Minimizing Latency in Cloud Based Systems: Replication Over Parallel Servers

We are in the midst of a major data revolution. The total data generated by humans from the dawn of civilization until the turn of the new millennium is now being generated every two days. Driven by a wide range of data-intensive devices and applications, this growth is expected to continue its astonishing march, and fuel the development of new and larger data centers. In order to exploit the low-cost services offered by these resource-rich data centers, application developers are pushing computing and storage away from the end-devices and instead deeper into the data-centers. Hence, the end-users’ experience is now dependent on the performance of the algorithms used for data retrieval within the data-centers. In particular, providing low-latency services is critically important to the end-user experience for a wide variety of applications. Our goal has been to develop the analytical foundations and methodologies to enable cloud computing and storage solutions that result in low-latency services. A variety of cloud based systems can be modeled using multi-server, multi queue queueing systems with data locality constraints. In these systems, replication (or most sophisticated coding schemes) can be used to not only improve reliability but to also reduce latency. However, delay optimality for multi-server queueing systems has been a long-standing open problem, with limited results usually in asymptotic regimes. The key question is can we design resource allocation schemes that are near optimal in distribution for minimizing several different classes of delay metrics that are important in web and cloud based services? In this talk, I will overview some of our recent research efforts at solving this problem, provide some key design principles, and outline a set of what I believe are important open problems.

Bio: Ness B. Shroff received his Ph.D. degree in Electrical Engineering from Columbia University in 1994. He joined Purdue university immediately thereafter as an Assistant Professor in the school of ECE. At Purdue, he became Full Professor of ECE in 2003 and director of CWSA in 2004, a university-wide center on wireless systems and applications. In July 2007, he joined The Ohio State University, where he holds the Ohio Eminent Scholar endowed chair in Networking and Communications, in the departments of ECE and CSE. He holds or has held visiting chaired professor positions at Tsinghua University, Beijing, China and Shanghai Jiaotong University, Shanghai, China, and a visiting position at the Indian Institute of Technology, Bombay, India.  Dr. Shroff is currently an editor at large of IEEE/ACM Trans. on Networking, and senior editor of IEEE Transactions on Control of Networked Systems. He has received numerous best paper awards for his research and listed Thomson Reuters Book on The World’s Most Influential Scientific Minds as well as noted as a highly cited researcher by Thomson Reuters (previously ISI). He also received the IEEE INFOCOM achievement award for seminal contributions to scheduling and resource allocation in wireless networks.