Adaptive Node Clustering Technique for Smart Ocean Under Water Sensor Network (SOSNET)

Sensors

Yunyoung Nam¹  Mehr Yahya Durrani²  Muazzam Maqsood²  Farhan Aadil²  Rehan Tariq²  Khan Muhammad³ 

[1] Department of Computer Science and Engineering, Soonchunhyang University, Asan 31538, Korea;Department of Computer Science, COMSATS University Islamabad, Attock Campus, Attock 43600, Pakistan;Department of Software, Sejong University, Seoul 143-747, Korea;

关键词: smart ocean;    underwater communication and networks;    routing;    clustering;    optimization;    moth flame optimizer;    transmission range optimization;   

DOI  :  10.3390/s19051145

来源: DOAJ

【 摘 要 】

Abstract: Smart ocean is a term broadly used for monitoring the ocean surface, sea habitat monitoring, and mineral exploration to name a few. Development of an efficient routing protocol for smart oceans is a non-trivial task because of various challenges, such as presence of tidal waves, multiple sources of noise, high propagation delay, and low bandwidth. In this paper, we have proposed a routing protocol named adaptive node clustering technique for smart ocean underwater sensor network (SOSNET). SOSNET employs a moth flame optimizer (MFO) based technique for selecting a near optimal number of clusters required for routing. MFO is a bio inspired optimization technique, which takes into account the movement of moths towards light. The SOSNET algorithm is compared with other bio inspired algorithms such as comprehensive learning particle swarm optimization (CLPSO), ant colony optimization (ACO), and gray wolf optimization (GWO). All these algorithms are used for routing optimization. The performance metrics used for this comparison are transmission range of nodes, node density, and grid size. These parameters are varied during the simulation, and the results indicate that SOSNET performed better than other algorithms.

【 授权许可】

Unknown