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An optimal trade-off between content freshness and refresh cost

Part of: Special processes

Published online by Cambridge University Press:  14 July 2016

Yibei Ling  and
Jie Mi
Yibei Ling*
Affiliation:
Telcordia Technologies
Jie Mi*
Affiliation:
Florida International University
*
∗ Postal address: Applied Research, Telcordia Technologies, RRC-1A204, One Telcordia Drive, Piscataway, NJ 08854-4157, USA. Email address: [email protected]
∗∗ Postal address: Department of Statistics, Florida International University, Miami, FL 33199, USA. Email address: [email protected]
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Abstract

Caching is an effective mechanism for reducing bandwidth usage and alleviating server load. However, the use of caching entails a compromise between content freshness and refresh cost. Constant refreshing allows a high degree of content freshness at a greater cost of system resource. Conversely, too little refreshing reduces content freshness but saves the cost of resource usage. To address the freshness-cost problem, we formulate the refresh scheduling problem with a generic cost model and use this cost model to determine an optimal refresh frequency that gives the best trade-off between refresh cost and content freshness. We prove the existence and uniqueness of an optimal refresh frequency under the assumptions that the arrival of updated content is Poisson and the age-related cost monotonically increases with decreasing freshness. In addition, we provide an analytic comparison of system performance under fixed refresh scheduling and random refresh scheduling, showing that two refresh schedulings with the same average refresh frequency are mathematically equivalent in terms of the long-run average cost.

Keywords

Cachingcontent freshnessrefresh costoptimal refresh frequencyPoisson process

MSC classification

Primary: 60K05: Renewal theory
Secondary: 60K10: Applications (reliability, demand theory, etc.)
Type
Research Papers
Information
Journal of Applied Probability , Volume 41 , Issue 3 , September 2004 , pp. 721 - 734
Copyright
Copyright © Applied Probability Trust 2004 

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