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Adaptive Relay Chain Routing With Load Balancing and High Energy Efficiency
Abstract
The concentration of data traffic toward sink makes sensor nodes nearby have heavier communication burden and more quickly use up their energy, leading to energy hole problem. Sink mobility can realize load balancing data delivery by changing the hotspots around the sink as the sink moves. However, sink mobility also brings about the problem of localization of sink. Frequently broadcasting of mobile sinks' position will generate significant overhead. In this paper, we propose a novel heterogeneous adaptive relay chain routing protocol with a few mobile relay nodes, which is applied to large-scale 1-D long chain network. Mobile relay node is the sink of local subnetwork. The protocol achieves the following performances. First, through scheduled movement of the mobile relay nodes, load balancing is achieved not only among sensor nodes but also among high tier relay nodes in continuous data delivery model. Second, in the context of clock synchronization among nodes, every node decides its operating state by algorithm stored in its own processor. So, there is no need for advertisement of mobile relay nodes' location. Only a few messages for clock synchronization among nodes are needed. Third, by synthetically utilizing node deployment strategy and routing protocol, base station can real-time monitoring residual energy of sensor nodes for timely maintenance, which can extend the protocol to be suitable for event-driven and query-driven data delivery models. Finally, the performances are evaluated via extensive simulations.
... In both transmission modes, the energy consumption is imbalanced and in multihop, data load on relay nodes is very high which leads to dramatic death of the node and degrades the network performance [5]. The imbalanced data load distribution is defined as; the immutable forwarder selection because of which all nodes transmit data from the same path leading to energy hole creation [6]. ...
... Lingxu et al. proposed an adaptive relay chain routing (ARCR) [6] protocol for balanced and efficient energy dissipation during the network nodes communication. The objective of this routing strategy was to adaptively distribute data load on the sensor nodes deployed nearby the sink. ...
... The noises are; turbulence noise N t ( f ), waves noise N w ( f ), shipping noise N s ( f ) and thermal noise is N th ( f ) [3]. The mathematical representation of noises is formulated in Eq. 6. ...
The imbalance energy consumption and high data traffic at intermediate nodes degrade the network performance. In this paper, we propose: energy grade and balance load distribution (EGBLOAD) corona, EG without corona and DA without corona based schemes to distribute data traffic across the network nodes for efficient energy consumption. The dynamic adjustment of transmission range in first scheme helps in reducing data load. Additionally, the transmission range is purely based on distance, energy and data load of the receiver node for achieving maximum network lifetime. Second scheme divides a data packet into three fractions; small, medium and large for transmitting from various paths to evenly distribute the data load on the network nodes. In third scheme, depth adjustment of void node is performed to resume network operations, whereas, the load distribution and transmission range mechanisms are the same. The extensive simulations are carried out to show the effectiveness of proposed schemes in terms of PDR, energy consumption, and load distribution against the baseline scheme.
... Estimation of energy consumption and time synchronization is becoming a center of research for WSN to enhance its lifetime. Time 1 3 synchronization between the sensor clocks is important for the applications like load balancing in adaptive message passing, chain routing algorithm [1]. The time synchronization in WSN is minimizing the variation in the clock offset between various sensor clocks [2]. ...
... Synchronizing clock with limited power supply for low-end sensors is a challenging task. Therefore, to optimize the power consumption in WSN and enhance its lifetime, various time-synchronization protocols are analyzed [1][2][3] in this paper. ...
Time synchronization is an essential characteristic for the faithful functioning of wireless sensor networks. Hypothetically, it is stated that the two clocks are considered to be synchronized with each other if their clock offset and frequency components within the oscillator are running at the same rate. But, practically, there is some degree of inaccuracy in the manufacturing of these clocks; as a result, their frequency sources have slight variations. This paper proposes a unique mathematical model which is based on maximum probable theory maximum probable clock offset estimation, along with the propagation delay factor for finding the best probable estimate for clock offset. In addition, a novel two-way message passing scheme-based network communication model is presented here. Based on results, it has been predicted that estimating the clock offset will help in improving the efficiency of the existing time-synchronization protocols i.e. time-sync protocol for sensor networks (TPSNs). It was observed that the standard error deviation of modified TPSN with MPCEO was reduced from 2.324 to 0.064 ms. This will make the modified TPSN model more accurate, efficient, and reliable.
... Kong et al 11 provided an advancement of localization free routing protocols of DBR, ie, energy efficient DBR and AMCTD as improved delay-sensitive versions. In this paper, the authors made the aforementioned schemes adaptable according to the requirements of the applications. ...
... 2,28 As the goal of geographic and opportunistic routing is to find the f i ⊆ N i to maximize the expected packet advance (EPA). The EPA of f i is formulated in Equation 11. ...
In this research work we propose three schemes: neighbor node approaching distinct energy efficient mates (NADEEM), fallback approach NADEEM (FA-NADEEM) and transmission adjustment NADEEM (TA-NADEEM). In NADEEM, immutable forwarder node selection is avoided with the help of three distinct selection parameters. Void hole is avoided using fallback recovery mechanism to deliver data successfully at the destination. The transmission range is dynamically adjusted to resume greedy forwarding among the network nodes. The neighbor node is only eligible to become forwarder when it is not a void node. Additionally, linear programming based feasible regions are computed for an optimal energy dissipation and to improve network throughput. Extensive simulations are conducted for three parameters: energy, packet delivery ratio (PDR) and fraction of void nodes. Further, an analysis is performed by varying transmission range and data rate for energy consumption and fraction of void node. The results clearly depict that our proposed schemes outperform the baseline scheme (GEDAR) in terms of energy consumption and fraction of void nodes.
... Kong et al. proposed a routing protocol called an adaptive relay chain routing (ARCR) [6]. The objective of this work is to reduce the energy hole problem. ...
... Load is an imbalance, and distance is small from sink ARCR [6] Network lifetime, energy balances, load balances ...
Underwater wireless sensor networks (UWSNs) provide the wide range of aquatic applications. These applications are used for many aspects of life i.e., the tsunami and
earthquake monitoring, pollution monitoring, ocean surveillance for defense strategies, seismic monitoring, and equipment monitoring, etc. The limited bandwidth, long
propagation delay, energy consumption, high manufacturer and deployment costs are
many challenges in the domain of UWSNs. In this thesis, we present the three techniques i.e., energy balanced load distribution through energy gradation (EBLOADEG), energy gradation (EG) and depth adjustment (DA) among various coronas and
in without the number of coronas. Our aim is to overcome these issues: Firstly, the
forwarder node determines the higher energy node and data is directly transmitted
to sink; secondly, if the forwarder node comes in void communication region then the
node moves to the new depth so that the data delivery ratio can be ensured effectively. However, data is forwarded on the basis of EG and DA in without the number
of coronas. Thirdly, the EBLOAD-EG scheme performs data transmission among
various coronas which are based upon the energy comparison of the first node with
any neighbor node. Moreover, our aim is to balance the load distribution among various coronas in a network field. Simulation results define that our proposed schemes
show better performance in terms of energy efficiency, packet delivery ratio (PDR),
network lifetime and stability period etc
... On the other hand, one should not ignore the energy consumption when frequently broadcasting the location of the mobile sink. To solve this problem, several mobile relay nodes were introduced in the network and they were regarded as the mobile sinks of the sub-networks [31]. These mobile relay nodes independently collect data in each sub-network and forward them to the In [28], the network is uniformly divided into sectors, and the nodes in each sector form a cluster. ...
... On the other hand, one should not ignore the energy consumption when frequently broadcasting the location of the mobile sink. To solve this problem, several mobile relay nodes were introduced in the network and they were regarded as the mobile sinks of the sub-networks [31]. These mobile relay nodes independently collect data in each sub-network and forward them to the static sink. ...
With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime.
... Relative distance based forwarding Energy efficiency, minimize end to end delay Due to small hop count the load is imbalance, and distance is small from sink ARCR [8] Clustering, relay node and mobile sink Network lifetime,energy balances,load balances higher end-to-end delay GEDAR [9] Geographic and opportunistic routing, Forwarder node based on Greedy forwarding scheme Void node decreases, better network performance, minimizes collision ...
... In [8], the authors proposed an adaptive relay chain routing (ARCR) protocol. Major objectives were to avoid the energy hole problem and also prevent the localization problem. ...
Underwater wireless sensor networks (UWSNs) find applications in various aspect of life like the tsunami and earthquake monitoring, pollution monitoring, 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 an energy balanced load distribution through energy gradation (EBLOAD-EG) technique to minimize the energy consumption in direct transmission. The proposed scheme aims to balance the load distribution among different coronas of network field. In this scheme, the numbers of sensor nodes are uniformly deployed in a circular network field and the sink is located at the center of network field. In EBLOAD-EG, the accumulated data is partitioned into data fractions like small, medium and large. Simulation results show that our scheme outperforms the existing scheme in terms of energy efficiency, balanced load distribution, stability period and network lifetime.
... Continuously tracking the location information of the sink node introduces overheads and makes the overall system inefficient in terms of energy consumption. Deployment of mobile relay nodes considered in [104] is a potential solution to such a problem in mobile sink This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and content may change prior to final publication. ...
A huge increase in the percentage of the world’s urban population poses resource management especially energy management challenges in smart cities. In this paper, the growing challenges of energy management in smart cities have been explored and significance of elimination of energy holes in converge cast communication has been discussed. The impact of mitigation of energy holes on the network lifetime and energy efficiency has been thoroughly covered. The particular focus of this work has been on energy-efficient practices in two major key enablers of smart cities namely, the Internet of Things (IoT) and Wireless Sensor Networks (WSNs). In addition, this paper presents a robust survey of state-of-the-art energy-efficient routing and clustering methods in WSNs. A niche energy efficiency issue in WSNs routing has been identified as energy holes and a detailed survey and evaluation of various techniques that mitigate the formation of energy holes and achieve balanced energy-efficient routing has been covered.
... The little, broadminded changes in the range and depth of the sound pressure are arranged in a grid. It makes approximations of unpredictability and wave motion, employing a vigorous transmission loss computation [51][52][53][54][55]. The writers show how even minor variations in penetration and node distance can significantly impact route loss due to the influence of ocean wave motions on audio propagation. ...
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.
... Zhao J proposed a new heuristic method for the physical host selection problem of the deployment request task, which is called Bayesian and clustering-based load balancing. As demonstrated by the results of the simulation, the proposed approach significantly reduces the failures of the mission deployment incidents, improves the amount of throughput, and optimizes the outside-in service performance of the hybrid service in the cloud data center compared to existing work [8]. ese studies provide a great reference for this article, but there are few studies on the application of ant colony optimization algorithms to cloud computing loads. ...
The networking scale and traffic have exploded. At the same time, the rapid development of virtualization and cloud computing technologies not only poses a considerable challenge to the endurance of the network, but also causes more and more problems to the traditional network architecture with IP as the core. Cloud computing is a supercomputing model based on the Internet. With the rapid growth of network access and data traffic, the processing power and computing intensity will also increase, and a single server cannot afford the increase in business. In order to reduce network pressure and improve computing efficiency, load balancing for network computing is particularly important. This paper uses ant colony algorithm to design cloud computing load balance. The ant colony algorithm runs in the controller. According to the real-time network load situation provided by the controller, it calculates the link with the smallest load and provides a dynamic data stream forwarding strategy. The result of the experiments shows that the load-balanced ACO optimized technique can significantly provide an improved computational response. In the ACO algorithm, the average response time is about 30% lower than that in other algorithms. This shows that the use of the ant colony algorithm achieves a good optimization effect.
... This framework requires former network data to function. In [13], the researchers suggested the use of mobile sensor nodes to reduce the issue of energy holes and keep the sink fixed. To fulfil this objective, clusters are formed in the network, and data gathering is carried out using mobile nodes. ...
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.
... However, a high end-to-end delay resulted from this system. The authors suggested a scheme to address the current shortcomings of the schemes in [14] so that they concentrated on the consistency of the connection and routing path problem. ...
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.
... The reduction in energy consumption for the Hot Spot Area and the balance of the energy consumption for the whole network can be achieved by means of making full use of the features that the relays have unlimited energy supply and carefully designing the relay's trajectory. Such strategies include the Optimal Mobile Relay Configuration (OMRC) [112] taking the energy consumption for both movement and communication of relays into consideration and the Adaptive Relay Chain Routing (ARCR) [113] that adopts mobile relays for data forwarding. ...
A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out.
... In [27], the author tried to solve the energy-hole problem by using some mobile relay nodes. The network is divided into several clusters with different sizes, and each "relay node" is responsible for uploading the sensing data of several clusters to Sink. ...
In the era of Big Data and Mobile Internet, how to ensure the terminal devices (e.g., sensor nodes) work steadily for a long time is one of the key issues to improve the efficiency of the whole network. However, a lot of facts have shown that the unattended equipments are prone to failure due to energy exhaustion, physical damage and other reasons. This may result in the emergence of energy-hole, seriously affecting network performance and shortening its lifetime. To reduce data redundancy and avoid the generation of sensing blind areas, a type of Virtual Force based Energy-hole Mitigation strategy (VFEM) is proposed in this paper. Firstly, the virtual force (gravitation and repulsion) between nodes is introduced that makes nodes distribute as uniformly as possible. Secondly, in order to alleviate the "energy-hole problem", the network is divided into several annuluses with the same width. Then, another type of virtual force, named "virtual gravity generated by annulus", is proposed to further optimize the positions of nodes in each annulus. Finally, with the help of the "data forwarding area", the optimal paths for data uploading can be selected out, which effectively balances energy consumption of nodes. Experiment results show that, VFEM has a relatively good performance on postponing the generation time of energy-holes as well as prolonging the network lifetime compared with other typical energy-hole mitigation methods.
... This leads to the disruption of network connectivity and creates energy hole (Abo-Zahhad et al., 2015; https://doi.org/10. 1016 Kong et al., 2016) in the network. In this situation, sink mobility provides a better solution to prevent the energy drainage in nearby sink area as compared to static sink ( Liu et al., 2010). ...
... In Adaptive Relay Chain Routing (ARCR) [25], the authors introduced to use of mobile sensor nodes to reduce the problem of energy hole and keeping sink fixed in its particular location. To achieve this, clusters are formed in the network and for collection of data mobile nodes are used. ...
Underwater Wireless Sensor Networks (UWSNs) have been considered as an emerging
and promising method for exploring and monitoring deep ocean. The UWSNs face
many challenges due to high transmission delays, high deployment cost, movement
of nodes, energy constraints, etc. In UWSNs nodes are sparsely and unevenly deployed, that may results in void hole occurrence. Secondly low propagation speed in
UWSNs causes high end-to-end delay and energy consumption. In this paper, we propose four schemes: Adaptive Transmission Range in WDFAD-DBR (ATR-WDFADDBR), Cluster Based WDFAD-DBR (CB-WDFAD-DBR), Backward Transmission
based WDFAD-DBR (BT-WDFAD-DBR) and Collision Avoidance based WDFADDBR (CA-WDFAD-DBR). The first scheme ATR-WDFAD-DBR scheme adjusts its
transmission range when it finds a void node and then continues to forward data towards the sink. CB-WDFAD-DBR is used to minimize end-to-end delay and energy
consumption. In BT-WDFAD-DBR fall back recovery mechanism is used to find an
alternative route to deliver the data when void hole occurs. In CA-WDFAD-DBR
fall along with nomination of forwarder node which has minimum number of neighbor nodes is selected. Simulation results show that our schemes outperform compared
with baseline solution in terms of average Packet Delivery Ratio (PDR), energy tax,
end-to-end delay and Accumulated Propagation Distance (APD).
... In Adaptive Relay Chain Routing (ARCR) [27], the authors introduced mobile sensor nodes to overcome the energy hole problem. Additionally, clusters were formed for collecting data via mobile nodes to improve the network performance. ...
Due to the limited availability of battery power of the acoustic node, an efficient utilization is desired. Additionally, the aquatic environment is harsh; therefore, the battery cannot be replaced, which leaves the network prone to sudden failures. Thus, an efficient node battery dissipation is required to prolong the network lifespan and optimize the available resources. In this paper, we propose four schemes: Adaptive transmission range in WDFAD-Depth-Based Routing (DBR) (A-DBR), Cluster-based WDFAD-DBR (C-DBR), Backward transmission-based WDFAD-DBR (B-DBR) and Collision Avoidance-based WDFAD-DBR (CA-DBR) for Internet of Things-enabled Underwater Wireless Sensor Networks (IoT, UWSNs). A-DBR adaptively adjusts its transmission range to avoid the void node for forwarding data packets at the sink, while C-DBR minimizes end-to-end delay along with energy consumption by making small clusters of nodes gather data. In continuous transmission range adjustment, energy consumption increases exponentially; thus, in B-DBR, a fall back recovery mechanism is used to find an alternative route to deliver the data packet at the destination node with minimal energy dissipation; whereas, CA-DBR uses a fall back mechanism along with the selection of the potential node that has the minimum number of neighbors to minimize collision on the acoustic channel. Simulation results show that our schemes outperform the baseline solution in terms of average packet delivery ratio, energy tax, end-to-end delay and accumulated propagation distance.
... In Adaptive Relay Chain Routing (ARCR) [8], the authors introduced to use mobile sensor nodes to reduce the problem of energy hole and keeping sink fixed in its particular location. To achieve this, clusters are used in the network and for collection of data mobile nodes are used and then the data is forwarded towards the sink. ...
Underwater Wireless Sensor Networks (UWSNs) facilitate an extensive variety of aquatic applications such as military defense, monitoring aquatic environment, disaster prevention, etc. However UWSNs routing protocols face many challenges due to adverse underwater environment such as high propagation and transmission delays, high deployment cost, nodes movement, energy constraints, expensive manufacture, etc. Due to random deployment of nodes void holes may occur that results in the failure of forwarding data packet. In this research work we propose two schemes, Geographic and Opportunistic Routing using Backward Transmission (GEBTR) and Geographic and Opportunistic Routing using Collision Avoidance (GECAR) for UWSNs. In aforesaid scheme fall back recovery mechanism is used to find an alternative route to deliver the data when void occurs. In later, fall along with nomination of forwarder node which has minimum number of neighbor nodes is selected. Simulation results shows that our techniques outperforms compared with baseline solution in terms of packet delivery ratio by 5% in GEBTR and 45%t in GECAR, fraction of void nodes by 8% and 11% in GECAR and energy consumption by 8% in GEBTR and 10% in GECAR.
... The analytical results of the scheme indicate efficient energy utilization and network lifetime longevity. The use of mobile relay nodes is introduced by the author in [29] to remove the energy hole problem and to solve the issue of localization of sink. For this purpose, the entire network is divided into different clusters and mobile relay nodes are applied in the network to collect data from sensor nodes and transmit further to the sink. ...
In wireless sensor networks (WSNs), energy balancing and energy efficiency are the key requirements to prolong the network lifetime. In this paper, we investigate the problem of energy hole, where sensor nodes located near the sink or in some other parts of the network die very early due to unbalanced load distribution. Moreover, there is a dire need to utilize the energy resource efficiently. For this purpose, balanced energy consuming and hole alleviating (BECHA), and energy-aware balanced energy consuming and hole alleviating (EA-BECHA) algorithms are proposed, not only to balance the load distribution of entire network but also to utilize the energy resource efficiently. This work mainly adopts data forwarding and routing selection strategy for the entire network. An optimal distance and energy-based transmission strategy which is free of location error is adopted to forward the data packets of different sizes. Finally, the simulation results validate the proposed schemes by showing improvement in network lifetime, energy balancing, and enhanced throughput with less number of packets drop on the cost of increased end to end delay.
... The analytical results of the scheme indicate efficient energy utilization and network lifetime longevity. The use of mobile relay nodes is introduced by the author in [28] to remove the energy hole problem and to solve the issue of localization of sink. For this purpose, the entire network is divided into different clusters and mobile relay nodes are applied in the network to collect data from sensor nodes and transmit further to the sink. ...
In wireless sensor networks (WSNs) energy balancing and energy efficiency are the
key requirements to prolong the network lifetime. In this thesis, we investigate the
problem of energy hole, where sensor nodes located near the sink or in some other
parts of the network die very early due to unbalanced load distribution. Moreover,
there is a dire need to utilize the energy resource efficiently. For this purpose, a
balanced energy consuming and hole alleviating (BECHA), and energy-aware balanced
energy consuming and hole alleviating (EA-BECHA) algorithms are proposed, not only
to balance the load distribution of entire network, but also to utilize the energy
resource efficiently. This work mainly adopts data forwarding and routing selection
strategy for the entire network. An optimal distance and energy-based transmission
strategy which is free of location error is adopted to forward the different size of data
to the neighbors by selecting the optimal forwarder. Finally, the simulation results
validate the proposed schemes by showing improvement in network lifetime, energy
balancing, and enhanced throughput with less number of packet drop.
The metaverse, as an emerging technical term, conceptually aims to construct a virtual digital space that runs parallel to the physical world. Due to humans behaviors and interactions are represented in the virtual world, security in metaverse is a challenging issue in which traditional centralized service model is one of the threat sources. In order to conquer the obstacle caused by centralized computing, blockchain-based solutions are potential problem-solving methods. However, it is difficult for a single blockchain to support large-scale data and business services in the metaverse, due to the scalability restrictions. Moreover, multi-chain settings also encounter the interoperability issues. In this work, we propose a R elay chain and A synchronous consensus-based C onsortium blockchain cross- C hain (RAC-Chain) model, which realizes message transmission and cross-chain transactions in multiple chains by adopting the relay chain and cross-chain gateways. All nodes of the application chains and the relay chain execute cross-chain transactions in sequence and reach a consensus on transactions at any transmission delay. Our experiment evaluations demonstrate that our approach performs well in atomicity, security, and functionality (cross-chain transactions), such that the performance of blockchain scalability in metaverse can be improved, comparing with the traditional relay chain schemes.
The Smart Grid (SG) enables electricity and energy exchange between two ends of the grid. Wireless Sensor Networks (WSNs) are considered as an enabling communication technology for effective SG management. How well the target region is covered by a WSN indicates the service quality of the relevant implementation. Since effective monitoring is key to exploiting the benefits of the SG, maintaining the desired coverage level is critical in WSN for SG applications. However, some uncovered regions (coverage holes) might emerge due to several reasons such as improper localization or sensor malfunctioning. In this paper, we propose using a mobile sensor to cover such blind regions in a timely and hence energy-efficient way. First, we present a novel 0-1 mixed integer programming model without restrictive assumptions about the mobility pattern to find the shortest trajectory for the mobile sensor. Then we show that the problem is NP-hard with a polynomial reduction to the Traveling Salesman Problem. Consequently, we present an optimization-based heuristic, two heuristic-based algorithms, and a hybrid algorithm. We show that our heuristics are efficient as they find high quality solutions in a few seconds. We also observe that assumptions about the starting point of the tour and the potential set of stops significantly affect the final tour’s length.
Load balancing is of great significance to extend the longevity of wireless sensor networks, due to the inherent imbalanced energy overhead in such networks. However, existing solutions cannot balance the load distribution in partially disconnected wireless sensor networks. For example, if a network is partitioned into several segments with different area sizes, some areas have much more traffic load than other areas. In this article, we propose a load-balanced routing scheme, which aims to balance energy consumption within each segment and among different segments. First, we adopt unequal transmission distances to build initial routing for intrasegment load balancing. Second, we adopt the genetic algorithm to build extra routing between different segments for intersegment load balancing. The unique character of our work is twofold. On one hand, we investigate partitioned wireless sensor networks where there are several isolated segments. On the other hand, we pursue load balancing from a global perspective rather than from a local one. Some simulations verify the effectiveness and the advantages of our scheme in terms of extra deployment cost, system longevity, and load balancing degree.
In order to effectively solve the problem of routing efficiency in wireless sensor networks, a new chained routing algorithm based on group perception is proposed in this paper. First, the performance index parameters such as energy consumption and area coverage are given. Meanwhile, a chained routing strategy based on node utility value is established, which combines the “storage-carrying-forwarding” opportunistic transmission mode and decides whether a message needs to be forwarded to an encounter node according to a message forwarding strategy. Finally, the key factors affecting the chained routing algorithm are studied through simulation experiments. The results show that compared with random routing, the chained routing algorithm has great advantages in message delivery rate, collision probability, accuracy, etc.
A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out.
In the era of Big Data and Mobile Internet, how to ensure the terminal devices (e.g., sensor nodes) work steadily for a long time is one of the key issues to improve the efficiency of the whole network. However, a lot of facts have shown that the unattended equipments are prone to failure due to energy exhaustion, physical damage and other reasons. This may result in the emergence of energy-hole, seriously affecting network performance and shortening its lifetime. To reduce data redundancy and avoid the generation of sensing blind areas, a type of Virtual Force based Energy-hole Mitigation strategy (VFEM) is proposed in this paper. Firstly, the virtual force (gravitation and repulsion) between nodes is introduced that makes nodes distribute as uniformly as possible. Secondly, in order to alleviate the “energy-hole problem”, the network is divided into several annuluses with the same width. Then, another type of virtual force, named “virtual gravity generated by annulus”, is proposed to further optimize the positions of nodes in each annulus. Finally, with the help of the “data forwarding area”, the optimal paths for data uploading can be selected out, which effectively balances energy consumption of nodes. Experiment results show that, VFEM has a relatively good performance on postponing the generation time of energy-holes as well as prolonging the network lifetime compared with other typical energy-hole mitigation methods.
Underwater wireless sensor networks (UWSNs) find applications in various aspect of life like the tsunami and earthquake monitoring, pollution monitoring, 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 an energy balanced load distribution through energy gradation (EBLOAD-EG) technique to minimize the energy consumption in direct transmission. The proposed scheme aims to balance the load distribution among different coronas of network field. In this scheme, the numbers of sensor nodes are uniformly deployed in a circular network field and the sink is located at the center of network field. In EBLOAD-EG, the accumulated data is partitioned into data fractions like small, medium and large. Simulation results show that our scheme outperforms the existing scheme in terms of energy efficiency, balanced load distribution, stability period and network lifetime.
Wireless sensor networks (WSNs) are used to monitor long linear structures such as pipelines, rivers, railroads, international borders, and high power transmission cables. In this case, a special type of WSN called linear wireless sensor network (LSN) is used. One of the main challenges of using LSNs is the reliability of the connections across the nodes. Faults in a few contiguous nodes may cause the creation of holes (segments where nodes on either end of them cannot reach each other) which will result in dividing the network into multiple disconnected segments. As a result, sensor nodes that are located between holes may not be able to deliver their sensed information which negatively affects the network's sensing coverage. In this paper, we provide an analysis of the different types of node faults in uniformly deployed LSNs and study their negative impact on the sensing coverage. We develop an analytical model to estimate the sensing coverage in uniformly deployed sensors LSNs in the presence of node faults. We verify the correctness of the developed model by conducting a number of simulation experiments to compare both calculated and simulated results under different network configurations and fault scenarios. In addition, we use this model to demonstrate three design applications that meet with specific performance requirements.
In a typical wireless sensor network, the batteries of the nodes near the sink deplete quicker than other nodes due to the data traffic concentrating towards the sink, leaving it stranded and disrupting the sensor data reporting. To mitigate this problem, mobile sinks are proposed. They implicitly provide load-balanced data delivery and achieve uniform-energy consumption across the network. On the other hand, advertising the position of the mobile sink to the network introduces an overhead in terms of energy consumption and packet delays. In this paper, we propose Ring Routing, a novel, distributed, energy-efficient mobile sink routing protocol, suitable for time-sensitive applications, which aims to minimize this overhead while preserving the advantages of mobile sinks. Furthermore, we evaluate the performance of Ring Routing via extensive simulations.
One of the key challenges facing wireless sensor networks (WSNs) is extending network lifetime due to sensor nodes having limited power supplies. Extending WSN lifetime is complicated because nodes of-ten experience differential power consumption. For example, nodes closer to the sink in a given routing topology transmit more data and thus con-sume power more rapidly than nodes farther from the sink. Inspired by the huddling behavior of emperor penguins where the penguins take turns on the cold extremities of a penguin "huddle", we propose mobile node rotation, a new method for using low-cost mobile sensor nodes to address differential power consumption and extend WSN lifetime. Specifically, we propose to rotate the nodes through the high power consumption loca-tions. We propose efficient algorithms for single and multiple rounds of rotations. Our extensive simulations show that mobile node rotation can extend WSN topology lifetime by more than eight times on average in a which is significantly better than existing alternatives.
The concentration of data traffic towards the sink in a wireless sensor network causes the nearby nodes to deplete their batteries quicker than other nodes, which leaves the sink stranded and disrupts the sensor data reporting. To mitigate this problem the usage of mobile sinks is proposed. Mobile sinks implicitly provide load-balancing and help achieving uniform energy-consumption across the network. However, the mechanisms to support the sink mobility (e.g., advertising the location of the mobile sink to the network) introduce an overhead in terms of energy consumption and packet delays. With these properties mobile sink routing constitutes an interesting research field with unique requirements. In this paper, we present a survey of the existing distributed mobile sink routing protocols. In order to provide an insight to the rationale and the concerns of a mobile sink routing protocol, design requirements and challenges associated with the problem of mobile sink routing are determined and explained. A definitive and detailed categorization is made and the protocols' advantages and drawbacks are determined with respect to their target applications.
Underground pipelines constitute one of the most important ways to transport large amounts of fluid (e.g. oil and water) through long distances. However, existing leakage detection techniques do not work well in monitoring the underground pipelines due to the harsh underground environmental conditions. In this paper, a new solution, the magnetic induction (MI)-based wireless sensor network for underground pipeline monitoring (MISE-PIPE), is introduced to provide low-cost and real-time leakage detection and localization for underground pipelines. MISE-PIPE detects and localizes leakage by jointly utilizing the measurements of different types of sensors that are located both inside and around the underground pipelines. By adopting an MI waveguide technique, the measurements of different types of the sensors throughout the pipeline network can be reported to the administration center in real-time. The system architecture and operational framework of MISE-PIPE is first developed. Based on the operational framework, research challenges and open research issues are then discussed.
In this paper, we assess the state of the art of Quality of Services (QoS) support in wireless sensor networks (WSNs). Unlike traditional end-to-end multimedia applications, many non-end-to-end mission-critical applications envisioned for WSNs have brought forward new QoS requirements on the network. Further, unique characteristics of WSNs, such as extremely resource-constrained sensors, large-scale random deployment, and novel data-centric communication protocols, pose unprecedented challenges in the area of QoS support in WSNs. Thus, we first review the techniques for QoS support in traditional networks, analyze new QoS requirements in WSNs from a wide variety of applications classified by data delivery models, and propose some non-end-to-end collective QoS parameters. Next, the challenges of QoS support in this new paradigm are presented. Finally, we comment on current research efforts and identify many exciting open issues in order to stimulate more research interest in this largely unexplored area.
We present in this paper an investigation of a special class of wireless sensor networks for monitoring critical infrastructures that may extend for hundreds of miles in distances. Such networks are fundamentally different from traditional sensor networks in that the sensor nodes in this class of networks are deployed along narrowly elongated geographical areas and form a chain-type topology. Based on careful analysis of existing sensor network architectures, we first demonstrate the need to develop new architecture and networking protocols to match the unique topology of chain-type sensor networks. We then propose hierarchical network architecture that consists of clusters of sensor nodes to enable the chain-type sensor networks to be scalable to cover typically long range infrastructures with tolerable delay in network-wide data collection. To maintain energy efficient operations and maximize the lifetime for such a chain-type sensor network, we devise a smart strategy for the deployment of cluster heads. Protocols for network initialization and seamless operations of the chain-type sensor networks are also developed to match the proposed hierarchical architecture and cluster head deployment strategy. Simulations have been carried out to verify the performance of the hierarchical architecture, the smart node deployment strategy, and the corresponding network initialization and operation protocols.
Real-time wireless sensor networks are becoming more and more important by the requirement of message delivery timeliness in emerging new applications. Supporting real-time QoS in sensor networks faces severe challenges due to the wireless nature, limited resource, low node reliability, distributed architecture and dynamic network topology. There are tradeoffs between different application requirements including energy efficiency and delay performance. This paper studies the state of the art of current real-time solutions including MAC protocols, routing protocols, data processing strategies and cross-layer designs. Some research challenges and future design favors are also identi¯ed and discussed.
Ad hoc and sensor networks is a new area of research which is rapidly growing due to the development of new technologies in inexpensive sensors. These electronic devices have increased capabilities in processing speed, memory, communication and networking [21][22]. Such sensor networks have a vast amount of applications including environmental monitoring, military, ecology, agriculture, inventory control, robotics and health care. This paper discusses the issues and challenges in the use of this new and very promising technology in the protection and monitoring of the critical and essential infrastructures of pipelines carrying oil, gas, water, and other important resources. The paper presents an architectural model that can be used to provide this monitoring and control functions. The model includes an overview of networking and routing protocols that can be used to provide the necessary communications. In addition, the paper provides discussions and recommendations concerning network reliability and the use of different wireless sensor technologies and protocols.
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.
Energy savings optimization becomes one of the major concerns in the wireless sensor network (WSN) routing protocol design, due to the fact that most sensor nodes are equipped with the limited nonrechargeable battery power. In this paper, we focus on minimizing energy consumption and maximizing network lifetime for data relay in one-dimensional (1-D) queue network. Following the principle of opportunistic routing theory, multihop relay decision to optimize the network energy efficiency is made based on the differences among sensor nodes, in terms of both their distance to sink and the residual energy of each other. Specifically, an Energy Saving via Opportunistic Routing (ENS_OR) algorithm is designed to ensure minimum power cost during data relay and protect the nodes with relatively low residual energy. Extensive simulations and real testbed results show that the proposed solution ENS_OR can significantly improve the network performance on energy saving and wireless connectivity in comparison with other existing WSN routing schemes.
Lossy transmission is a common problem for monitoring systems based on wireless sensors. Reliable communication protocols, which enhance communication reliability by repetitively transmitting unreceived packets, is one approach to tackle the problem of data loss. An alternative approach allows data loss to some extent and seeks to recover the lost data from an algorithmic point of view. Compressive sensing (CS) provides such a data loss recovery technique. This technique can be embedded into smart wireless sensors and effectively increases wireless communication reliability without retransmitting the data; the promise of this approach is to reduce communication and thus power savings. The basic idea of CS-based approach is that, instead of transmitting the raw signal acquired by the sensor, a transformed signal that is generated by projecting the raw signal onto a random matrix, is transmitted. Some data loss may occur during the transmission of this transformed signal. However, according to the theory of CS, the raw signal can be effectively reconstructed from the received incomplete transformed signal given that the raw signal is compressible in some basis and the data loss ratio is low. Specifically, this paper targets to provide accurate compensation for stationary and compressible acceleration signals obtained from structural health monitoring (SHM) systems with data loss ratio below 20%. This CS-based technique is implemented into the Imote2 smart sensor platform using the foundation of Illinois Structural Health Monitoring Project Service Tool-suite. To overcome the constraints of limited onboard resources of wireless sensor nodes, a method called random demodulator (RD) is employed to provide memory and power efficient construction of the random sampling matrix. Adaptation of RD sampling matrix is made to accommodate data loss in wireless transmission and meet the objectives of the data recovery. The embedded program is tested in a series of sensing and com- unication experiments. Examples and parametric study are presented to demonstrate the applicability of the embedded program as well as to show the efficacy of CS-based data loss recovery for real wireless SHM systems.
Interference between concurrent transmissions can cause severe performance degradation in wireless sensor networks (WSNs). While multiple channels available in WSN technology such as IEEE 802.15.4 can be exploited to mitigate interference, channel allocation can have a significant impact on the performance of multi-channel communication. This paper proposes a set of distributed protocols for near-optimal channel allocation in WSNs with theoretical bounds. We first consider the problem of minimizing the number of channels needed to remove interference in a WSN, and propose both receiver-based and link-based distributed channel allocation protocols. Then, for WSNs with an insufficient number of channels, we formulate a fair channel allocation problem whose objective is to minimize the maximum interference (MinMax) experienced by any transmission link in the network. We prove that MinMax channel allocation is NP-hard, and propose a distributed link-based MinMax channel allocation protocol. Finally, we propose a distributed protocol for link scheduling based on MinMax channel allocation that creates a conflict-free schedule for transmissions. The proposed decentralized protocols are efficient, scalable, and adaptive to channel condition and network dynamics. Simulations based on the topologies and data traces collected from a WSN testbed of 74 TelosB motes have shown that our channel allocation protocols significantly outperform a state-of-the-art channel allocation protocol.
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.
Designing of multi-hop Wireless Sensor Network (WSN) depends upon the requirements of the underlying sensing application. The main objective of WSNs is to monitor physical phenomenon of interest in a given Region of Interest using sensors and provide collected data to sink. WSN is made of large number of energy, communication and computational constraint nodes, to overcome energy constrains replacing or recharging the batteries of the WSN nodes is impossible task, once they are deployed in a hostile environments. Therefore, to keep the network alive as long as possible, communication between the WSN nodes must be done with load balancing. Time critical applications like forest fire detection, battle field monitoring demands reception of data by the sink with the bounded delay to avoid disasters. Hence, there is a need to design a protocol which enhances the network lifetime and provides information to the sink with a bounded delay. The paper will address this problem and solution. In the paper, a routing algorithm is proposed by introducing Energy Delay Index for Trade-off (EDIT) to optimize both objectives – energy and delay. EDIT is used to select Cluster Heads (CHs) and “next hop” by considering energy and/or delay requirements of a given application. Proposed approach is derived using two different aspect of distances between a node and the sink named Euclidean distance and Hop-count, and further proven using realistic parameters of radio to get data closest to the test bed implementation. The results aspires to give sufficient insights to others before doing test bed implementation.
Wireless sensor networks (WSNs) are a target technology for oil and gas pipeline monitoring because they offer benefits of low cost, ease of deployment and ability to cater for data acquisition at great spatial and temporal scales. In order for WSN to achieve trademark performance in remote monitoring of pipelines, and surpass the performance of present-day traditional monitoring systems, certain design requirements must be met. In this paper, we identify vital design issues that must be considered to facilitate the employment of WSN for pipeline monitoring. We classify these design issues into five different categories namely; sensing modality, power efficiency, energy harvesting, network reliability and localization. In addition, we discuss the concept of cooperative communication for pipeline-monitoring sensor networks deployed in sub-sea environments. We also study the employment of sensor networks for monitoring underground pipelines. Our findings are based on extensive study of the recent literature and comprehensive survey of existing WSN technologies. The WSN design considerations presented in this paper are particularly prolific for pipeline monitoring scenarios, they can however be easily extended to other oil and gas infrastructures. For example; well-head and heat exchanger monitoring, oil platform process monitoring, monitoring of natural gas storage facilities and data collection on coastal infrastructures that could support oil and gas exploration.
We are interested in event collection in a 2D region where sensors are deployed to detect and collect interested events. Using traditional multi-hop routing in wireless sensor networks to report events to a sink node or base station, will result in severe imbalanced energy consumption of static sensors. In addition, full connectivity among all the static sensors may not be possible in some cases since generally the sensors are randomly deployed in the target region. In this paper, we exploit a mobile sensor as the sink node to assist the event collection by controlling the movement of the mobile sink to collect static sensor readings. A key observation of our work is that an event has spatial-temporal correlation. Specifically, the same event can be detected by multiple nearby sensors within a period of time. Thus, it is more energy-efficient if the mobile sink can selectively communicate with only a portion of static sensors, while still collecting all the interested events. In this paper, we discuss the event collection problem by leveraging the mobility of the sink node and the spatial-temporal correlation of the event, in favor of maximizing the network lifetime with a guaranteed event collection rate. We first model the problem as sensor selection problem and show that it could be solved in polynomial time, if global knowledge of events is available and there is no velocity constraints on mobile sink. We also analyze the design of a feasible movement route for mobile sink to minimize the velocity requirements for a practical system. An online scheme is then proposed to relax the assumption about global knowledge of events and we prove that the expected event collection rate can be guaranteed in theory. Through comprehensive simulation on real trace data, we demonstrate that the network lifetime can be significantly extended, comparing to some other schemes.
The imminent growth of user-centric, pervasive sensing environments promotes sink mobility in an increasing number of event-based, sensor network applications including rescue missions, intrusion detection, and smart buildings. In these settings, one of the most critical challenges toward supporting quality of service, is effective distributed congestion avoidance. Congestion control techniques have been proposed in sensor networks mostly in the context of a static sink. In our work, we study the problem of traffic management in the context of sensor networks with a mobile sink. Under sink mobility, various new challenges arise that need to be effectively addressed. Adaptation to sink mobility requires agile as well as effective load estimation techniques. In addition, unlike static networks, path reliability often fluctuates due to path reconfigurations. Thus, injecting traffic during transient periods of poor path quality might wastefully detain network resources. In this work, we first study the effect of sink mobility on traffic load in sensor networks. We then propose adaptive routing as well as load estimation techniques that effectively adapt to sink relocations. A novel aspect of our approach is that it jointly considers the network load as well as path quality variations to facilitate intelligent, mobility-adaptive rate regulation at the sources. We provide a thorough study of the trade-offs induced due to persistent path quality variations and conduct extensive real MICA2-based testbed experiments to study the performance of the sensor network under sink mobility.
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.
In this paper, we present Railroad, a data dissemination architecture for large-scale wireless sensor networks. Railroad system proactively exploits a virtual infrastructure called Rail, which is an area where all the metadata of event data are stored. There is only one Rail in the network and it acts as a rendezvous area of the events and the queries. Rail is placed in the middle area of the field so that every node can easily access it. Once a query is issued, it circulates around Rail and searches relevant data stored in Rail. When a relevant metadata is found, the source node of the data transmits the corresponding data to the sink node which has issued the query. By using Rail, Railroad achieves a scalable and energy-efficient data dissemination architecture under dynamic conditions with multiple mobile observers and targets. We evaluate and compare the communication cost and the hot spot message complexity of Railroad with previous approaches.
We investigate the benefits of a heterogeneous architecture for wireless sensor networks (WSNs) composed of a few resource rich mobile relay nodes and a large number of simple static nodes. The mobile relays have more energy than the static sensors. They can dynamically move around the network and help relieve sensors that are heavily burdened by high network traffic, thus extending the latter's lifetime. We first study the performance of a large dense network with one mobile relay and show that network lifetime improves over that of a purely static network by up to a factor of four. Also, the mobile relay needs to stay only within a two-hop radius of the sink. We then construct a joint mobility and routing algorithm which can yield a network lifetime close to the upper bound. The advantage of this algorithm is that it only requires a limited number of nodes in the network to be aware of the location of the mobile relay. Our simulation results show that one mobile relay can at least double the network lifetime in a randomly deployed WSN. By comparing the mobile relay approach with various static energy-provisioning methods, we demonstrate the importance of node mobility for resource provisioning in a WSN.
