Sharad Sharma

Work place: Deptt. of Electronics and Communication Engineering, National Institute of Technology, Kurukshetra, India



Research Interests: Computer Networks, Data Structures and Algorithms, Combinatorial Optimization


Sharad Sharma, received his B.Tech in Electronics Engineering from Nagpur University, Nagpur, India in 1998 and M.Tech in Electronics and Communication Engineering from Thapar Institute of Engineering and Technology, Patiala, India in 2004. He has conducted many workshops on Soft Computing and its applications in engineering, Wireless Networks, Simulators etc. He has opened up a student chapter of IEEE as Branch Counselor. Presently, he is working towards the Ph.D. degree in Electronics and Communication Engineering from National Institute of Technology, Kurukshetra, India. His research interests are routing protocol design, performance evaluation and optimization for wireless mesh networks using nature inspired computing.

Author Articles
Hybrid Intelligent Routing in Wireless Mesh Networks: Soft Computing Based Approaches

By Sharad Sharma Shakti Kumar Brahmjit Singh

DOI:, Pub. Date: 8 Dec. 2013

Wireless Mesh Networks (WMNs) are the evolutionary self-organizing multi-hop wireless networks to promise last mile access. Due to the emergence of stochastically varying network environments, routing in WMNs is critically affected. In this paper, we first propose a fuzzy logic based hybrid performance metric comprising of link and node parameters. This Integrated Link Cost (ILC) is computed for each link based upon throughput, delay, jitter of the link and residual energy of the node and is used to compute shortest path between a given source-terminal node pair. Further to address the optimal routing path selection, two soft computing based approaches are proposed and analyzed along with a conventional approach. Extensive simulations are performed for various architectures of WMNs with varying network conditions. It was observed that the proposed approaches are far superior in dealing with dynamic nature of WMNs as compared to Adhoc On-demand Distance Vector (AODV) algorithm.

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