Self-Organization through Bottom-up Coalition Formation

We present a distributed approach to self-organization in a distributed sensor network. The agents in the system use a series of negotiations incrementally to form appropriate coalitions of sensor and processing resources. Since the system is cooperative, we have developed a range of protocols that allow the agents to share meta-level information before they allocate resources. On one extreme the protocols are based on local utility computations, where each agent negotiates based on its local perspective. From there, a continuum of additional protocols exists in which agents base decisions on marginal social utility, the combination of an agent's marginal utility and that of others. We present a formal framework that allows us to quantify how social an agent can be in terms of the set of agents that are considered and how the choice of a certain level affects the decisions made by the agents and the global utility of the organization. Our results show that by implementing social agents, we obtain an organization with a high global utility both when agents negotiate over complex contracts and when they negotiate over simple ones. The main difference between the two cases is mainly the rate of convergence. Our algorithm is incremental, and therefore the organization that evolves can adapt and stabilize as agents enter and leave the system.