the number of control packets needed to be exchanged in the second phase. Therefore, they can start the network operation in a short time, then switch to the second phase with the goal of adapting to topological changes. A pairwise code-assignment scheme is proposed to assign codes to edges. Simulations based on well-controlled topologies (sparse topologies) show that the scheme requires much fewer codes than transmitter-based code assignment, while maintaining similar throughput performance
Clustering wireless sensors networks with FFUCA
- S Fouchal
- D Mansouri
- L Mokdad
- J Ben-Othman
- M Ioualalen
Fouchal, S., Mansouri, D., Mokdad, L., Ben-Othman, J.
and Ioualalen, M. (2013) 'Clustering wireless sensors
networks with FFUCA', IEEE International Conference on
Communications (ICC), 2013, Vol. 6438, No. 6443, pp.9-13,
doi: 10.1109/ICC.2013.6655642.