D K Dobiyal

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

E-mail: lobiyal@gmail.com

Website:

Research Interests: Bioinformatics, Computer systems and computational processes, Natural Language Processing, Computer Networks, Data Structures and Algorithms

Biography

D K Lobiyal is a Professor in school of computer and system sciences, Jawaharlal Nehru University New Delhi 110067. He has received Ph.D. and M. Tech degree in computer science and technology from Jawaharlal Nehru University New Delhi in year 1996 and 1991 respectively. He has received B. Tech degree in computer science and technology from Institute of Engineering and Technology, Lucknow University, in year 1988. His present research area is Vehicular Ad-hoc network, Natural language processing, Video on demand and Wireless Sensor Network. His field of teaching is mobile ad-hoc network, Data communications and computer networks.

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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