Dynamic information-based scalable hashing on a cluster of web cache servers

  • Authors:
  • Hukeun Kwak;Andrew Sohn;Kyusik Chung

  • Affiliations:
  • School of Electronic Engineering, Soongsil University, 511 Sangdo-dong, Dongjak-gu, Seoul, 156-743, Korea;Computer Science Department, New Jersey Institute of Technology, Newark, NJ07102, U.S.A.;School of Electronic Engineering, Soongsil University, 511 Sangdo-dong, Dongjak-gu, Seoul, 156-743, Korea

  • Venue:
  • Concurrency and Computation: Practice & Experience
  • Year:
  • 2011

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Abstract

Caching web pages is an important part of web infrastructures. Medium to large-scale infrastructures deploy a cluster of servers to solve the scalability and storage problems inherent in caching. In this paper we present dynamic information-based scalable hashing that evenly hashes client requests to a cluster of cache servers, resulting in performance scalability. Runtime information is used to determine when and how to cache pages. Cached pages are stored and retrieved mutually exclusively to/from all the servers to minimize the use of storage, resulting in storage scalability. We set up an experimental environment consisting of various machines, including client servers, a cluster of 16 cache servers, and a load balancer. We demonstrate through experimental results that dynamic information-based scalable hashing maximizes both performance scalability and storage scalability while the existing approaches do only either one of the two. Copyright © 2011 John Wiley & Sons, Ltd.