Continuously maintaining sliding window skylines in a sensor network

52Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Currently, wireless sensor network has been widely used in environment monitoring. The skyline query, as an important operator for multiple criteria decision making and data mining, plays an important role in many sensing applications. Though skyline queries have been well-studied in traditional database system, the existing solutions designed for data stored in a centralized site are not directly applicable to sensor environment due to the unique characteristics of wireless sensor network. In this paper, we propose an energy-efficient algorithm, called Sliding Window Skyline Monitoring Algorithm (SWSMA), to continuously maintain sliding window skylines over a wireless sensor network. Specifically, SWSMA employs two types of filters within each sensor to reduce the amount of data transferred and save the energy consumption as a consequence. In addition to SWSMA, a set of optimization mechanisms are also discussed to improve the performance of SWSMA. Our extensive simulation studies show that SWSMA together with the optimization techniques performs effectively on reducing communication cost and saving the energy on monitoring sliding window skylines. © Springer-Verlag Berlin Heidelberg 2007.

Cite

CITATION STYLE

APA

Xin, J., Wang, G., Chen, L., Zhang, X., & Wang, Z. (2007). Continuously maintaining sliding window skylines in a sensor network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4443 LNCS, pp. 509–521). Springer Verlag. https://doi.org/10.1007/978-3-540-71703-4_44

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free