Incentive-Based Self-Organization for 2 Dimensional Event Tracking

For problems that cannot be modeled and solved efficiently using a centralized approach, distributed algorithms are a necessity. Self-organizing systems are systems constructed from a network of autonomous communicating agents whereby from simple individual behaviors emerges a global system behavior that is complex, efficient, adaptable, and robust. For the right behavior to emerge, the components must have the correct incentives when they select among their next action. In this paper, we explore the problem of self organization in the context of a mobile sensor network tracking an event. We select two different paradigms, a newtonian force-based approach and a potential energy approach. We test the resulting algorithms in a simulation environment.