SELF ORGANIZATION MECHANISM IN AN AGENT NETWORK BY DECENTRALIZED APPROACH

Abstract

Self-organization provides a suitable model for developing self-managed complex distributed systems, such as grid computing and sensor networks. Unlike current related studies, which propose only a single principle of self-organization, this mechanism synthesizes the three principles of self-organization: cloning/ spawning, resource exchange and relation adaptation. Based on this mechanism, an agent can autonomously generate new agents when it is overloaded, exchange resources with other agents if necessary, and modify relations with other agents to achieve a better agent network structure. In this way, agents can adapt to dynamic environments. The proposed mechanism is evaluated through a comparison with three other approaches, each of which represents state-of-the-art research in each of the three self-organization principles. Experimental results demonstrate that the proposed mechanism outperforms the three approaches in terms of the profit of individual agents and the entire agent network, the load-balancing among agents, and the time consumption to finish a simulation run. In addition, in a dynamic environment, it is nearly impossible to use a static, design time generated system structure for efficient problem solving. Instead, the system needs to be able to self-organize at runtime, which means that the components of the system are responsible for adapting themselves to suit the dynamic environment. Self-organization is usually defined as "the mechanism or the process enabling the system to change its organization without explicit external command during its execution time.