Balanced and Safe Weighted Clustering Algorithm for Mobile Wireless Sensor Networks

Dahane, Amine; Berrached, Nasr-Eddine; Loukil, Abdelhamid

doi:10.1007/978-3-319-19578-0_35

Cited by 12 publications

(4 citation statements)

References 19 publications

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“…The residual energy and throughput of the individual sensor nodes were determined to be higher through an average margin of 21% and 16% compared to the existing cluster approaches. Then, a Balanced and Safe Weighted Algorithm‐based Cluster Head Selection Mechanism (BSWCA‐CHSM) was proposed for improving the limitations of the previous energy efficiency and safe weighted method through the combination of five factors that include mobility, degree of connectivity, sensor node and its collaborating neighbors distance, residual energy, and behavioral metrics 16 . This BSWCA‐CHSM method inherits a principle of heuristics for assigning the weights to the cooperating sensor nodes based on the potential of the nodes acting as the cluster heads.…”

Section: Related Workmentioning

confidence: 99%

Markov Modulated Bernoulli Prediction Process‐based Cluster Head Selection Mechanism for improving resilience in wireless sensor networks

Arulmurugan

Amuthan

2021

Int J Communication

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Summary The clustering process in wireless sensor networks is considered to be predominant for facilitating minimized energy consumptions through the selection of potential cluster heads that are efficient in energy and trust. The significant cluster head selection is deterministic in topology control with the view to manage the sensor member nodes of the cluster with the view to enhance energy efficiency in the network. In this paper, a Markov Modulated Bernoulli Prediction Process‐based Cluster Head Selection Mechanism (MMBPP‐CHSM) is proposed by modeling the success probability of sensor nodes' state into a Bernoulli process that dynamically evolves over time based on Markov chain for extending the lifetime of the network. This proposed MMBPP‐CHSM scheme is vital in quantifying the reliability and availability of the sensor nodes in a dynamically evolving wireless sensor network through the estimation of trust and energy in order to facilitate effective cluster head selection. The simulation results of the proposed MMBPP‐CHSM scheme confirmed a superior enhancement in percentage of alive nodes and death nodes in the network to a maximum level of 28% and 23% on par with the baseline cluster head selection approaches used for investigation.

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Section: Related Workmentioning

confidence: 99%

Markov Modulated Bernoulli Prediction Process‐based Cluster Head Selection Mechanism for improving resilience in wireless sensor networks

Arulmurugan

Amuthan

2021

Int J Communication

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“…For comparison purpose in Fig. 6, the performance of WOATCA has been compared with existing schemes such as Topology Control Algorithm for node mobility (TCM) [28], TCM [29], and secure CH selection [30] in terms of the number of dead nodes per round.…”

Section: Evaluation Of Proposed Schemementioning

confidence: 99%

“…7 shows the statistics of the number of alive or surviving nodes per round for the proposed approach. For WOATCA, the number of nodes alive per round is comparatively more than Adoptive LEACH Mobile (ALM) [28], TCM [29], and secure CH selection [30] as shown in Fig. 7.…”

Section: Evaluation Of Proposed Schemementioning

confidence: 99%

WOATCA: A secure and energy aware scheme based on whale optimisation in clustered wireless sensor networks

2020

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“…Dahane et al [17] presented an algorithm shortly called TCM, which is completely decentralized and goes for making a virtual topology with the reason to minimize regular reelection of the CH and evade by and large rebuilding of the whole network. This scheme chooses the most powerful and safe CHs with the obligation of checking the node in their cluster and maintaining clusters locally.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy Efficient Secure Trust Based Clustering Algorithm for Mobile Wireless Sensor Network

Rehman

Sher

Naqvi

et al. 2017

Journal of Computer Networks and Communications

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The main benefit of selecting a suitable node as cluster head (CH) in clustering for wireless mobile sensor networks (MWSNs) is to prolong the network lifetime. But the safe selection of CH is a challenging task by taking security into account. Mostly CH selection algorithms in MWSN do not consider security when selecting CH. We have proposed secure CH selection algorithm by calculating weight of each node to deal with secure selection using minimum energy consumption. The weight of node is a combination of different metrics including trust metric (behaviors of sensor node) which promotes a secure decision of a CH selection; in terms of this, the node will never be a malicious one. The trust metric is definitive and permits the proposed clustering algorithm to keep away from any malignant node in the area to select a CH, even if the rest of the parameters are in its favor. Other metrics of node include waiting time, connectivity degree, and distance among nodes. The selection of CHs is completed utilizing weights of member nodes. The preparatory outcomes acquired through simulation exhibit the adequacy of our proposed scheme as far as average rate of avoiding malicious node as a CH, energy efficiency, and some other performance parameters are concerned.

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Balanced and Safe Weighted Clustering Algorithm for Mobile Wireless Sensor Networks

Cited by 12 publications

References 19 publications

Markov Modulated Bernoulli Prediction Process‐based Cluster Head Selection Mechanism for improving resilience in wireless sensor networks

Markov Modulated Bernoulli Prediction Process‐based Cluster Head Selection Mechanism for improving resilience in wireless sensor networks

WOATCA: A secure and energy aware scheme based on whale optimisation in clustered wireless sensor networks

Energy Efficient Secure Trust Based Clustering Algorithm for Mobile Wireless Sensor Network

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