A New Computing Paradigm for Energy-Efficient Collaboration in Underwater Sensor Networks

In this proposal, Intelligent Automation, Inc. (IAI) and its subtractor, Prof. Hairong Qi of the University of Tennessee at Knoxville, propose a novel mobile-agent-based computing paradigm for collaborative information exchange among distributed sensor nodes. Unlike the traditional client/server-based method, the proposed mobile-agent-based approach transfers the partially integrated results and executable code from one node to another and the processing can be done locally on the sensor nodes. The proposed approach consists of two levels: (1) mobile-agent-based computing for collaborative processing among multiple sensor nodes and (2) data processing and fusion at the local nodes. The proposed mobile-agent-based computing model provides a nice balance between energy efficiency and fault tolerance. It presents a framework for efficient usage of energy and bandwidth, scalable computing, reliable and fault-tolerant decision making, as well as supports intermediate results with progressive accuracy. The collaborative data processing and fusion algorithms use the information from multiple sensors. We develop both simulators to study the performance between the mobile-agent-based collaborative processing and the client/server-based centralized processing based on compression algorithms providing a compression ratio.