Load Balancing Using Limited State Information
Abstract:
Social network providers, search engine providers, and other big data companies operate massive data centers with thousands of processors handling data processing requests from incoming tasks. A central problem in such data centers is to design good load balancing
algorithms using very little state information, where the state of each processor is the queue length of tasks waiting to be processed at that processor. We will present an algorithm which does remarkably well while sampling approximately only one queue per arriving task. This reduces the sampling requirement by half compared to previously known algorithms, while matching the delay performance of the best known algorithms. Joint work with Lei Ying and Xiaohan Kang.
Biography:R. Srikant received his B.Tech. from the Indian Institute of Technology, Madras in 1985, his M.S. and Ph.D. from the University of Illinois at Urbana-Champaign in 1988 and 1991, respectively, all in Electrical Engineering. He was a Member of Technical Staff at AT&T Bell Laboratories from 1991 to 1995. He is currently with the University of Illinois at Urbana-Champaign, where he is the Fredric G. and Elizabeth H. Nearing Endowed Professor of Electrical and Computer Engineering and a Professor in the Coordinated Science Lab.