The 42nd IPP Symposium
The Role of Quantitative Models in Building Scalable Cloud Infrastructures
Joseph L. Hellerstein, Google, Inc.
Planetary scale cloud computing requires scalable infrastructures for compute, storage, network, and services that support programming models such as Map Reduce. There are many design choices that arise in the construction of cloud infrastructures. Examples include: scheduling policies for compute clusters, caching and replication policies for storage, and approaches to integrating bandwidth management with application requirements for quality of service (QoS). These design choices must be evaluated in terms of their impact on QoS considerations such as throughput, latency, and jitter as well as the consumption of power, compute, storage, and network bandwidth. The scale of cloud infrastructures typically makes it impractical or ineffective to do these evaluations using test systems, and, for the most part, it is too costly and time-consuming to evaluate designs by building and deploying multiple implementations. This talk discusses ways in which Google uses quantitative models to evaluate design decisions for cloud infrastructures. In some cases, we incorporate quantitative models into production systems to improve the quality of on-line decision making. Since the effectiveness of a quantitative model relies on the type and accuracy of workload characteristics, the talk also addresses workload characterization.
Joseph L Hellerstein is at Google, Inc. where manages the Performance Analytics Department that develops scalable resource management algorithms and tools for performance prediction and analysis. From 2006 to 2008, he was a Principal Architect at Microsoft Developer Division where he developed scheduling optimizations for .NET. From 1984 through 2006, he was a Senior Manager at the IBM Thomas J. Watson Research Center in Hawthorne, New York, where he founded the Adaptive Systems Department that contributed control technologies to IBM products. Dr. Hellerstein received his undergraduate degree from the University of Michigan in Ann Arbor, and his M.S. and Ph.D. in Computer Science from the University of California at Los Angeles. He has published over 100 peer-reviewed papers and two books, and has taught at Columbia University and the University of Washington. Dr. Hellerstein is a Fellow of the IEEE and received the IEEE/IFIP Stokesberry Award for outstanding contributions to the network management community.
