Energy-Efficient Skyline Queries over Sensor Network Using Mapped Skyline Filters

Junchang Xin, Guoren Wang, Xiaoyi Zhang

Abstract: In recent years, wireless sensor network has been widely used in military and civil applications. For many wireless sensor applications, the skyline query is a very important operator for retrieving data according to multiple criteria. In traditional database system skyline queries have been well studied, but in sensor environment the existing solutions are not suitable, because of the essential characteristics of wireless sensor network, such as wireless, multi-hop communication, resource-constrained and distributed environment. An Energy-Efficient Sliding Window Skyline Maintaining Algorithm (EES), which continuously maintains sliding window skylines over a wireless sensor network, is proposed in this paper. In particular, we propose a mapped skyline filter (MSF) in EES. MSF resides in each sensor node and filters the tuples having no contribution to the final result, therefore energy consumption is saved significantly. Our extensive performance studies show that EES can effectively reduce communication cost and save the energy on maintaining sliding window skylines over wireless sensor network.