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Delay-tolerant charging scheduling by multiple mobile chargers in wireless sensor network using hybrid GSFO
Ist Teil von
Journal of ambient intelligence and humanized computing, 2023-12, Vol.14 (12), p.16063-16079
Ort / Verlag
Berlin/Heidelberg: Springer Berlin Heidelberg
Erscheinungsjahr
2023
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
In wireless rechargeable sensor networks (WRSNs), wireless energy transfer procedures are provided to refill sensor batteries using chargers. WRSNs provide energy replacement and prolonged network lifetime to the sensors. Instead of charging utility, most of the sensors focused only on the sensing tasks which reduces the optimal result and also, they suffer from non-flexible charging scheduling. So, a hybrid optimization algorithm is proposed to allocate the charging tasks to several chargers to reduce the travelling time and moving distance of mobile chargers (MCs). Initially,
k
-
medoids clustering algorithm is used to group the sensors into equal sized clusters. Then, a Wind Driven Water Wave Optimization algorithm is applied to elect cluster heads based on the distance and residual energy of sensors. Finally, hybrid Galactic Sun Flower Optimization algorithm is utilized to solve charging scheduling problem with MCs. Parameters like packet delivery ratio, packet loss rate, energy consumption, network lifetime, throughput, end-to-end delay, charging latency, and travel distance of MCs are calculated to show the scalability and efficiency of the suggested methodology. The outcomes indicated that the proposed technique minimizes the charging latency by 23.52
%
of hybrid CS-GA, 82.35
%
of GSA, 90.90
%
of NJNP, and 94.73
%
of FCFS based scheme with varying speed of MCs.