A New Version of Energy-Efficient Optimization Protocol Using ICMA-PSOGA Algorithm in Wireless Sensor Network

• Published in: SN computer science Vol. 3; no. 5; p. 353
• Main Authors: Rambabu, Ch, Prasad, V. V. K. D. V., Prasad, K. Satya
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 30.06.2022; Springer Nature B.V
• Subjects: Agents (artificial intelligence); Clustering; Collaboration; Computer Imaging; Computer Science; Computer Systems Organization and Communication Networks; Data Structures and Information Theory; Data transmission; Energy consumption; Energy efficiency; Energy utilization; Genetic algorithms; Information Systems and Communication Service; Methods; Nodes; Optimization algorithms; Original Research; Particle swarm optimization; Pattern Recognition and Graphics; Routing (telecommunications); Sensor Networks; Sensors; Software Engineering/Programming and Operating Systems; Vision; Wireless communications; Wireless sensor networks; Wireless sensor network; Energy consumption; Network lifetime; Intraclustering; Optimization algorithms; Mobile agent; Energy-efficient routing
• ISSN: 2661-8907; 2662-995X; 2661-8907
• DOI: 10.1007/s42979-022-01232-8

In Wireless Sensor Networks (WSNs), the transmission of information through wireless medium is facilitated using nodes which are small and self-organizing and moreover enhances the process. The energy saving and effective utilization of energy are major issues in WSNs. The relationship between the cluster heads and sensor nodes was only considered in previous cluster-based routing protocols by ignoring the cost differences among them. The residual nodes, which are not considered as cluster members, may exist in certain existing clustering protocols. The network lifetime might be reduced by these residual nodes. Clustering is a proven technique for energy optimization. However, most of the clustering algorithms failed to address the routing overhead and the energy consumption rate between the CH nodes and the SINK node. Here, we introduce a new improved energy-efficient intra-cluster routing technique using mobile agents to reduce communication overhead and an optimal positioning strategy of SINK node using PSOGA for energy optimization. A novel framework is proposed in this method, in which an effective clustering mechanism using Intra Mobile Agents (IN-MA) is present. Moreover, on the basis of the network structure, an optimal position is determined for the sink by introducing a Particle Swarm Optimization-Genetic Algorithm (PSO-GA)-based location estimation algorithm. The data are collected from the members and delivered to the CHs using Intra Mobile Agents. The PSO-GA algorithm estimates the optimal position of a sink. Based on the experimental results, the better outcomes are observed using the proposed method when compared to the previous techniques. The parameters like lifetime of a network, consumption of energy, and throughput rate are considered mainly to analyze the efficiency of the proposed energy-efficient strategy.