QoS enhanced energy efficient cluster based routing protocol realized using stochastic modeling to increase lifetime of green wireless sensor network

Banerjee, Ishita; Madhumathy, P.

doi:10.1007/s11276-022-03124-4

Cited by 9 publications

(1 citation statement)

References 24 publications

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“…Although gathering environmental data is the main objective of clustering, wireless nodes are more effective at gathering this data owing to resource limitations. Metaheuristic algorithms have local optima that may be resolved utilizing hybrid methods connected to cluster head (CH) selection [5].…”

Section: Introductionmentioning

confidence: 99%

Penguin search with Harris-Hawk optimization algorithm to improve clustering performance in wireless network

Sabapathy Ranganathan,

Sampathrajan

2024

IJEECS

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<span>Integrating optimal search algorithm concepts across the wireless core and cluster structure enables next-generation wireless networks to effectively provide reliable low-delay communications and connectivity for internet of things (IoT) devices. This article describes penguin search with the Harris-Hawk optimization algorithm (PHHO) to improve clustering performance in wireless networks. The penguin search optimization algorithm (PSO) algorithm computes the fitness value for feature selection from the database. Harris-Hawk optimization (HHO) algorithm to reduce the time and energy required for network transmission. This mechanism builds the clusters based on node communication range. The node direction, node mobility, node bandwidth availability, and energy parameters to decide the cluster head (CH) by applying the HHO algorithm. This approach uses a PSO algorithm fitness function to select the feature subset to minimize error and overhead in the network. Using a network simulator (NS)-3, this method assesses and chooses the most efficient way for data transmission, and the result is compared to a baseline mechanism.</span>

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Section: Introductionmentioning

confidence: 99%