Efficient Multidimensional Top- Query Processing in Wireless Multihop Networks

Top- queries, which retrieve the most preferable data objects, have been receiving much attention. An emerging challenge is to support efficient top- query processing in a wireless distributed network. In this study, we investigated how to process multidimensional top- queries efficiently in a wireless multihop network. A major challenge for multidimensional top- queries is that answers for different users are typically different, because each user has a unique preference and search range. Meanwhile, it is desirable for wireless networks to reduce unnecessary traffic even if users issue top- queries with their own unique preferences. Therefore, we address the above problem and propose a top- query processing method in wireless multihop networks, called ClusTo. ClusTo performs a novel clustering scheme for multidimensional top- query processing and routes queries based on the cluster while guaranteeing the user’s specified search range. Moreover, ClusTo takes a dynamic threshold approach to suppress unnecessary query transmissions to nodes which do not contribute to top- data retrieval. Extensive experiments on both real and synthetic data have demonstrated that ClusTo outperforms existing methods in terms of traffic and delay.