Performance analysis for lifetime improvement of a regression based clustered network through cluster member allocation and secondary cluster head selection in a distributed WSN

Joshitha, K. Lakshmi; Jayashri, S.

doi:10.1007/s10586-017-1592-y

Cited by 8 publications

(4 citation statements)

References 13 publications

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Section: Introductionmentioning

confidence: 99%

“…Wireless sensor networks (WSNs) have evolved as an indispensable and significant method of facilitating pervasive computing for making suitable and applicable in diversified applications of deployment. 1 In WSNs, energy efficiency has emerged as one of the major challenge in research. The main focus in energy efficiency have attracted major focus due to the limitations enforced by the batteries used for energizing sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Hybrid shuffled frog leaping and improved biogeography‐based optimization algorithm for energy stability and network lifetime maximization in wireless sensor networks

Tamilarasan

Lenin²,

Jayapandian

et al. 2021

Int J Communication

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Wireless sensor networks are significantly used for data sensing and aggregating dusts from a remote area environment in order to utilize them in a diversified number of engineering applications. The data transfer among the sensor nodes is attained through the inclusion of energy efficient routing protocols. These energy efficient routing necessitates optimal cluster head selection procedure for handling the challenge of energy consumption to extend the stability and lifetime in the sensor networks. The implementation of energy efficient routing is still complicated even when the process of clustering is enhanced through the cluster head selection. The majority of the existing cluster head selection schemes suffer from the issues of poor selection accuracy, increased computation, and duplicate nodes' selection. In this paper, hybrid shuffled frog leaping and improved biogeography-based optimization algorithm (HSFLBOA) for optimal cluster head selection is proposed for resolving issues that are common in cluster head selection schemes. This proposed HSFLBOA used the objective function that used the parameters of node energy, data packet transmission delay, cluster traffic density, and internode distance in the cluster. The simulation results of the proposed HSFLBOA is determined to be significant in achieving superior throughput and network energy compared to benchmarked metaheuristic optimal cluster head schemes.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid shuffled frog leaping and improved biogeography‐based optimization algorithm for energy stability and network lifetime maximization in wireless sensor networks

Tamilarasan

Lenin²,

Jayapandian

et al. 2021

Int J Communication

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“…Because of the restrained energy-resource and failure prone dispositions of the network, the design of lifetime-enhancement and aggregation-aware routing solutions in WSN yet continues to be a challenging and significant research field in recent years [5], [6], [7], [8].With data aggregation, identical sensory packets can be amassed at some nodes and conveyed to the BS in single or multi-hop fashion. Notably, the strategy of aggregating similar data curtails the network's traffic, reduces collision overheads, and promotes low energy consumption at the nodes [7]. The design of routing scheme and network design are key factors that impact the aggregation performance.…”

Section: Introductionmentioning

confidence: 99%

Lifetime-enhancement Schemes for Power-constrained Routing in Wireless Sensor Networks: A Survey

2021

IJETER

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Notwithstanding the broad applicability of wireless sensor network (WSN), the successful development and deployment in various real-world applications is currently challenging. The node-devices are powered by constrained-batteries that are typically impossible to substitute after deployments. Therefore, WSNs are energy-constrained and liable to early failure while expected to run for long-terms without battery replenishments.Diverse researchers have recently presented specific lifetime enhancement routing solutions based on data aggregation technology targeted at reducing energy-consumption,and improving the communication reliability of various WSNs.This paper presents a brief survey of the research field of data aggregation-ware routingin energy-constrained WSN. The paper overviews and classifies various existing routing solutions based on their delivery models and also identifies someof their majordrawbacks.

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“…12 The clustering process is determined to be suitable for improving scalability in the sensor network as it derives the merits of local decisions by increasing the essentiality for central organization. 13 In the recent past, a diversified number of researchers have contributed a wide number of routing protocols for handling the issue of energy balance in the network during the process of clustering. 14 However, the majority of the clustering algorithms contributed in the literature are determined to suffer from some specific limitations that attribute towards high energy utilization, minimized network lifetime, large scalability, percentage of dead nodes, poor stability, poor adaptation, residual energy, energy coverage, information transmission delay, sensor nodes' unbalanced lifetime, and extra overhead on the network.…”

Section: Introductionmentioning

confidence: 99%

A hybrid elephant herding optimization and cultural algorithm for energy‐balanced cluster head selection scheme to extend the lifetime in WSNs

Murugadass

Poruran

2020

Int J Communication

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Summary Clustering‐based optimal cluster head selection in wireless sensor networks (WSNs) is considered as the efficient technique essential for improving the network lifetime. But enforcing optimal cluster head selection based on energy stabilization, reduced delay, and minimized distance between sensor nodes always remain a crucial challenge for prolonging the network lifetime in WSNs. In this paper, a hybrid elephant herding optimization and cultural algorithm for optimal cluster head selection (HEHO‐CA‐OCHS) scheme is proposed to extend the lifetime. This proposed HEHO‐CA‐OCHS scheme utilizes the merits of belief space framed by the cultural algorithm for defining a separating operator that is potent in constructing new local optimal solutions in the search space. Further, the inclusion of belief space aids in maintaining the balance between an optimal exploitation and exploration process with enhanced search capabilities under optimal cluster head selection. This proposed HEHO‐CA‐OCHS scheme improves the characteristic properties of the algorithm by incorporating separating and clan updating operators for effective selection of cluster head with the view to increase the lifetime of the network. The simulation results of the proposed HEHO‐CA‐OCHS scheme were estimated to be superior in percentage of alive nodes by 11.21%, percentage of dead nodes by 13.84%, residual energy by 16.38%, throughput by 13.94%, and network lifetime by 19.42% compared to the benchmarked cluster head selection schemes.

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Performance analysis for lifetime improvement of a regression based clustered network through cluster member allocation and secondary cluster head selection in a distributed WSN

Cited by 8 publications

References 13 publications

Hybrid shuffled frog leaping and improved biogeography‐based optimization algorithm for energy stability and network lifetime maximization in wireless sensor networks

Hybrid shuffled frog leaping and improved biogeography‐based optimization algorithm for energy stability and network lifetime maximization in wireless sensor networks

Lifetime-enhancement Schemes for Power-constrained Routing in Wireless Sensor Networks: A Survey

A hybrid elephant herding optimization and cultural algorithm for energy‐balanced cluster head selection scheme to extend the lifetime in WSNs

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