• DocumentCode
    652859
  • Title

    Proteus: Power Proportional Memory Cache Cluster in Data Centers

  • Author

    Shen Li ; Shiguang Wang ; Fan Yang ; Shaohan Hu ; Saremi, Fatemeh ; Abdelzaher, Tarek

  • Author_Institution
    Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2013
  • fDate
    8-11 July 2013
  • Firstpage
    73
  • Lastpage
    82
  • Abstract
    In this paper, we describe the design, implementation and evaluation of Proteus, a power-proportional cache cluster which eliminates the delay penalty during server provisioning dynamics. To speed up data center services, a cache cluster is used in front of the database tier, providing fast in-cache data access. Since the number of cache servers is large, building power-proportional cache clusters can lead to considerable monetary savings. Dynamic server provisioning, one common methodology for realizing power proportionality in data centers, calls for agile load balancing schemes and smart in-cache data migration algorithms when applied to cache clusters. Otherwise, it induces unacceptable delay spikes due to data re-allocation among cache servers. Proteus addresses both challenges by using a specifically designed virtual nodes placement algorithm and an amortized data migration policy. We implement Proteus, and evaluate it on a 40-server cluster using real Wikipedia data and workload traces. The results show that, with Proteus, the load distribution is much more evenly balanced compared to the case of applying unmodified consistent hashing. At the same time, Proteus induces almost no extra delay during provisioning transitions, which is a significant advantage over other state-of-the-art solutions.
  • Keywords
    cache storage; computer centres; power aware computing; resource allocation; Proteus; Wikipedia data; agile load balancing schemes; amortized data migration policy; data center services; database tier; delay penalty; delay spikes; dynamic server provisioning; in-cache data access; power proportional memory cache cluster; power proportionality; server provisioning dynamics; smart in-cache data migration algorithms; virtual nodes; workload traces; Algorithm design and analysis; Clustering algorithms; Databases; Delays; Heuristic algorithms; Web servers; Bloom filter; Data center; Energy proportionality; Load balancing; Memcached;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing Systems (ICDCS), 2013 IEEE 33rd International Conference on
  • Conference_Location
    Philadelphia, PA
  • ISSN
    1063-6927
  • Type

    conf

  • DOI
    10.1109/ICDCS.2013.50
  • Filename
    6681577