The Open UniversitySkip to content
 

Distributed and Load-Adaptive Self Configuration in Sensor Networks

Iqbal, Mudasser M.; Gondal, Iqbal and Dooley, Laurence S. (2005). Distributed and Load-Adaptive Self Configuration in Sensor Networks. In: 11th Asia-Pacific Conference on Communications (APCC '05), 3-5 October 2005, Perth, Western Australia.

Full text available as:
[img]
Preview
PDF (Not Set) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (391Kb)
URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumb...
Google Scholar: Look up in Google Scholar

Abstract

Proactive self-configuration is crucial for MANETs such as sensor networks, as these are often deployed in hostile environments and are ad hoc in nature. The dynamic architecture of the network is monitored by exchanging so-called Network State Beacons (NSBs) between key network nodes. The Beacon Exchange rate and the network state define both the time and nature of a proactive action to combat network performance degradation at a time of crisis. It is thus essential to optimize these parameters for the dynamic load profile of the network. This paper presents a novel distributed adaptive optimization Beacon Exchange selection model which considers distributed network load for energy efficient monitoring and proactive reconfiguration of the network. The results show an improvement of 70% in throughput, while maintaining a guaranteed quality-of- service for a small control-traffic overhead.

Item Type: Conference Item
Extra Information: ISBN: 0-7803-9132-2
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 12495
Depositing User: Laurence Dooley
Date Deposited: 02 Dec 2008 06:58
Last Modified: 04 Oct 2016 18:16
URI: http://oro.open.ac.uk/id/eprint/12495
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

▼ Automated document suggestions from open access sources

Actions (login may be required)

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk