Hybrid Atom Search-Heap Energy Optimization Algorithm for Dynamic Topology in Underwater Acoustic Sensor Network

Benefits obtained from the water resources are many in terms of renewable energy, food, materials, communication and security. Monitoring, sensing, routing and analysis of underwater happenings is the challenging task in a sparse environment. Due to the dynamic nature of underwater topology, routing among the nodes is a complex task, hence optimal node identification is mandatory for enhancing network performance. The environment and vast area of ocean makes it highly unlikely for humans to explore and monitor as a challenging task and more cost then manual labour. Hence, economical solutions for monitoring and exploration applications in the ocean are possible with Underwater Acoustic Sensor Network (UWASN). This work proposes a meta-heuristic novel hybrid Atom searchHeap optimization (NHASHO) algorithm to enhance the network performance in terms of energy, end-to-end delay and throughput. The NS2 simulation results show that the proposed work outperforms with existing Cat Optimization algorithm (CAO) for dynamically varying underwater topology condition.