Some cloud storage services, like Windows Azure, replicate data while providing strong consistency to their clients while others, like Amazon, have chosen eventual consistency in order to obtain better performance and availability. A broader class of consistency guarantees can, and perhaps should, be offered to clients that read shared data. During a baseball game, for example, different participants (the scorekeeper, umpire, sportswriter, and so on) benefit from six different consistency guarantees when reading the current score. Eventual consistency is insufficient for most of the participants, but strong consistency is not needed either.
Slides linked below.
Video available on Youtube: https://www.youtube.com/watch?v=gluIh8zd26I.
Doug Terry is a Principal Researcher in the Microsoft Research Silicon Valley Lab. His main research interests are in the design and implementation of novel distributed systems. Prior to joining Microsoft, Doug was the founder and CTO of Cogenia and chief scientist of Xerox PARC's Computer Science Laboratory, where he helped pioneer the notion of ubiquitous computing and led a number of research projects on eventually consistent distributed and mobile systems. He has published papers on a variety of topics including epidemic algorithms, collaborative filtering, continuous queries, active documents, the Etherphone system, the Bayou replicated database, track-based applications, and consistency guarantees, and he wrote a Synthesis Lecture on "Replicated Data Management for Mobile Computing." Doug has a Ph.D. in Computer Science from U. C. Berkeley, where he worked on Berkeley UNIX, developed the first version of the BIND DNS server, and occasionally teaches courses. He earned a B.A. in Computer Science from UCSD. He is a Fellow of the ACM.Speakers home page
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