An Efficient Mobile Data Collector Based Data Aggregation Scheme for Wireless Sensor Networks

Recently, mobile collector or sink mobility has become an important research topic in WSNs. Data collector mobility can improve the performance of WSNs. Mobile sinks are mounted on some vehicles, animals or people moving randomly to collect information sensed by the sensor nodes where the data sink trajectories are changing or random. In the scenarios where the trajectories of the mobile collectors are fixed or predetermined, the efficient data collection problems are concerned to improve the performance of the network. Therefore, in this paper we propose an intelligent mobile data gathering scheme which dynamically changes its DGT (Data Gathering Tour) in between by utilizing information from NIT (Neighbor Information Table). Each CH (Cluster Head) learns about its neighbors whether they have data to send or not and thus creates a NIT. Based on the information in NIT at a CH, MDC (Mobile data Collector) decides its further course of action. Hence, the path travelled is dynamically pruned using this information at each cluster head. Simulation results show significant energy savings when this scheme is applied to various data collection scenarios in which different CHs are deployed as opposed to scenarios when no dynamic path pruning and data filtering is used.