A K Giri

Work place: Jawaharlal Nehru University, SC&SS, New Delhi, 110067, India

E-mail: akgjnu0810@gmail.com

Website:

Research Interests: Computer Networks, Network Architecture, Network Security

Biography

A K GIRI is a research scholar in school of computer and system sciences, Jawaharlal Nehru University New Delhi 110067 and is working as an Assistant Professor in IT Department of Krishna Institute of Engineering & Technology, Ghaziabad (UP) 201206. He has received his B. Tech degree in Information Technology from Uttar Pradesh

Technical University in year 2005 and M. Tech degree in Computer Science from Jawaharlal Nehru University in year 2010. His current research area is Optimization of Routing protocols in Vehicular Ad-hoc Network.

Author Articles
Optimization of Value of Parameters in Ad-hoc on Demand Multipath Distance Vector Routing Using Magnetic Optimization Algorithm

By A K Giri D K Dobiyal C.P. Katti

DOI: https://doi.org/10.5815/ijcnis.2015.12.03, Pub. Date: 8 Nov. 2015

Vehicular Ad-hoc Networks is one of the emerging research areas of Mobile ad- hoc network. One of the key problems of VANET is changing topology of vehicles which leads to frequent disconnections. Therefore, for communication among the running vehicles, routing of the message becomes a challenging problem. Although, many routing protocols have been proposed in the literatures, but the performance of these protocols, in different scenarios, depends on the value of parameters used in. The objective of our work is to find best fitness function value for Ad-hoc on demand multipath distance vector routing protocol, in real scenario map by obtaining an optimal value of parameters using Magnetic Optimization Algorithm. Therefore, in this paper, we have proposed an algorithm based on Magnetic Optimization Algorithm which finds the optimal value of parameters for Ad-hoc on demand multipath distance vector routing protocol in a given scenario. The fitness function guides Magnetic Optimization Algorithm to achieve the best fitness value. The experimental results, using the optimal value of parameters obtained by Magnetic Optimization Algorithm, show 81.41% drop in average end-to-end delay, 39.24 % drop in Normalized Routing Loads, and slight rise (0.77%) in the packet delivery ratio as compared to using default value of parameters in Ad-hoc on demand multipath distance vector routing protocol.

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