Silo, rainbow, and caching token: schemes for scalable, fault tolerant stream caching

  • Authors:

  • Youngsu Chae;K. Guo;M. M. Buddhikot;S. Suri;E. W. Zegura

  • Affiliations:

  • Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA;-;-;-;-

  • Venue:
  • IEEE Journal on Selected Areas in Communications
  • Year:
  • 2006

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Abstract

In the current Internet, Web content is increasingly being cached closer to the end user to reduce network and Web server load and improve performance. Existing Web caching systems typically cache entire Web documents and attempt to keep them consistent with the origin server. This approach works well for text and images; for bandwidth intensive multimedia data such as audio and video, caching entire documents is not cost effective and does not scale. An alternative approach is to cache parts of the multimedia stream on different caches in the network and coordinate stream playback from these independent caches. From the perspective of the clients, the collection of cooperating distributed caches acts as a single fault tolerant, scalable cache. In this paper, we focus on data placement and replacement techniques for such co-operating distributed caches. Specifically, we propose the following new schemes that work together. 1) A family of distributed layouts, consisting of two layouts, namely RCache and Silo. The RCache layout is a simple, randomized, easy-to-implement layout that distributes constant length segments of a clip among caches and provides modest storage efficiency. The Silo scheme improves upon RCache; it accounts for long term clip popularity and intraclip segment popularity metrics and provides parameters to tune storage efficiency, server load, and playback switch-overs. 2) Rainbow, a local data replacement scheme based on the concept of segment access potential that accurately captures the popularity metrics. 3) Caching Token, a dynamic global data replacement or redistribution scheme that exploits existing data in distributed caches to minimize data distribution overhead. Our schemes optimize storage space, startup latency, server load, network bandwidth usage, and overhead from playback switch-overs. Our analytical and simulation results show that the silo scheme provides three to eight times higher cache hit ratio than a comparable traditional Web caching system that has the same amount of storage space.