Towards Evolutionary-Pricing Framework for Mobile Sensor Network Self-organization
Vladimir V. Marbukh, Kamran Sayrafian, Hamid Mahboubi, Ahmadreza Momeni, Amir G. Aghdam
This paper reports on work in progress on developing a unified co-evolutionary/pricing framework for Mobile Sensor Networks (MSN) self-organization. MSN self-organization involves cooperative sensor positioning and formation of a multi-hop Mobile Ad-hoc NETwork (MANET) enabling sensor information acquisition and communication while prolonging MSN life-span. A number of inherent MSN traits such as lack of centralized control and variety of performance criteria suggest framing MSN self-organization as a sensor co-evolutionary optimization. The first issue to be addressed is aligning individual sensor utility/fitness landscapes with the overall MSN goals as selfish sensor behavior may result in suboptimal overall MSN performance. The paper proposes using socially optimal pricing to internalize the effect of each sensor relocation on the overall MSN performance. It is assumed that intermediate nodes in the MSN relay sensor information to a single fusion point without processing. The proposed framework is illustrated for the special case of a MSN tracking a single target.
2010 IEEE World Congress on Computational Intelligence