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With data correlation considered, this paper formulates the route computation problem in terms of maximizing an objective function, which is directly proportional to the received signal strength and inversely proportional to the path loss. Further, we propose an improved ant colony algorithm to compute a suboptimal solution of the NP-hard problem by adjusting local pheromone decay parameter p and pheromone quantity parameter Q adoptively. The simulation results demonstrate the superior performance both in solution quality and convergence speed of our algorithm over other two heuristics, i.e., local closest first and ant-cycle system.
Date of Conference: 12-15 May 2008