A Biology-Based Algorithm to Minimal Exposure Problem of Wireless Sensor Networks

The Minimal Exposure Problem (MEP), which corresponds to the quality of coverage, is a fundamental problem in wireless sensor networks. This paper exploits a biological model of physarum to design a novel biology-inspired optimization algorithm for MEP. We first formulate MEP and the related models,...

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Bibliographic Details
Published in:IEEE eTransactions on network and service management 2014-09, Vol.11 (3), p.417-430
Main Authors: Yuning Song, Liang Liu, Huadong Ma, Vasilakos, Athanasios V.
Format: Article
Language:English
Subjects:
Algorithms
Approximation algorithms
Approximation methods
Biological
Biological system modeling
Computational modeling
Computer simulation
Exposure
Junctions
Monitoring
Optimization
Remote sensors
Sensors
Wireless networks
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Summary:The Minimal Exposure Problem (MEP), which corresponds to the quality of coverage, is a fundamental problem in wireless sensor networks. This paper exploits a biological model of physarum to design a novel biology-inspired optimization algorithm for MEP. We first formulate MEP and the related models, and then convert MEP into the Steiner problem by discretizing the monitoring field to a large-scale weighted grid. Inspired by the path-finding capability of physarum, we develop a biological optimization solution to find the minimal exposure road-network among multiple points of interest, and present a Physarum Optimization Algorithm (POA). Furthermore, POA can be used for solving the general Steiner problem. Extensive simulations demonstrate that our proposed models and algorithm are effective for finding the road-network with minimal exposure and feasible for the Steiner problem.
ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2014.2346080