Date	May 4, 2017
Speaker	Mahesh Balakrishnan Yale University
Title	The FuzzyLog Approach to Building Distributed Services
Abstract	Control plane applications such as coordination services, SDN controllers, filesystem namespaces, and big data schedulers have strong requirements for consistency as well as performance. Building such applications is currently a black art, requiring a slew of complex distributed protocols that are inefficient when layered and difficult to combine. The shared log approach (seen in the Corfu, Tango, and CorfuDB systems) achieves simplicity for distributed applications by replacing complex protocols with a single shared log; however, it does so by introducing a global ordering over all updates in the system, which can be expensive, unnecessary, and sometimes impossible. We propose the FuzzyLog abstraction, which provides applications the simplicity of a shared log without its drawbacks. The FuzzyLog allows applications to construct and access a durable, iterable partial order of updates in the system. FuzzyLog applications retain the simplicity of their shared log counterparts while extracting parallelism, providing a range of consistency guarantees and tolerating network partitions.
Bio	Mahesh Balakrishnan is an Associate Professor (pre-tenure) at Yale University since Fall 2015. He received a PhD in Computer Science from Cornell University in 2009. He worked at Microsoft Research Silicon Valley from 2008 to 2014, where he co-led the CORFU and Tango projects on shared log systems, and briefly at VMware Research in 2015. His research interests span distributed systems, storage and networking. Currently, his research centers on new abstractions that simplify the construction of fast, reliable and consistent systems, while hiding the complexity of concurrency, failures and hardware details from programmers. He has published 35+ peer-reviewed papers in systems conferences such as SOSP, NSDI and FAST and journals such as TOCS. His current research is funded by NSF, Facebook Awards, and a VMware Early Career faculty grant.
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