A New Crossover Methods and Fitness Scaling for Reducing Energy Consumption of Wireless Sensor Networks

Alsharafat, Wafa; Al-Shdaifat, Alaa; Batiha, Khaled; Alsukker, Akram

doi:10.1109/access.2022.3203696

Cited by 3 publications

(1 citation statement)

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“…Compared to LEACH, on average, the overall survival rate of the working nodes in the network increased by more than 30%. A central cluster algorithm based on an improved genetic algorithm (EGA) that finds appropriate numbers of CHs in networks is proposed [34]. It outperforms LEACH in a longer network lifetime measured in terms of the first node dying, half of the nodes dying, and the last node dying but does not consider residual energy while selecting CHs.…”

Section: Background Studiesmentioning

confidence: 99%

Efficient Clustering Based Routing for Energy Management in Wireless Sensor Network-Assisted Internet of Things

et al. 2022

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Wireless sensor networks (WSNs) play a huge part in arising innovations like smart applications, the Internet of Things, and numerous self-designed, independent applications. Energy exhaustion and efficient energy consumption are principal issues in wireless sensor networks. Energy is a significant and valuable asset of sensor nodes; early energy depletion ultimately leads to a shorter network lifetime and the replacement of sensor nodes. This research proposes a novel Power-Efficient Cluster-based Routing (PECR) algorithm. It takes in clustering using K-Means, the arrangement of Cluster Heads (CHs) and a Main Cluster Head (MCH), the optimal route choice, communication in light of the energy utilization model, cluster heads, and main cluster head alternation based on residual energy and relative location. PECR decreases traffic overburden, restricts energy usage, and at last, expands the network lifetime. Sensor nodes sense the information and transmit traffic to a Base Station (BS) through a legitimate channel. The results confirm it decreases the traffic overhead and effectively utilizes the energy assets. The simulation results show that PECR’s performance is 44% more improved than LEACH, EC, EECRP, and EECA algorithms. It is suitable for networks that require a stretched life.

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Section: Background Studiesmentioning

confidence: 99%