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Comparing Agent Paradigms for Resource Management in Sensor Networks

— Management of power and other resources that effect field life is an important consideration in sensor networks. This paper presents and compares alternative agent paradigms applicable for resource management. Such a comparison provides an increased understanding of how the performance of the sensor network changes with the number, functionality, and presence of agents at different levels in the network hierarchy. A modular simulation framework based on object-oriented design was developed to facilitate the implementation and comparison of different agent-based scenarios. This framework was used to generate data for detailed analysis of component interactions and for evaluation of the integrated system. Results comparing the number of computations, number of communications, tracking performance and field life for Monte Carlo simulations of scenarios in which different agent paradigms are employed are presented. The performance results were compared and contrasted with a measure of machine intelligence of agent-based systems that facilitates comparing alternatives having different complexity. Comparison results presented in this paper will assist designers of agent-based systems in utilizing agents to their best advantages in scenarios similar to the wide range of those explored.