Efficient Multidimensional Top-k Query Processing in Wireless Multihop Networks

• Main Authors: Daichi Amagata, Yuya Sasaki, Takahiro Hara, Shojiro Nishio
• Format: Article
• Language: English
• Published: Hindawi Limited 2015-01-01
• Series: Mobile Information Systems
• Online Access: http://dx.doi.org/10.1155/2015/657431

Top-k queries, which retrieve the k most preferable data objects, have been receiving much attention. An emerging challenge is to support efficient top-k query processing in a wireless distributed network. In this study, we investigated how to process multidimensional top-k queries efficiently in a wireless multihop network. A major challenge for multidimensional top-k 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-k queries with their own unique preferences. Therefore, we address the above problem and propose a top-k query processing method in wireless multihop networks, called ClusTo. ClusTo performs a novel clustering scheme for multidimensional top-k 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-k data retrieval. Extensive experiments on both real and synthetic data have demonstrated that ClusTo outperforms existing methods in terms of traffic and delay.