A graph based approach to supporting reconfiguration in wireless sensor networks

Horré, W, Lee, K ORCID logoORCID: https://orcid.org/0000-0002-2730-9150, Hughes, D, Michiels, S and Joosen, W, 2009. A graph based approach to supporting reconfiguration in wireless sensor networks. In: Proceedings of the First International Conference on Networks and Communications, NetCoM 2009, Chennai, India, 27-29 December 2009. Los Alamitos, California: IEEE Computer Society, pp. 326-331. ISBN 9780769539249

[thumbnail of 221142_2818.pdf]
Preview
Text
221142_2818.pdf

Download (348kB) | Preview

Abstract

Considerable research has been performed in applying run-time reconfigurable component models to Wireless Sensor Networks. The ability to dynamically deploy or update software components has clear advantages in sensor network deployments, which are typically large in scale and expected to operate for long periods in dynamic environments. Realizing distributed reconfiguration in Wireless Sensor Networks is complicated by the inherently asynchronous and unreliable nature of these systems. In such an environment, achieving quiescence is both costly and impossible to guarantee. Additionally, the success of reconfiguration actions cannot be determined with certainty. This paper advocates for a hierarchical, adaptive, graph-based approach to supporting reconfiguration. We argue that application developers should specify only high level reconfiguration graphs, which are then compiled, partitioned and enacted in an adaptive manner by a context aware distributed reconfiguration engine.

Item Type: Chapter in book
Creators: Horré, W., Lee, K., Hughes, D., Michiels, S. and Joosen, W.
Publisher: IEEE Computer Society
Place of Publication: Los Alamitos, California
Date: 2009
ISBN: 9780769539249
Identifiers:
Number
Type
10.1109/NetCoM.2009.18
DOI
Divisions: Schools > School of Science and Technology
Record created by: EPrints Services
Date Added: 09 Oct 2015 10:53
Last Modified: 09 Jun 2017 13:43
URI: https://irep.ntu.ac.uk/id/eprint/19663

Actions (login required)

Edit View Edit View

Statistics

Views

Views per month over past year

Downloads

Downloads per month over past year