SENSORS: Approximate Dynamic Programming for Dynamic Scheduling and Control in Sensor Networks

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Intellectual merit Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. This project explores new techniques using concepts of approximate dynamic programming for sensor scheduling and control to provide computationally feasible and optimal/near optimal solutions to the limited and varying bandwidth problem. The concept of virtual sensors for sensor data selection iwill also be used to accelerate management of sensor networks under dynamic communication constraints. The goal is to enhance the operational performance of distributed sensor networks and advance knowledge and understanding on how to carry out dynamic stochastic scheduling and control in sensor networks. A novel local and global dynamic stochastic scheduling and control strategy for a large scale sensor network will be designed and demonstrated with laboratory simulation and real-time laboratory implementations. Methods proposed to carry out efficient data reduction and representation will result in overcoming bandwidth constraints. The algorithms developed using brain-like structures in this proposal will provide optimal scheduling with guaranteed stability.Broader impacts The benefit to the society includes efficiently operated reliable and secure sensor networks of national and global interest for applications including border surveillance, landmine detection, unmanned aerial vehicle, vehicle navigation, forest fire response, critical infrastructures heavily dependent on network of sensors for control such as the electric power grid, etc. The sensor scheduling algorithms that are developed in this proposal are directly applicable to many other well known problems such as the supply chain management in a warehouse where several tens of mobile Personal Digital Assistants (sensors capable of transmitting images, text and voice) interacting with central sophisticated servers provide command and control solutions for smooth delivery of products and maintenance of inventory. The investigators will promote best practices in engineering, science and education by integrating research in teaching. Underrepresented minority students and female students from Electrical and Computer Engineering as well as students from other departments currently enrolled at the universities will be recruited to participate in the research activities of this proposal. Other broader impacts include international collaboration, between the U.S. and Australia on this proposal.