Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 149513, 11 pages
http://dx.doi.org/10.1155/2015/149513
Research Article

Energy-Efficient β-Approximate Skylines Processing in Wireless Sensor Networks

1College of Information Science & Engineering, Northeastern University, Shenyang 110819, China
2Liaoning Key Lab of Big Data Management & Analysis, Northeastern University, Shenyang 110819, China
3Sino-Dutch Biomedical & Information Engineering School, Northeastern University, Shenyang 110819, China
4College of Information Science & Technology, Liaoning University, Shenyang 110036, China

Received 29 November 2014; Accepted 16 February 2015

Academic Editor: Vladimir Turetsky

Copyright © 2015 Junchang Xin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

As the first priority of query processing in wireless sensor networks is to save the limited energy of sensor nodes and in many sensing applications a part of skyline result is enough for the user’s requirement, calculating the exact skyline is not energy-efficient relatively. Therefore, a new approximate skyline query, β-approximate skyline query which is limited by a guaranteed error bound, is proposed in this paper. With an objective to reduce the communication cost in evaluating β-approximate skyline queries, we also propose an energy-efficient processing algorithm using mapping and filtering strategies, named Actual Approximate Skyline (AAS). And more than that, an extended algorithm named Hypothetical Approximate Skyline (HAS) which replaces the real tuples with the hypothetical ones is proposed to further reduce the communication cost. Extensive experiments on synthetic data have demonstrated the efficiency and effectiveness of our proposed approaches with various experimental settings.