Dynamic task allocation in multi-hop multimedia wireless sensor networks with low mobility.

Jin, Y, Vural, S, Gluhak, A and Moessner, K (2013) Dynamic task allocation in multi-hop multimedia wireless sensor networks with low mobility. Sensors (Basel), 13 (10). pp. 13998-14028.

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Abstract

This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines.

Item Type:	Article
Divisions :	Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :	Name Email ORCID Jin, Y Vural, S Gluhak, A Moessner, K
Date :	17 October 2013
DOI :	10.3390/s131013998
Copyright Disclaimer :	© 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Related URLs :	Author
Additional Information :	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.
Depositing User :	Symplectic Elements
Date Deposited :	22 Aug 2014 10:57
Last Modified :	31 Oct 2017 16:51
URI:	http://epubs.surrey.ac.uk/id/eprint/805836

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