By Topic

On Efficient Processing of Continuous Historical Top- k Queries in Sensor Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Jie Cheng ; Department of Electronics and Information Engineering, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China ; Hongbo Jiang ; Jiangchuan Liu ; Wenyu Liu
more authors

The top-k query has long been an important topic in computer science. Efficient implementation of top-k queries is the key for information searching. In this paper, we develop the Efficient algorithm for the Continuous Historical Top-k (ECHT) extraction, which is a novel algorithm that can effectively process the continuous historical top-k query. A simple top-k extraction algorithm based on aggregation is used for user query processing, and two additional steps on the filter setting by which individual nodes do not have to report all their readings are proposed to further reduce communication cost. To the best of our knowledge, this is the first work for continuous historical top-k query processing in sensor networks, and our simulation results show that our schemes can reduce the total communication cost by up to two orders of magnitude, as compared with the centralized scheme or a straightforward extension from the previous top-k algorithm on a continuous monitoring query.

Published in:

IEEE Transactions on Vehicular Technology  (Volume:60 ,  Issue: 5 )