【报告题目】 Provably Delay Efficient Data Retrieving In Storage Clouds
【报 告 人】 Dr. Yin Sun
【摘 要】One key requirement for storage clouds is to be able to retrieve data quickly. Recent system measurements have shown that the data retrieving delay in storage clouds is highly variable, which may result in a long latency tail. One crucial idea to improve the delay performance is to retrieve multiple data copies by using parallel downloading threads. However, how to optimally schedule these downloading threads to minimize the data retrieving delay remains to be an important open problem. In this paper, we develop low-complexity thread scheduling policies for several important classes of data downloading time distributions, and prove that these policies either minimize the average delay or deviate from the optimum average delay by at most a constant gap. These theoretical results hold for an arbitrary arrival process of read requests that may contain finite or infinite read requests, and for the coexistence of multiple MDS storage codes with diverse code parameters. Our numerical results show that the delay performance of the proposed policies is significantly better than that of First-Come-First-Served (FCFS) policies considered in prior work.
Reference: Y. Sun, Z. Zheng, C. E. Koksal, K. Kim, and N. B. Shroff, Provably delay efficient data retrieving in storage clouds, in Proceeding of IEEE INFOCOM, 2015, with technical report available at http://arxiv.org/abs/1501.01661
YIN SUN received his B.S. and Ph.D. degrees from Tsinghua University, Beijing, China, in 2006 and 2011, respectively, in Electrical Engineering. He has been working as a Postdoctoral Fellow in the Department of Electrical and Computer Engineering at the Ohio State University during 2011- 2014, and as a research associate since 2014. His research interests include the design, performance, and control of information, communication, and computer systems. The paper he co-authored received the best student paper award at IEEE WiOpt 2013.