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Algorithms for Data Management and Migration

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Google Tech TalksJanuary, 23 2008ABSTRACTI will describe some algorithms for addressing some fundamental optimizationproblems that arise in the context of data storage and management. In thefirst part of the talk we will address the following question: How shouldwe store data in order to effectively cope with non-uniform demand fordata? How many copies of popular data objects do we need? Where shouldwe store them for effective load balancing?In the second part of the talk we will address the issue of movingdata objects quickly, to react to changing demand patterns. We willdevelop 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 KhullerSamir Khuller received his M.S and Ph.D from Cornell University in 1989and 1990, respectively. He spent 2 years as a Research Associate at theInstitute for Advanced Computer Studies at the University of Maryland,before joining the Computer Science Department in 1992, where he is a Professorand Associate Chair in the Department of Computer Science.His research interests are in graph algorithms, discrete optimization, andcomputational geometry. He has published about 130 journal and conferencepapers, 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 forthe ACM PODS Conference. He received the University of Maryland'sDistinguished Scholar Teacher Award in 2007.

Channel: People & Blogs
Uploaded: November 30, 1999 at 12:00 am
Author: googletechtalks

Length: 54:56
Rating: 4.50
Views: 6979

Tags: education  engedu  google  googletechtalks  talk  talks  techtalk  techtalks  

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tqd86 (November 30, 1999 at 12:00 am)
it is.
hyungpower (November 30, 1999 at 12:00 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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