Optimization and Control of Stochastic Wireless

Massachusetts Institute Of Technology, Cambridge MA

Investigators

Abstract

0621922 Parrilo The goal of this research effort is to develop a systematic approach to the analysis and synthesis of dynamic cross-layer control policies for stochastic wireless networks. Our aim is to produce mathematical and computational tools to systematically explore the performance and robustness trade-offs inherent to the resulting scheduling policies, and to devise efficient distributed algorithms for their implementation. We will be inspired by control-theoretic concepts to quantify performance, heavily modified to take into account the structural features specific to the networking setting. Among the performance characteristics that our formulation will tackle are network delay and rate of convergence, with computational ideas playing a prominent role in our developments. Intellectual Merit: The major goal in this project is to extend promising early results and develop new frameworks to understand and systematically analyze the operation of dynamic wireless networks. Such a task requires the combination of ideas and mathematical tools from network optimization, systems theory, stochastic control, and game theory. This is an important step towards the development of a framework capable of dealing with realistic, large-scale stochastic networks, aimed at the development of new network protocols and architectures with much better performance improvements. Broader Impacts: The methods and techniques will contribute to the efficient and reliable design and operation of wireless networks. This is an area of clear technological interest, wide societal impact, and obvious economic implications. Key features of this proposal include its integration with curriculum development, undergraduate research projects, new programs on computational optimization, and close collaboration with industrial partners and government research labs.