By Topic

An Ant Odor Analysis Approach to the Ant Colony Optimization Algorithm for Data-Aggregation in Wireless 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
$31 $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

3 Author(s)
Vijaykumar, V. ; Dept. of Inf. Technol., Sri Venkateswara Coll. of Eng., Sriperumbudur ; Chandrasekar, R. ; Srinivasan, T.

In this paper we present an ant odor analysis approach to the ant colony optimization (ACO) algorithm for data aggregation in wireless sensor networks. We provide a modification to the existing ACO data aggregation scheme by accounting for multiple sinks and sources in an energy-constrained wireless sensor network. By forming families of ants (FoA), an intrinsic way is provided to explore the search space for routing and for determining optimal data aggregation. An ant odor identification model (AOIM) serves to determine and increase the correlation between data at the various nodes by trying to include hitherto different data under the same family (FoA). Simulation results show that the energy-efficiency achieved is high with less associated costs even for a larger number of sources and sinks

Published in:

Wireless Communications, Networking and Mobile Computing, 2006. WiCOM 2006.International Conference on

Date of Conference:

22-24 Sept. 2006