By Topic

A lightweight classification algorithm for energy conservation 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
$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

2 Author(s)
N. Tezcan ; Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA ; W. Wang

Classification of sensor nodes can be used as a technique for conserving energy and prolonging the lifetime of a wireless sensor network (WSN). In this paper, we present a new algorithm of lightweight and dynamic classification. By this algorithm, energy consumption is reduced while providing a full coverage, which is an important network parameter in WSNs. Moreover, node classification is adaptive to topology changes and has no constraint on routing protocols and hardware. Based on sensors residual energy, they are classified as essential and non-essential and rotated dynamically. Essential nodes send their measurements to the sink, whereas, non-essential ones do not send new data and receive queries from the sink. This reduces transmitting and receiving energy of non-essential nodes and regulates data traffic. Further, our mechanism may provide location-based tunable redundancy, e.g., if redundant data is needed from a specific region, the sink may query the corresponding essential nodes to activate non-essential ones in that region. We analyze the complexity and energy consumption for the scenario where nodes are randomly deployed in a given region. Analysis, supported by extensive simulation in ns2, shows that energy consumption due to communications can be reduced in proportional to the ratio of essential nodes and fairly distributed among sensors by rotation.

Published in:

Proceedings. 14th International Conference on Computer Communications and Networks, 2005. ICCCN 2005.

Date of Conference:

17-19 Oct. 2005