Skyline cube computation over wireless sensor networks

Recently, wireless sensor network has been widely used in many sensing applications. In these applications, skyline cube, as an important operator for data analysis, plays a more and more important role. Though skyline cube computation has been well studied in traditional database literature, the existing approaches are not directly applicable to sensor environment due to the traits of wireless sensor network. In this paper, we propose two approaches, One-Phase Algorithm (OPA) and Two-Phase Algorithm (TPA), to evaluate the skyline cube query energy-efficiently over wireless sensor networks. OPA gathers the useful data based on relaxing the dominant relationship to strict dominant relationship. While TPA utilize the full-space skyline to refine the skyline cube based on the novel property of subspace skyline. Both of them aim at reducing the unnecessary result transmission. Our experimental study shows that our proposed approaches perform energy-effectively on evaluating the skyline cube query over wireless sensor networks.