Through the massive use of mobile devices, data clouds, and the rise of the Internet of Things, large amounts of data have been generated, digitized, and analyzed for the benefit of society. As data are often collected and maintained at different sites, communication has become necessary for nearly every computational task. Moreover, decision makers naturally want to maintain a centralized view of all the data in a timely manner, which requires frequent queries on the distributed data and, in the extreme, continuous monitoring of the query output. The cost of communication has naturally become the bottleneck for such applications. This project aims to develop communication-efficient solutions for distributed computation and monitoring.
This project targets three fundamental aspects of distributed computation: (1) the tradeoffs between the communication cost and the number of rounds of the computation in distributed one-shot computation, (2) the power of data partitioning, and (3) the connections between distributed one-shot computation and continuous monitoring.
Educational and Other Development A Trilogy of Courses: