By Topic

Self-Organization of Sensor Networks Using Genetic Algorithms

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)
Khanna, R. ; Intel Corporation, 2111 NE 25th Ave., Hillsboro, OR 97124, USA. E-mail: rahul.khanna@intel. com ; Huaping Liu ; Hsiao-Hwa Chen

In this paper we propose a reduced-complexity genetic algorithm for optimization of multi-hop sensor networks. The goal of the system is to generate optimal number of sensor-clusters with cluster-heads. It results in minimization of the power-consumption of the sensor-system while maximizing the sensor objectives (coverage and exposure). The genetic algorithm is used to adaptively create various components such as cluster-members, cluster-heads, and next-cluster. These components are then used to evaluate the average fitness of the system based on the sequence of communication links towards the sink.

Published in:

Communications, 2006. ICC '06. IEEE International Conference on  (Volume:8 )

Date of Conference:

June 2006