Efficient Pr-Skyline Query Processing and Optimization in Wireless Sensor Networks

Abstract

As one of the commonly used queries in modern databases, skyline query has received extensive attention from database research community. The uncertainty of the data in wireless sensor networks makes the corresponding skyline uncertain and not unique. This paper investigates the Pr-Skyline problem, i.e., how to compute the skyline with the highest existence probability in a computational and energy-efficient way. We formulate the problem and prove that it is NP-Complete and cannot be approximated in a given expression. However, the proposed algorithm SKY-SEARCH with pruning techniques can guarantee the computational efficiency given relatively large input size, while the filter-based distributed optimization strategy significantly reduces the transmission cost and the required storage space of the sensor nodes. Extensive experiments verify the efficiency and scalability of SKY-SEARCH and the distributed optimizing strategy.

Based on Energy-Efficient Opportunistic Multicast Routing for Mobile Wireless Sensor Networks

“…Wireless sensor networks [1] is composed of many small, self-configuring intelligence sensor nodes, where the nodes limited by the energy, computational, storage capacity and by selforganized manner, in order to perceive the target object or the environment to form a wireless network. Wireless sensor network systems typically include sensor nodes and aggregation nodes [2]. Sensors are used increasingly in real life, such as: disaster monitoring and forecasting of natural disasters, military exercises and operations, medical systems [3], their self-organizing wireless network has gradually become the focus of attention.…”