Due to dynamic network conditions, routing is the most critical part in WMNsand needs to be optimised. The routing strategies developed for WMNs must beefficient to make it an operationally self configurable network. Thus we needto resort to near shortest path evaluation. This lays down the requirement ofsome soft computing approaches such that a near shortest path is available inan affordable computing time. This paper proposes a Fuzzy Logic basedintegrated cost measure in terms of delay, throughput and jitter. Based uponthis distance (cost) between two adjacent nodes we evaluate minimal shortestpath that updates routing tables. We apply two recent soft computing approachesnamely Big Bang Big Crunch (BB-BC) and Biogeography Based Optimization (BBO)approaches to enumerate shortest or near short paths. BB-BC theory is relatedwith the evolution of the universe whereas BBO is inspired by dynamicalequilibrium in the number of species on an island. Both the algorithms have lowcomputational time and high convergence speed. Simulation results show that theproposed routing algorithms find the optimal shortest path taking into accountthree most important parameters of network dynamics. It has been furtherobserved that for the shortest path problem BB-BC outperforms BBO in terms ofspeed and percent error between the evaluated minimal path and the actualshortest path.
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