To converge more quickly and effectively—Mean field annealing based optimal path selection in WMN

Multi-constrained path selection with optimization aims at finding an optimal path that satisfies a set of QoS parameters, as an NP-hard problem, which is also a big challenge for wireless mesh networks. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem. However, existing methods either have analyses in specific network models or cannot support the change of network topology well. Thus, multi-constrained QoSR in emerging wireless mesh networking is worth investigating further. In this paper, we propose a novel Routing Algorithm based on Mean Field Annealing (MFA_RA) to solve this problem. MFA_RA first uses a function of two QoS parameters, wireless link’s delay and transmission success rate, as the cost function, and then seeks to find a feasible path by mean field annealing. Moreover, a set of deterministic equations are utilized to replace the stochastic process in simulated annealing (SA), and a saddle point approximation is adopted for the calculation of the stationary probability distribution at equilibrium. Extensive simulation results demonstrate that MFA_RA is an effective algorithm and can outperform other heuristic algorithms.