Deepanshu

Work place: Department of Computer Science, P.K. University, Shivpuri, 473665, India

E-mail: deepanshu.sharma1991@gmail.com

Website:

Research Interests:

Biography

Deepanshu did his B.Tech. in year-2012 and M.Tech. in year – 2018. He is working in industry for more than 7 years. He has published various research papers and presently pursuing Ph.D in Computer Science.

Author Articles
An Energy Efficient Optimal Path Routing (EEOPR) for Void Avoidance in Underwater Acoustic Sensor Networks

By Deepanshu B. Singh Bhumika Gupta

DOI: https://doi.org/10.5815/ijcnis.2022.03.02, Pub. Date: 8 Jun. 2022

UASN (Underwater Acoustic Sensor Network) has intrinsic impediments, since it is utilized and utilizes acoustic signs to impart in the sea-going world. Examples include long delays in propagation, limited bandwidth, high transmitting energy costs, very high attenuation in the signal, expensive implementation and battery replacement etc. The UASN routing schemes must therefore take account of these features to achieve balance energy, prevent void hole and boost network life. One of the significant issue in routing is the presence of void node. A void node is a node that does not have any forwarder node. The presence of void may cause the bundle conveyance in the steering time which prompts information misfortune. The gap during steering influences the network execution regarding proliferation delay, vitality utilization and network lifetime, and so forth. So with the objective to remove the void node in the networks, this work presents an energy efficient optimal path routing for void avoidance in underwater acoustic sensor networks. This work uses the concept of gray wolf optimization algorithm to calculate the fitness function and that fitness function is used to select the best forwarder node in the networks. This work only consider the vertical directions which further reduces the end to end delay. The proposed work has been simulated on MATLAB and performances are evaluated in terms of broadcast copies of data, energy tax, and packet delivery ratio, number of dead nodes, network lifetime and delay.

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