Development of Energy Efficient and Optimized Coverage Area Network Configuration to Achieve Reliable WSN Network Using Meta-Heuristic Approaches

Author:

Banerjee Avishek1ORCID,Das Victor1,Biswas Arindam2,Chattopadhyay Samiran3,Biswas Utpal4

Affiliation:

1. Asansol Engineering College, Asansol, India

2. Kazi Nazrul University, Asansol, India

3. Jadavpur University, India

4. University of Kalyani, India

Abstract

Energy optimization and coverage area optimization of wireless sensor networks (WSN) are two major challenges to accomplish reliability optimization in the field of WSN. Reliability optimization in the field of WSN is directly connected to the performance and efficiency and consistency of the network. In this paper, the authors describe how these challenges can be resolved by designing an efficient WSN with the help of meta-heuristic algorithms. They have configured an optimized route/path using ant colony optimization (ACO) algorithm and deployed static WSN nodes. After configuring an efficient network, if we can maximize the coverage area, then we can ensure that the network is a reliable network. For coverage area optimization, they used a hybrid differential evolution-quantum behaved particle swarm optimization (DE-QPSO) algorithm. The result has been compared with existing literature, and the authors found good results applying those meta-heuristic and hybrid algorithms.

Publisher

IGI Global

Subject

Decision Sciences (miscellaneous),Computational Mathematics,Computational Theory and Mathematics,Control and Optimization,Computer Science Applications,Modelling and Simulation,Statistics and Probability

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Caddisfalcon optimization algorithm for on-demand energy transfer in wireless rechargeable sensors based IoT networks;Sustainable Energy Technologies and Assessments;2024-04

2. Coverage Area Maximization Using MOFAC-GA-PSO Hybrid Algorithm in Energy Efficient WSN Design;IEEE Access;2023

3. Design of Cost-Effective WSN by Minimizing Energy Consumption Using Hybrid Algorithm;Advances in Data Science and Computing Technologies;2023

4. A Survey on Designing Efficient WSN Using Duty Cycle Optimization;Communications in Computer and Information Science;2023

5. Design of an Efficient WSN with Reducing Energy and Overlapping Coverage Area;2022 International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON);2022-12-23

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