Dynamic information-based scalable hashing on a cluster of web cache servers
- Authors
- Kwak, Hukeun; Sohn, Andrew; Chung, Kyusik
- Issue Date
- 10-Mar-2012
- Publisher
- WILEY-BLACKWELL
- Keywords
- cluster utilization; scalability; storage; traffic management; web caching
- Citation
- CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, v.24, no.3, pp.322 - 340
- Journal Title
- CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
- Volume
- 24
- Number
- 3
- Start Page
- 322
- End Page
- 340
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/12477
- DOI
- 10.1002/cpe.1830
- ISSN
- 1532-0626
- 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 (c) 2011 John Wiley & Sons, Ltd.
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Collections - College of Information Technology > Department of Smart Systems Software > 1. Journal Articles
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