Routing in Wireless Mesh Networks: Three New Nature Inspired Approaches
Multi radio, multi hop, self organizing and self configuring wireless technology are the characteristic features of wireless mesh networks (WMNs) to offer last mile access to end users. The emergence of stochastically varying network environments critically affects routing in WMNs. Any routing policy meant for WMNs must be quickly adaptive and evolve in a decentralized self organizing and self configuring manner. This paper firstly proposes formulation of a soft computing i.e. fuzzy logic based hybrid performance metric which includes per flow (throughput, delay and jitter) as well as per node (residual energy of the node) parameters. This fuzzy logic based hybrid performance metric enumerates the integrated link cost (ILC) which is used as distance measure between two adjacent nodes. The paper further proposes three routing algorithms based upon nature inspired computing approaches namely firefly algorithm, Big Bang Big Crunch and Ant Colony Optimization. The proposed routing approaches aim at finding the minimal ILC path within a stipulated time constraint. The time constraint is governed by the mobility of network nodes. Extensive simulations were conducted for various WMN topologies. The results of the proposed approaches have been compared with two commonly used conventional approaches and were found to be far more superior. It was also observed that the self organizing capability of the proposed nature inspired routing approaches effectively reduces the complexity and makes a network quite adaptive to the dynamic network behavior found in WMNs.
wireless mesh network nature inspired computing firefly algorithm big bang big crunch ant colony optimization