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Several algorithms have been developed for problems of data aggregation in wireless sensor networks, all of which tried to increase networks lifetime. In this paper, the authors deal with this problem using a more efficient method, and offer a heuristic algorithm based on distributed learning automata to solve data aggregation problems within stochastic graphs. Given that data aggregating through creating backbones and making Connected Dominating Sets (CDS) in networks lowers the ratio of responding hosts to the hosts existing in virtual backbones, they employed this idea to their algorithm, trying to increase networks lifetime considering such parameters as sensors lifetime, remaining and consumption energies in order to have an almost optimal data aggregation within networks.
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