Liu wins National Science Foundation CIF Grant
In total, Liu will receive $317,896 for his work based on his research, “Taming Convergence and Delay in Stochastic Network Optimization with Hessian Information.”
Essentially, Liu’s theoretical approaches strive to help advance the resource control and optimization algorithms behind next generation complex networks, making them rapidly approach the optimal operation states in terms of network throughput and end-to-end latency.
Liu’s research focus is on the areas of network control and optimization, data analytics, and cyber-physical systems (CPS).
According to NSF’s award notice, “With the rapid integration of massive amounts of data and new network devices, today's network infrastructures are being stretched to their limits. As a result, recent years have witnessed a critical need for developing fast-converging distributed stochastic network control and optimization algorithms to increase throughput and reduce delay.”
Liu’s work, and the CIF program, address the challenge of distributed control and optimization for next generation complex network systems, where the rapidly changing network states necessitate fast-convergence and low-delay in distributed optimization algorithms.
“The research in my proposed project not only works for computer networks, but can also transition to other complex network systems, such as smart electric power grid, smart transportation networks, supply chain management,” Liu said.
As for the technical jargon “Hessian information,” which is a mathematical term describing the local curvature of a function of many variables, Liu said its physical meaning in practice can be roughly interpreted as the network states variations, such as queueing backlogs, service/arrival statistics, which occur across both space and time domains.
“This is contrasted to the traditional network control and optimization approaches, which only consider network states variations in time domain,” he said.
Liu’s research will develop a series of new distributed algorithmic techniques that offer orders of magnitudes improvements in both convergence speed and queueing delay compared to the traditional approaches, while attaining the same provable network-utility optimality.
To learn more about details of Liu’s research and how the CIF funds will be utilized, go online to the official NSF award notice:
http://www.nsf.gov/awardsearch/showAward?AWD_ID=1618318
To learn more about Prof. Liu and his research:
