Title
Dynamic task allocation in multi-hop multimedia wireless sensor networks with low mobility.
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.
Year
DOI
Venue
2013
10.3390/s131013998
SENSORS
Keywords
Field
DocType
multi-hop multimedia wireless sensor network,task allocation,low mobility,genetic algorithm
Network service,Key distribution in wireless sensor networks,Heuristic,Wireless,Computer science,Real-time computing,Shared resource,Multimedia,Wireless sensor network,Genetic algorithm,Performance improvement,Distributed computing
Journal
Volume
Issue
ISSN
13
10.0
1424-8220
Citations 
PageRank 
References 
5
0.44
26
Authors
4
Name
Order
Citations
PageRank
Yichao Jin151.12
Serdar Vural2312.01
A. Gluhak31537.94
K. Moessner414423.09