A route restoration algorithm based on the ant colony optimization(RRACO)is presented to find an energy-efficient route in dynamic sensor networks. A novel probabilistic model is constructed to find an energy-efficient route from the source node to the sink node. Both the overhead and the residual energy of nodes on routes are taken into account in the selection of the route. A new re-initialization rule for local pheromone is also presented to adapt the dynamic change of sensor networks. The rule reinitializes the local pheromone in the area where a nodes failure occurs. Most of the information for the original optimization route can be reserved and the local area can be searched. Hence the optimization route can be restored quickly. Simulation results show that the proposed method generates a route with the least overhead and the largest residual energy of the nodes
and that a new optimization route can be found very quickly when some nodes fail.
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references
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