Load management scheme for energy holes reduction in wireless sensor networks

Chanak, Prasenjit; Banerjee, Indrajit; Rahaman, Hafizur

doi:10.1016/j.compeleceng.2015.05.013

Cited by 25 publications

(16 citation statements)

References 23 publications

(35 reference statements)

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“…The energy‐related issues in WSNs have prompted the designing of numerous latest routing strategies, especially clustering techniques or routing strategies for enhancing network lifetime. For the research community, retaining the energy of routing protocols for longer duration is still an open challenge in WSNs 25–37 . The basic thought of clustering in WSNs is to divide the network into a small group of sensor nodes, in which one CH is included; others are the member nodes.…”

Section: Related Workmentioning

confidence: 99%

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

Anand

Pandey

2020

Int J Communication

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SummaryWireless sensor networks (WSNs) not only have become an essential technology in the current scenario but also has been established as a core technology for many applications, like the Internet of Things (IoT). The drawback of limited energy resources in WSN creates the challenge of designing an energy‐efficient network topology and routing path. As these devices are generally not attended for any maintenance, such as battery replacement or charging, these resources need to be intelligently used. The paper represents a methodology for enhancing the lifetime of a network by using a genetic algorithm‐based clusteringand particle swarm optimization‐based routing in WSN. The best cluster head (CH) that collects the data from the remaining nodes is selected using a genetic algorithm, which considers distance and energy parameters. Further, the particle swarm optimization algorithm depends on optimal routing paths that are chosen for all relay nodes to send data to the Base Station (BS). The proposed procedure shows that the relay node supports and facilitates communication among the sink and CH, which enhances energy efficiency. Finally, the quality of service (QoS) of the WSNs is improved, due to which the system would survive longer. The results of simulated experiments show that the proposed approach significantly increases the lifetime of WSN and that energy consumption is reduced when compared with the existing protocols.

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Section: Related Workmentioning

confidence: 99%

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

Anand

Pandey

2020

Int J Communication

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“…9 Most of the unequal clustering algorithms can balance energy consumption and prolong network lifetime. Chanak et al 10 proposed a new cluster-based load management scheme which can balance energy consumption of the deployed sensor nodes and reduce energy holes from the network by balancing the communication load as equally as possible. Energyefficient unequal clustering (EEUC) 11 is the first unequal cluster-based routing protocol to mitigate the energy hole problem.…”

Section: Related Workmentioning

confidence: 99%

Avoidance of energy hole problem based on feedback mechanism for heterogeneous sensor networks

Peng

Jian-hui

Chen

et al. 2017

International Journal of Distributed Sensor Networks

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The application-based wireless sensor networks have the energy hole problem when considered for performance measures in balancing the energy load. To avoid the energy hole problem for heterogeneous sensor networks, a feedback mechanism-based unequal clustering algorithm is proposed. In the initial stage of the network, this article divides the network into several layers with different layer heights by only considering the distance from nodes to the sink. Then, this article introduces a feedback mechanism and dynamically changes the size of each cluster according to the feedback value calculated by the sink. After the size of each cluster varies for several rounds, the energy consumption between each cluster will tend to be balanced. To save the energy consumption cost of receiving the sink feedback signal, this article proposes the termination condition for the feedback process. When the termination condition is satisfied, the feedback process finishes and the network turns into the stable clustering stage. The simulation results show that compared with the existing algorithms of data transmission, feedback mechanism-based unequal clustering algorithm can make better use of node energy and prolong the network lifetime.

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“…Liu et al [12] designed WSNs to optimize their energy consumption. Chanak et al [13] considered ways to deploy sensors to balance WSN energy consumption. Collotta et al [14] and Kumar and Chaturvedi [15] aimed to optimize the energy efficiency of dynamic WSNs via fuzzy methods.…”

Section: Introductionmentioning

confidence: 99%

Improve Energy Consumption and Signal Transmission Quality of Routings in Wireless Sensor Networks

et al. 2020

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Wireless (smart) sensor networks (WSNs) comprise a myriad of embedded wireless smart sensors. They play a cardinal role in the functioning of many applications, such as the Internet of Things, smart grids, smart production systems, and smart homes, which ultimately render them paramount instruments in the modern age. Recent advances in WSNs have resulted in the rapid development of sensors. However, WSNs will only able to achieve better execution efficiencies if their energy consumption-owing to limited battery life and difficulty of recharging-can be better controlled. Moreover, signal transmission quality determines WSN performance. Hence, two main concerns-energy consumption and signal transmission quality-should be addressed to improve the performance of WSNs. Thus, a new bi-objective simplified swarm optimization algorithm (bSSO) is proposed by employing the concepts of simple routing, SSO, and crowd distance. The performance and applicability of the proposed bSSO using eight different parameter settings are demonstrated through an experiment involving ten WSN benchmarks ranging from 100 to 1000 sensors. The proposed algorithm is then compared with NSGA-II, which is an algorithm widely used to solve multi-objective problems. The results show that the proposed bSSO can successfully achieve the aim of this work.

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Load management scheme for energy holes reduction in wireless sensor networks

Cited by 25 publications

References 23 publications

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

New approach of GA–PSO‐based clustering and routing in wireless sensor networks

Avoidance of energy hole problem based on feedback mechanism for heterogeneous sensor networks

Improve Energy Consumption and Signal Transmission Quality of Routings in Wireless Sensor Networks

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