Optimizing Multiple Data Acquisition Queries in Sparse Mobile Sensor Networks

In mobile sensor networks (MSNs), it is common for the base station to issue {\em data acquisition} queries requesting for data to be sensed from specific regions of the data space. Such kind of queries are especially important in MSNs for reconnaissance and disaster rescue applications. In this paper, we investigate how multiple data acquisition queries can be answered quickly in sparse mobile sensor networks. Because of the sparseness and mobility, the number of sensors is limited, the connection is intermittent and the topology is unpredictable. To effectively handle the above challenges, we design distributed schemes where mobile sensors strategically relocate themselves to proper locations to collaboratively facilitate efficient query processing and enable sharing over space and time. We first propose a novel scheme, {\em Dynamic}, that enables queries to share resources at runtime while sensors are greedily relocated to benefit the processing of each query. We also design another scheme, {\em aMST}, that optimizes a batch of queries as a whole and utilizes a Minimum Steiner Tree to guide the execution of all queries in the batch. In addition, a parameter is defined to guide the selection of the most appropriate scheme to adapt to the environment. Our extensive performance study shows the effectiveness of our proposed schemes.