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.
Original language | English (US) |
---|---|
Pages (from-to) | 322-340 |
Number of pages | 19 |
Journal | Concurrency Computation Practice and Experience |
Volume | 24 |
Issue number | 3 |
DOIs | |
State | Published - Mar 10 2012 |
All Science Journal Classification (ASJC) codes
- Software
- Theoretical Computer Science
- Computer Networks and Communications
- Computer Science Applications
- Computational Theory and Mathematics
Keywords
- cluster utilization
- scalability
- storage
- traffic management
- web caching