The research objective of this award is to develop a computational framework addressing dynamic clustering and classification problems defined over large-scale networks. This framework will specifically address combinatorial computational complexity and scalability, variability in coverage and coordination cost functions, area-specific constraints on dynamics of constituent elements, their communication network structures, and their interactions or interdependencies. The dominant methods in our framework are deterministic, but have a strong stochastic conceptual basis where a probability density function is ascribed on the space of decision variables in such a way that the most probable value for the decision variable is an approximate solution to the combinatorial problem. This probability density function is derived using the maximum entropy principle. In this research, we bring together tools from control and dynamic system theory, optimization theory, and information theory to formulate a flexible framework that can be used for many application domains. In particular, we will demonstrate the framework through clustering and classification problems related to Intelligent Building Systems and Disaster Relief Operations.
If successful, the proposed research will directly impact analysis and design of combinatorial optimization algorithms and application areas of great significance to medical, infrastructure, and cyber industries such as bioinformatics, chemoinformatics, sensor networks, combinatorial drug discovery, and data mining. In particular our results will (1) enable simultaneous coverage and routing in sensor networks found in intelligent building systems, (2) facilitate optimization of search and rescue operations in disaster relief scenarios, and (3) generate scalable algorithms for combinatorial drug design. Graduate and undergraduate engineering students will benefit through classroom instruction and involvement in the research. A graphical user interface (GUI) based software module will be integrated with the web to generate interactive communication, capabilities with experts, students and the community at large.
