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A parallel and adaptative query routing scheme for wireless sensor networks

The use of wireless sensor networks for information discovery and monitoring of continuous physical fields has emerged as a novel and efficient solution. To this end, a sink node disseminates a query message through the network to fetch data from sensor nodes. As several applications only require a limited subset of the available data in the network, the query could be ideally routed to obtain only relevant information, hence minimizing energy consumption. In this work, we apply computational intelligence algorithms to adapt the query process to the characteristics of the network in order to direct queries to relevant nodes, thus, limiting the routing space. This proposal is validated by extensive simulations which show that the routing cost can be reduced by approximately 60% over flooding with an error less than 5%.