EURASIP Journal on Advances in Signal Processing
Volume 2007 (2007), Article ID 36871, 13 pages
doi:10.1155/2007/36871
Research Article
Mobile Agent-Based Directed Diffusion in Wireless Sensor Networks
1Department of Electrical and Computer Engineering, University of British Columbia, Vancouver V6T 1Z4, BC, Canada
2School of Computer Science and Engineering, Seoul National University, Seoul 151-744, South Korea
3Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Received 29 November 2005; Revised 12 May 2006; Accepted 16 July 2006
Academic Editor: Deepa Kundur
Copyright © 2007 Min Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In the environments where the source nodes are close to one another
and generate a lot of sensory data traffic with redundancy,
transmitting all sensory data by individual nodes not only wastes
the scarce wireless bandwidth, but also consumes a lot of battery
energy. Instead of each source node sending sensory data to its
sink for aggregation (the so-called client/server computing), Qi et
al. in 2003 proposed a mobile agent (MA)-based distributed sensor
network (MADSN) for collaborative signal and information processing,
which considerably reduces the sensory data traffic and query
latency as well. However, MADSN is based on the assumption that the
operation of mobile agent is only carried out within one hop in a
clustering-based architecture. This paper considers MA in multihop
environments and adopts directed diffusion (DD) to dispatch MA. The
gradient in DD gives a hint to efficiently forward the MA among
target sensors. The mobile agent paradigm in combination with the DD
framework is dubbed mobile agent-based directed diffusion (MADD).
With appropriate parameters set, extensive simulation shows that
MADD exhibits better performance than original DD (in the client/server paradigm)
in terms of packet delivery ratio, energy
consumption, and end-to-end delivery latency.