Adaptive aggregation tree transformation for energy-efficient query processing in sensor networks Online publication date: Sat, 29-Aug-2009
by Mu-Huan Chiang, Gregory T. Byrd
International Journal of Sensor Networks (IJSNET), Vol. 6, No. 1, 2009
Abstract: Data aggregation reduces energy consumption by reducing the number of message transmissions in sensor networks. Effective aggregation requires that event messages be routed along common paths. While existing routing protocols provide many ways to construct the aggregation tree, this opportunistic style of aggregation is usually not optimal. The Minimal Steiner Tree (MST) maximises the possible degree of aggregation, but finding such a tree requires global knowledge of the network, which is not practical in sensor networks. In this paper, we propose the Adaptive Aggregation Tree (AAT) to dynamically transform the structure of the routing tree to improve the efficiency of data aggregation. It adapts to changes in the set of source nodes automatically, and approaches the cost savings of MST without explicit maintenance of an infrastructure. The evaluation results show that AAT reduces the communication energy consumption by 23%, compared to shortest-path tree, and by 31%, compared to GPSR.
Online publication date: Sat, 29-Aug-2009
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Sensor Networks (IJSNET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com