A survey of Web cache replacement strategies

Podlipnig, Stefan; Böszörményi, László

doi:10.1145/954339.954341

Cited by 638 publications

(354 citation statements)

References 52 publications

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“…The static cache content is filled using the frequent queries obtained from a query log. The dynamic cache changes its content based on the query stream, applying a cache eviction policy such as the least recently used (LRU) or least frequently used (LFU) policies (a detailed survey on cache replacement policies is provided in [Podlipnig and Boszormenyi 2003]). Markatos shows that a static cache achieves better hit ratios for small cache capacities; however, a dynamic cache is preferable for large-capacity caches.…”

Section: Search Results Cachingmentioning

confidence: 99%

Second Chance: A Hybrid Approach for Dynamic Result Caching in Search Engines

Altıngövde

Ozcan

Cambazoğlu

et al. 2011

Lecture Notes in Computer Science

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Web search engines are known to cache the results of previously issued queries. The stored results typically contain the document summaries and some data that is used to construct the final search result page returned to the user. An alternative strategy is to store in the cache only the result document IDs, which take much less space, allowing results of more queries to be cached. These two strategies lead to an interesting trade-off between the hit rate and the average query response latency. In this work, in order to exploit this trade-off, we propose a hybrid result caching strategy where a dynamic result cache is split into two sections: an HTML cache and a docID cache. Moreover, using a realistic cost model, we evaluate the performance of different result prefetching strategies for the proposed hybrid cache and the baseline HTML-only cache. Finally, we propose a machine learning approach to predict singleton queries, which occur only once in the query stream. We show that when the proposed hybrid result caching strategy is coupled with the singleton query predictor, the hit rate is further improved.

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Section: Search Results Cachingmentioning

confidence: 99%

Second Chance: A Hybrid Approach for Dynamic Result Caching in Search Engines

Altıngövde

Ozcan

Cambazoğlu

et al. 2011

Lecture Notes in Computer Science

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“…This adds another dimension to caching strategies [15], which are in this context often measured differently: By the hit rate, which is the relative number of hits to objects of the total number of object accesses, and by the byte hit rate, which is the number of bytes served from the cache compared to the total number of bytes requested.…”

Section: Caching In Various Contextsmentioning

confidence: 99%

“…Williams et al [18] found that for web proxy caches both size based and frequency based algorithms outperform pure LRU. For a more detailed overview of caching in the web context see Podlinig and Böszörmenyi [15]. While files storing research papers also differ in size, the difference in scale is much smaller and in fact for this study the sizes are not considered.…”

Section: Caching In Various Contextsmentioning

confidence: 99%

Effectiveness of caching in a distributed digital library system

Hollmann

Ardö

Stenström

2007

Journal of Systems Architecture

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Today independent publishers are offering digital libraries with fulltext archives. In an attempt to provide a single user-interface to a large set of archives, the studied Article-Database-Service offers a consolidated interface to a geographically distributed set of archives. While this approach offers a tremendous functional advantage to a user, the fulltext download delays caused by the network and queuing in servers make the user-perceived interactive performance poor. This paper studies how effective caching of articles at the client level can be achieved as well as at intermediate points as manifested by gateways that implement the interfaces to the many fulltext archives. A central research question in this approach is: What is the nature of locality in the user access stream to such a digital library. Based on access logs that drive the simulations, it is shown that client-side caching can result in a 20% hit rate. Even at the gateway level temporal locality is observable, but published replacement algorithms are unable to exploit this temporal locality. Additionally, spatial locality can be exploited by considering loading into cache all articles in an issue, volume, or journal, if a single article is accessed. But our experiments showed that improvement introduced a lot of overhead. Finally, it is shown that the reason for this cache behavior is the long time distance between re-accesses, which makes caching quite unfeasable.

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“…Over the past few years, most studies for Web cache management have focused on Web cache replacement algorithms, such as LRU, LFU, LRU-K, and GD-SIZE that determine which objects in the Web cache should be replaced when a new object is brought in [1]. However, most of them have not considered the issue of admission control, which determines whether a new object should be cached or not.…”

Section: Introductionmentioning

confidence: 99%

An Effective Self-Adaptive Admission Control Algorithm for Large Web Caches

Yang

Lee

Chung

et al. 2009

IEICE Trans. Inf. & Syst.

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SUMMARYIn this paper, we propose an effective Web cache admission control algorithm. By selectively admitting objects into the cache, the proposed algorithm can significantly reduce the amount of disk I/O on a Web cache while maintaining a high hit ratio. The proposed algorithm adaptively adjusts its own admission control parameter, requiring no usersupplied parameters. Through extensive experiments, we show the effectiveness of the proposed algorithm.

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A survey of Web cache replacement strategies

Cited by 638 publications

References 52 publications

Second Chance: A Hybrid Approach for Dynamic Result Caching in Search Engines

Second Chance: A Hybrid Approach for Dynamic Result Caching in Search Engines

Effectiveness of caching in a distributed digital library system

An Effective Self-Adaptive Admission Control Algorithm for Large Web Caches

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