Energy Hole Problem Research Articles

Energy and Network Balanced Distributed Clustering in Wireless Sensor Network

Balancing energy consumption of sensor nodes to extend the network lifetime is a major concern for the energy constrained wireless sensor network. Improper load balance and disproportionate energy consumption of sensor nodes during network activities such as transmitting and receiving of data cause energy hole problem and shorten the lifetime of the network. Many research works cited that clustering mechanism and the use of mobile sink can be effective to mitigate the energy hole problem and can improve the network lifetime. But using a mobile sink causes extra delay which is a major concern if the network is delay bound. In this work, we give deep insight into the problem of disproportionate energy consumption and aim to improve the network load balance and increase the network lifetime by applying efficient distributed clustering method with the help of a mobile sink. The proposed scheme named Energy Balanced Distributed Clustering Protocol (EBDCP) guarantees to transmit the sensed data to the base station within the tour deadline with the aid of a mobile sink. For this purpose, an efficient sojourn point determination algorithm has also been proposed. The simulation results prove that the proposed scheme performs significantly better than the existing works in terms of the energy distribution in the network, clustering overhead, residual energy of the network, number of alive nodes and network lifetime.

Selection of Optimal Deployment and Routing Configurations in Underwater Acoustic Sensor Networks for Avoiding Energy Holes

Improving the energy efficiency of underwater acoustic sensor networks (UW-ASNs) is a crucial issue due to the reduced and nonrechargeable energy resource of the underwater sensor nodes. In this work, we address the energy sink hole problem in UW-ASNs while considering the unique and harsh characteristics of the underwater channel. Our goal is to determine the optimal deployment and routing settings that surmount the energy sink hole problem and hence maximize the network lifetime. We prove that sensors can evenly consume their initial battery power provided that first they adjust their transmission power when they transmit the route through traffic and second they are appropriately placed while deployed. Mainly, we propose a deployment scheme and the corresponding balanced routing strategy that lead to uniform energy consumption among all underwater sensors subject to a predefined reliability level at the sink. Specifically, we look for the optimal deployment settings especially in terms of nodes’ separation distances that help achieving uniform energy consumption in the network while satisfying the application requirement especially in terms of desired information reliability. Jointly, at the routing layer, we assume that each sensor is provided with the possibility of dynamically adjusting its transmission power up to a given number of levels N. To this goal, we mainly deal with two main cases: fixed and variable nodes separation distance. For the fixed case, we suppose that any two successive nodes in the network are equally spaced, and we strive for deriving the optimal distance as well as the optimal number of transmission power levels along with optimal load weight corresponding to every possible transmission power level for every sensor node. For the variable case, we deal with two subcases: first, we suppose that the distance separating successive nodes follows an arithmetic progression, and second, we assume that the distance separating successive nodes is following a geometric sequence. Note that for both cases, namely, fixed and variable, we succeed to determine the optimal distances separating successive nodes and the optimal number N of transmission power levels along with the corresponding optimal load weight that overcome the energy holes problem, and hence the network lifespan is maximized while respecting the desired reliability level.

Self‐stabilising hybrid connectivity control protocol for WSNs

In this study, the authors address the problem of combining hierarchical and flat techniques to construct and maintain nodes’ connectivity as well as links’ symmetry (bidirectionality) in a wireless sensor network (WSN) comprising static nodes. They propose a localised and asynchronous self-stabilising hybrid message passing a solution that seamlessly merges three well known connectivity control techniques for such ad hoc networks, namely k -hop clustering , power control (transmission range adjustment) and sleep/wake scheduling. Their stigmergy-based strategy (i.e. inspired from ants’ pheromone-based communication, division of labour and swarming behaviours) allows a WSN to simultaneously cope with issues such as scalability, fault tolerance, transmission range minimisation, energy hole problem (i.e. premature node deaths in the vicinity of the sink), channel overhearing and signalisation reduction. To the best of their knowledge, such a solution does not exist in the literature. The few self-stabilising hybrid connectivity control protocols currently proposed use only two of the above-mentioned techniques. The authors formally prove the correctness of their scheme and its self-stabilisation property under an unfair distributed daemon. Simulation results show that the proposed scheme has a low average convergence time, is energy efficient and can prolong network lifetime.

Energy-Efficient Trajectory Planning Algorithm Based on Multi-Objective PSO for the Mobile Sink in Wireless Sensor Networks

In wireless sensor networks (WSNs), collecting data with mobile sinks is an effective way to solve the “energy hole problem”. However, most of existing algorithms of mobile sinks ignore the load balance of rendezvous nodes, which will significantly shorten the network lifetime. Moreover, most mobile sinks are usually required to visit locations of sensor nodes without taking advantage of their communication ranges. Therefore, this paper proposes an energy-efficient trajectory planning algorithm (EETP) based on multi-objective particle swarm optimization (MOPSO) to shorten the trajectory length of the mobile sink and balance the load of rendezvous nodes. EETP aims to reduce the delay in data delivery and prolong the network lifetime. To shorten the trajectory length of the mobile sink, we design a mechanism to select potential visiting points within communication overlapping ranges of sensor nodes, rather than locations of sensor nodes. Additionally, according to trajectory characteristics of the mobile sink, we design an effective trajectory encoding method that can generate a trajectory containing an unfixed number of visiting points. The simulation results show that the proposed EETP is superior to existing WRP, CB and the MOPSO-based algorithm, in terms of delay in data delivery, network lifetime and energy consumption.

Regulating the Packet Transmission Cost of Source Location Privacy Routing Schemes in Event Monitoring Wireless Networks

Sensor nodes in wireless sensor networks (WSNs) are usually battery-operated and resource-constrained. The sensor nodes are often deployed in remote areas where the batteries cannot easily be recharged or replaced. Consequently, power becomes a limited resource in WSNs. Thus, energy consumption of the sensor nodes is among parameters of paramount importance. Subsequently, source location privacy (SLP) routing schemes must be energy-efficient and overall cost-effective. Angle-based routing schemes can cost-effectively protect the SLP. The goal of this study is to propose a new path node offset angle routing algorithm to improve the packet transmission cost of two existing SLP routing schemes. The proposed algorithm considers path node offset angles, arbitrary factors, and contrived regions to compute relatively short but greatly randomized routing paths. The routes offer a reduced number of packet forwarding events in the near-sink region and eventually diminish the packet transmission cost. Performance analysis results verify that the proposed path node offset angle routing algorithm effectively improves the packet transmission cost of the schemes and guarantees strong SLP protection throughout the WSN domain. Furthermore, the routing algorithm is capable of alleviating the energy-hole problem.

Energy Efficient Data Collection Algorithm for Mobile Wireless Sensor Network

Wireless sensor network (WSN) with mobile sink serves a lot of industrial and agricultural monitoring applications. The data collection with WSN has been popularly known in many applications such as smart environments, health monitoring, habitat monitoring, surveillance and tracking systems. The mobile sink moves to the corresponding cluster and gathers the data and moves to the next cluster head (CH) for the same. The data loss and waiting time of the data in the CH results from energy consumption and work repetition. This article provides a novel energy efficient data collection scheme. The data collection is done by the sink in a Polling based M/G/1 server model. The cluster member (CM) sends the data in N threshold model to the CH. The CH gathers the data from the CM and reports to sink once it arrives nearby. The energy efficient cluster head selection algorithm is evaluated with the proposed model and the waiting time is analyzed. The data arrival from the CM to the CH is considered as Poisson in nature. The sink mobility with respect to polling system is analyzed. The sink data collection is done through dynamic polling mechanism based on the CH arrival rate. The proposed algorithm outperforms the modified low energy adaptive clustering hierarchy and energy-aware multi-hop routing protocol (M-GEAR) protocols in terms of lifetime, waiting time and throughput. The proposed algorithm provides high resistance to energy hole and HOTSPOT problem.

A Two-Tier Distributed Fuzzy Logic Based Protocol for Efficient Data Aggregation in Multihop Wireless Sensor Networks

This study proposes a two-tier distributed fuzzy logic based protocol (TTDFP) to improve the efficiency of data aggregation operations in multihop wireless sensor networks (WSNs). Clustering is utilized for efficient aggregation requirements in terms of consumed energy. In a clustered network, member (leaf) nodes transmit obtained data to cluster-heads (CHs) and CHs relay received packets to the base station. In multihop wireless networks, this CH-generated transmission occurs over other CHs. Due to the adoption of a multihop topology, hotspots and/or energy-hole problems may arise. This article proposes a TTDFP to extend the lifespan of multihop WSNs by taking the efficiency of clustering and routing phases jointly into account. TTDFP is a distribution-adaptive protocol that runs and scales sensor network applications efficiently. Additionally, along with the two-tier fuzzy logic based protocol, we utilize an optimization framework to tune the parameters used in the fuzzy clustering tier in order to optimize the performance of a given WSN. This paper also includes performance comparisons and experimental evaluations with the selected state-of-the-art algorithms. The experimental results reveal that TTDFP performs better than any other protocols under the same network setup considering metrics used for comparing energy-efficiency and network lifespan of the protocols.

Inter- and intra-cluster movement of mobile sink algorithms for cluster-based networks to enhance the network lifetime

Due to limited resources of the sensor nodes energy efficiency is an important performance metric to evaluate the wireless sensor networks (WSN). In cluster-based WSNs, the cluster heads (CH) located around base station (BS) consume more energy and exhaust their energy supplies faster than other ones which leads to energy hole problem and premature network death. Furthermore, single-hop transmission manner is usually applied for intra-cluster communication, therefore the member nodes (MN) located farther away from CHs die sooner than other MNs, which leads to coverage holes and reduce the network performance. In this paper, we propose mobile sink (MS) based inter- and intra-cluster routing algorithms. The first algorithm aims to solve the unbalanced energy consumption of CHs, which results in enhanced network lifetime. Likewise, the goal of the second algorithm is to balance the energy consumption of MNs, which results in improved coverage time of the network. In the proposed mechanism, MSs move along clusters and stay in each cluster for a limited sojourn time calculated via first algorithm. Then, the optimal sojourn positions of MSs in the clusters are determined via second algorithm. Simulation results reveal that the proposed algorithms enhance the network performance in terms of different performance evaluation metrics.

Improved clustering with firefly-optimization-based mobile data collector for wireless sensor networks

To maximize the network lifetime of a wireless sensor network, an efficient transmission technique is critical. The energy constraint is a crucial factor in the sensor network because the sensor nodes are typically battery-run and it is impossible or difficult to recharge them in most application scenarios. Unbalanced data transference in the communication channel frequently produces an energy hole problem, which causes the premature death of the sensor nodes and reduces the network lifetime. To resolve this issue and improve the network lifetime, the proposed approach adjusts the transmission range according to the distances between the cluster heads and their members. Furthermore, a mobile data collector based on the firefly optimization algorithm is employed to increase the network lifetime. The proposed algorithm is compared with standard benchmark algorithms in several scenarios. The simulation results demonstrate that the proposed algorithm outperforms existing algorithms with respect to the network lifetime.

A Type of Annulus-Based Energy Balanced Data Collection Method in Wireless Rechargeable Sensor Networks.

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.

Optimization energy consumption with multiple mobile sinks using fuzzy logic in wireless sensor networks

Each sensor in WSNs receives data from the limited area under its coverage. The received data is processed by the sensor; then, it is wirelessly transmitted to the sink. Sensors’ energy consumption and the energy hole problem are considered as outstanding challenge of these networks. That is, since sensors use batteries with limited lifetimes and sensors which are closer to the sink transmit more data than remoter sensors, hence, they run up their energies sooner than other sensor nodes. Consequently, optimizing energy consumption is regarded as one of the most critical issues throughout a network’s operational lifetime. In this paper, by dividing a respective area into several smaller areas and using a multiple mobile sink (MS), we proposed an unequal clustering method via fuzzy logic which leads to the reduction of distances among sensors with respect to the movement direction of sink. As a result, the sizes of clusters are reduced. Accordingly, such a reduction in the sizes of clusters and the smart selection of the route by the MS eliminates energy hole issue. Regarding the metrics of FND and HNA, it was found that the proposed method optimized energy consumption for 19%. Hence, it was able to fix energy hole problem in WSNs.

Energy-efficient sink placement in wireless sensor networks

Prolonging a wireless sensor network’s lifetime is closely related to energy consumption and particularly the energy hole problem, where sensor nodes close to the sink consume a considerable amount of their energy for relaying purposes. To tackle the energy hole problem’s effects, this paper proposes an analytical model for analyzing the available energy in the network. The next step is to analytically model the overall energy consumption as a k-median facility location problem, its solution corresponding to the location of k sinks in the network.As analytically shown, when k sinks are placed according to the solution of the previous facility location problem, then the overall energy consumption is minimized, resulting in a higher energy-saving system. Thus, the saved energy can be further utilized, e.g., to extend the network’s lifetime and support modern replenishing techniques such as energy harvesting and battery recharging.Simulation results validate the analytical model that is the basis of the analysis and confirm the results with respect to the available energy in the network. In particular, significant energy savings are observed when the analytical results are applied, thus resulting in better energy utilization and subsequent network lifetime increment.

Improved network lifetime and avoidance of uneven energy consumption using load factor

In wireless sensor networks, communication load over a network is not uniform and hence the nodes closer to higher load area (near to sink node) exhaust their energy quickly than nodes situated other areas, i.e. hot spot or energy hole problem. This may lead to network partition into many unreachable segments and therefore affect the performance of the network. This problem is very critical for the random deployed networks. Therefore, we propose a load balancing method based upon the modifications in the sensing and communication ranges that overcomes the non-uniform load problem (energy hole) and also ensure full coverage and connectivity with least possible nodes. This approach controls the energy disparity by dividing the network into many segments (clusters) and then providing a suitable set of communication and sensing ranges for each segment based on its load. After fixing these parameters, the nodes can get the similar energy consumption and consequently network lifetime is enhanced. The proposed method is examined analytically and verified through Matlab tool based simulation experiments. The results exhibit improvement over the existing methods.

Specifying the Optimal Transmission Manner in WSNs: Analysis and Simulation

Employing multi-hop transmission (MH) in wireless sensor networks achieves the uniform distribution of energy cost between nodes. However, the minimum energy cost isn’t completely guaranteed. Therefore, in several cases, the total energy cost might be greater than direct transmission (DT). In this paper, we are interested in determining the factors that influence choosing the efficient transmission manner. It’s assumed that there is a judging metric, called characteristic distance $$d_{char}$$ that specifies whether to use DT or MH. If the transmission distance is greater than $$d_{char}$$ MH is used, else DT is preferred. The previous conclusion is obtained through the following three steps: The first step is to analyze the relation between the radio hardware parameters and the consumed energy of the different transmission techniques. Hence, a general law for $$d_{char}$$ will be deduced. Secondly, a supplementary analysis will be performed to understand the effect of these parameters on $$d_{char}$$ . Finally, a great concern is paid to estimate efficient design of cluster size in cluster-based routing protocols. Therefore, $$d_{char}$$ and the radio hardware parameters are exploited in specifying the optimum size of the cluster. The proposed design consumes the least energy cost and minimizes the variance of nodes residual energy in comparison with DT, MH and normal clustering. This helps in avoiding energy hole problem and enhancing the network lifetime.

ACO-based mobile sink path determination for wireless sensor networks under non-uniform data constraints

In wireless sensor networks, a mobile sink is used to collect data from sensors by traversing the network periodically to prevent hotspot or energy-hole problem. In order to avoid the delay incurred by visiting all the sensor nodes, a mobile sink may allow visiting only a few number of locations or nodes referred as rendezvous points and remaining nodes send their data to the nearest rendezvous point. Finding an optimal set of rendezvous points will improve the data gathering process of the sink and also maximize the network lifetime. However, it is more challenging to find an optimal set of rendezvous points and traveling path of the mobile sink when the sensor node generates data unevenly. In this paper, we propose a new Ant Colony Optimization-based mobile sink path determination for wireless sensor networks. The objective of the proposed algorithm is to maximize the network lifetime and minimize the delay in collecting data from the sensor nodes. In the proposed algorithm, we devise an efficient mechanism to find a near-optimal set of rendezvous points and traveling path of the mobile sink to achieve the desired objectives. The proposed algorithm also adopts re-selection of rendezvous points to balance the energy consumption of the sensors. Through simulation runs, we show that the proposed algorithm outperforms the existing ones.

Energy Efficient Energy Hole Repelling (EEEHR) Algorithm for Delay Tolerant Wireless Sensor Network

Reducing energy consumption and increasing network lifetime are the major concerns in Wireless Sensor Network (WSN). Increase in network lifetime reduces the frequency of recharging and replacing batteries of the sensor node. The key factors influencing energy consumption are distance and number of bits transmitted inside the network. The problem of energy hole and hotspot inside the network make neighbouring nodes unusable even if the node is efficient for data transmission. Energy Efficient Energy Hole Repelling (EEEHR) routing algorithm is developed to solve the problem. Smaller clusters are formed near the sink and clusters of larger size are made with nodes far from the sink. This methodology promotes equal sharing of load repelling energy hole and hotspot issues. The opportunity of being a Cluster Head (CH) is given to a node with high residual energy, very low intra cluster distance in case of nodes far away from the sink and very low CH to sink distance for the nodes one hop from the sink. The proposed algorithm is compared with LEACH, LEACH-C and SEP routing protocol to prove its novel working. The proposed EEEHR routing algorithm provides improved lifetime, throughput and less packet drop. The proposed algorithm also reduces energy hole and hotspot problem in the network.

Temperature-Aware Routing Using Secondary Sink in Wireless Body Area Sensor Network

Wireless Body Area Sensor Network (WBASN) is a developing application of Wireless Sensor Network (WSN) which is very useful in diagnosis of human health remotely. Tiny and smart sensors are placed inside or outside of human body which collects useful data time to time from various parts of body and send it to the corresponding medical staff or doctor. In the future, WBASN will surely make a huge change in traditional health monitoring system and will be helpful for elderly people and patients who suffer from difficult physical mobility. WBASN have many challenges while its design and one of main challenge is controlling temperature rise of sensor node during routing when placed inside human body because temperature rise beyond certain limit will be harmful for human body. The study of controlling temperature rise of sensor nodes during data routing comes under the category of Temperature Aware Routing Protocols. In this article the authors have raised a problem called “Energy Hole Problem” under Temperature Aware Routing Protocols which affects the performance of a network.

A recharging distance analysis for wireless sensor networks

Efficient energy consumption is a challenging problem in wireless sensor networks especially close to the sink node, known as the energy hole problem. Various policies for recharging battery exhausted nodes have been proposed using special recharging vehicles. The focus in this paper is on a simple recharging policy that permits a recharging vehicle, stationed at the sink node, to move around and replenish any node’s exhausted battery when a certain recharging threshold is violated. The minimization of the recharging distance covered by the recharging vehicle is shown to be a facility location problem, and particularly a 1-median one. Simulation results investigate various aspects of the recharging policy – including an enahnced version – related to the recharging threshold and the level of the energy left in the network nodes’ batteries. In addition, it is shown that when the sink’s positioning is set to the solution of the particular facility location problem, then the recharging distance is minimized irrespectively of the recharging threshold.

Comparative Study of Different Cost Functions Between Neighbors for Optimizing Energy Dissipation in WSN

Lifetime of a battery is one of the major concerns in wireless sensor networks (WSNs). The traditional network algorithm chooses the data transmission path based on the distance between sender and receiver. For example, in directed diffusion, the nodes closer to the sink node are more active so that the continuous data flow of the network is maintained. However, in such a scenario, there is an energy hole problem because the nodes closer to the sink reduce their energy since they are more active. But if the residual energy and shortest hop counts can be taken together, then the problem can be overcome. We have analyzed different transmission cost functions with respect to approximated uniform energy dissipation directed diffusion algorithm. The final goal of the paper is to find out the suitable cost function to resist the early death of the first node of a network. We introduce dynamic priority variable, which is a tradeoff between total energy consumption and uniform energy dissipation.

Retransmission Avoidance for Reliable Data Delivery in Underwater WSNs.

The energy-efficient and reliable delivery of data packets in resource constraint underwater wireless sensor networks (UWSNs) is one of the key considerations to enhance the network lifetime. The traditional re-transmissions approach consumes the node battery and increases the communication overhead, which results in congestion and affects the reliable data packet delivery in the network. To ensure the reliability and conserve the node battery, in this paper, we propose adaptive forwarding layer multipath power control routing protocol to reduce the energy dissipation, achieve the data reliability and avoid the energy hole problem. In order to achieve the reliability, tree based topology is exploited to direct multiple copies of the data packet towards the surface through cross nodes in the network. The energy dissipation is reduced by a substantial amount with the selection of low noise path between the source and the destination including the information of neighbors of the potential forwarder node. Extensive simulation results show that our proposed work outperforms the compared existing scheme in terms of energy efficiency and packet received ratio (PRR).