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Algorithms for Data Management and Migration

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Google Tech Talks January, 23 2008 ABSTRACT I will describe some algorithms for addressing some fundamental optimization problems that arise in the context of data storage and management. In the first part of the talk we will address the following question: How should we store data in order to effectively cope with non-uniform demand for data? How many copies of popular data objects do we need? Where should we store them for effective load balancing? In the second part of the talk we will address the issue of moving data objects quickly, to react to changing demand patterns. We will develop approximation algorithms for these problems. The first part of the talk is joint work with Golubchik, Khanna,Thurimella and Zhu. The second part is joint work with Kim and Wan. Speaker: Samir Khuller Samir Khuller received his M.S and Ph.D from Cornell University in 1989 and 1990, respectively. He spent 2 years as a Research Associate at the Institute for Advanced Computer Studies at the University of Maryland, before joining the Computer Science Department in 1992, where he is a Professor and Associate Chair in the Department of Computer Science. His research interests are in graph algorithms, discrete optimization, and computational geometry. He has published about 130 journal and conference papers, and several book chapters on these topics. He received the National Science Foundation's Career Development Award, the Dean's Teaching Excellence Award and also a CTE-Lilly Teaching Fellowship. In 2003, he and his students were awarded the "Best newcomer paper" award for the ACM PODS Conference. He received the University of Maryland's Distinguished Scholar Teacher Award in 2007.

Channel: People & Blogs
Uploaded: January 24, 2008 at 10:06 am
Author: googletechtalks

Length: 54:56
Rating: 4.50
Views: 6007

Tags: education  engedu  google  googletechtalks  talk  talks  techtalk  techtalks  

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hyungpower (March 13, 2008 at 6:18 am)
I'm just curious. Is this algorithm evaluated with real-world applications and data? To me, Load Balancing for storing data is quite interesting.

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