| Popis: |
Wireless Sensor Networks (WSNs) are a multihop self-organizing network that generates wireless communication by using numerous tiny sensor nodes. The energy efficiency of the WSN is a key issue, because of the restricted, irreplaceable, and non-rechargeable energy resources of the sensors. Clustering over sensors is an adequate approach in developing the routing approach for WSN that helps to improve energy efficiency and life expectancy. Therefore, Energy Centric optimization such as Multiobjective Jellyfish Search Optimizer and Multiobjective Ant Colony Optimization (EC-MJSO-MACO) is proposed to enhance the energy efficiency of WSN. The optimal Cluster Heads (CHs) in the network are selected by using EC-MJSO, whereas the path via the CHs is discovered using EC-MACO. The developed EC-MJSO-MACO minimizes the energy expenditure of the nodes while improving the data delivery. The performances of EC-MJSO-MACO are analyzed based on alive & dead nodes, normalized energy, packets to BS, throughput, and life expectancy. The EC-MJSO-MACO is compared with other approaches such as Low Energy Adaptive Clustering Hierarchy (LEACH), Butterfly Optimization Algorithm (BOA) and Grasshopper Optimization Algorithm (GOA), Cuckoo Insisted-Rider Optimization Algorithm (CI-ROA), Rider-Cat Swarm Optimization (RCSO). Alive nodes of the EC-MJSO-MACO for 2000 rounds are 100, which are greater than other methods. |
