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Learning Predictive Execution for Data-driven Applications
Beteiligte : Khuzaima Daudjee (U. Waterloo)Khuzaima Daudjee
Cheriton School of Computer Science
University of Waterloo
Caching is a popular technique for bringing data closer to applications that are geographically distributed. I will present Apollo, our system that can learn data access patterns exhibited by applications to identify results of queries that, when predictively executed and cached, can improve performance of these applications.
Khuzaima Daudjee is a faculty member at the University of Waterloo. His research interests are in designing and building large scale systems with a focus on storage systems, database systems, distributed systems and graph processing systems. He has served on program committees of major conferences such as VLDB, ICDE, ICDCS and is Associate Editor for Information Systems and IEEE Transactions on Knowledge and Data Engineering. He has been a Visiting Research Scientist at Japan National Institute of Informatics and Visiting Professor at Sapienza University of Rome. He is the recipient of a best paper award at the ACM Symposium on Cloud Computing and University of Waterloo Outstanding Performance Award.
marc.shapiro (at) nullacm.org