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Anycast is a mechanism that it sends the data groups to the nearest interface during which they have the same anycast address. Ant colony system, a population-based algorithm, provides natural and intrinsic way of exploration of search space in optimization settings in determining optimal anycast tree. In this paper, the authors propose a sink selection heuristic algorithm called Minimum Ant-based Data Fusion Tree (MADFT) for energy constraint wireless sensor networks. Different from existing schemes, MADFT not only optimizes over the data transmission cost, but also incorporates the cost for data fusion which can be significant for emerging sensor networks with vectorial data and/or security requirements. Via simulation, it is shown that this algorithm has excellent performance behavior and provides a near-optimal solution.
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