Volume 50, Number 4-5, October-December 2016
Special issue - Advanced Optimization Approaches and Modern OR-Applications
|Page(s)||797 - 807|
|Published online||03 November 2016|
Two stage decision making approach for Sensor Mission Assignment Problem
1 Assistant Professor, Department of Mathematics, Velalar
College of Engineering and Technology, Erode 638012, Tamil Nadu, India.
2 Director, SSM College of Engineering, Komarapalayam, Namakkal 638183, Tamil Nadu, India.
Accepted: 26 July 2016
Sensor Mission Assignment (SMA) is the process of assigning sensors to missions in the best way, which may depend on the cost of using individual sensors and the requirements of individual missions. SMA is Np-complete and is a special case of Generalized Assignment Problem. The significant bottlenecks in SMA are energy conservation and uncertainty in the demand of the missions. In order to conserve energy, some sensors are considered to be in sleeping state while others remain active for sensing. In this paper, Sensor Mission Assignment problem is studied in the context of Generalized Assignment Problem combined with decision making approach. Two stage decision making approach is formulated to determine the minimum number of sleeping sensors to be activated so as to assign exactly one sensor to each mission optimally subject to some of the energy resource constraints and environmental constraints imposed on it. The method draws upon the existing generalized assignment problem and the decision making approaches by analyzing trade-offs among desirable value of objective function and the constraints that include all the parameters. The proposed method is applied to the simulation on a small sized wireless sensor network and it is shown that the method is energy efficient. The proposed method provides more holistic point of view on the factors impacting sensor mission assignment.
Mathematics Subject Classification: 90B50
Key words: Sensor Mission Assignment / Generalized Assignment Problem / decision making
© EDP Sciences, ROADEF, SMAI 2016
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