Web caching framework: analytical models and beyond

Zhang, J.; Izmailov, Rauf; Reininger, D.; Ott, Maximilian

doi:10.1109/wiapp.1999.788030

Cited by 23 publications

(27 citation statements)

References 8 publications

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“…According to a survey by Podlipnig and Böszörmenyi [9], these algorithms can be grouped into five different categories. The first category consists of recency based algorithms [16,17,29], which use the time elapsed since the last request to a cached page as the main factor in their replacement decisions. LRU is the most representative of such algorithms and other algorithms are usually extensions of standard LRU.…”

Section: Related Workmentioning

confidence: 99%

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An adaptive semantics-aware replacement algorithm for web caching

Negrão

Roque

Ferreira

et al. 2015

J Internet Serv Appl

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As the web expands its overwhelming presence in our daily lives, the pressure to improve the performance of web servers increases. An essential optimization technique that enables Internet-scale web servers to service clients more efficiently and with lower resource demands consists in caching requested web objects on intermediate cache servers. At the core of the cache server operation is the replacement algorithm, which is in charge of selecting, according to a cache replacement policy, the cached pages that should be removed in order to make space for new pages. Traditional replacement policies used in practice take advantage of temporal reference locality by removing the least recently/frequently requested pages from the cache. In this paper we propose a new solution that adds a spatial dimension to the cache replacement process. Our solution is motivated by the observation that users typically browse the Web by successively following the links on the web pages they visit. Our system, called SACS, measures the distance between objects in terms of the number of links necessary to navigate from one object to another. Then, when replacement takes place, objects that are distant from the most recently accessed pages are candidates for removal; the closest an object is to a recently accessed page, the less likely it is to be evicted. We have implemented a cache server using SACS and evaluated our solution against other cache replacement strategies. In this paper we present the details of the design and implementation of SACS and discuss the evaluation results obtained.

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Section: Related Workmentioning

confidence: 99%

“…At the other end of the spectrum, more complex solutions based on machine learning try to predict which pages are going to be more frequently accessed by users based on past behavior [11][12][13]. In between, several other cache replacement algorithms have been proposed [14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

An adaptive semantics-aware replacement algorithm for web caching

Negrão

Roque

Ferreira

et al. 2015

J Internet Serv Appl

View full text Add to dashboard Cite

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“…Since Zipf-like distribution has been widely tested against the distributions collected from the real traces, e.g., [3], [7], [10], as well as our own tests in Section IV, we model by Zipf-like distributions for and (2) where is the normalization factor, is the popularity rank of document at cache , and is a parameter taking values in [0. 6,1].…”

Section: A Model Description and Notationsmentioning

confidence: 99%

“…Most of the research papers on cache replacement algorithm design, to date, have focused on a single cache, e.g., [3], [6], [8], [10], [13]. However, when caches are arranged in a hierarchical structure, running a cache replacement algorithm which is optimized for an isolated cache may not lead to overall good performance.…”

Section: Introductionmentioning

confidence: 99%

“…First, unlike the previous analytic work on web caching which is based on statistic analysis, e.g., [1], [3], this paper proposes a stochastic model, which allows us to characterize the caching processes for individual documents in a two-level hierarchical caching system. In this model, the LRU algorithm runs at individual caches in an uncooperative manner.…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical Web caching systems: modeling, design and experimental results

Che

Tung

Wang

2002

IEEE J. Select. Areas Commun.

363

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Abstract-This paper aims at finding fundamental design principles for hierarchical web caching. An analytical modeling technique is developed to characterize an uncooperative twolevel hierarchical caching system where the least recently used (LRU) algorithm is locally run at each cache. With this modeling technique, we are able to identify a characteristic time for each cache, which plays a fundamental role in understanding the caching processes. In particular, a cache can be viewed roughly as a low-pass filter with its cutoff frequency equal to the inverse of the characteristic time. Documents with access frequencies lower than this cutoff frequency have good chances to pass through the cache without cache hits. This viewpoint enables us to take any branch of the cache tree as a tandem of low-pass filters at different cutoff frequencies, which further results in the finding of two fundamental design principles. Finally, to demonstrate how to use the principles to guide the caching algorithm design, we propose a cooperative hierarchical web caching architecture based on these principles. Both model-based and real trace simulation studies show that the proposed cooperative architecture results in more than 50% memory saving and substantial central processing unit (CPU) power saving for the management and update of cache entries compared with the traditional uncooperative hierarchical caching architecture.Index Terms-Cache replacement algorithms, hierarchical caching, least recently used (LRU), web caching.

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An analytical model for the performance evaluation of stack‐based Web cache replacement algorithms

Messaoud

Youssef

2009

Int J Communication

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SUMMARYWeb caching has been the solution of choice to web latency problems. The efficiency of a Web cache is strongly affected by the replacement algorithm used to decide which objects to evict once the cache is saturated. Numerous web cache replacement algorithms have appeared in the literature. Despite their diversity, a large number of them belong to a class known as stack-based algorithms. These algorithms are evaluated mainly via trace-driven simulation. The very few analytical models reported in the literature were targeted at one particular replacement algorithm, namely least recently used (LRU) or least frequently used (LFU). Further they provide a formula for the evaluation of the Hit Ratio only. The main contribution of this paper is an analytical model for the performance evaluation of any stack-based web cache replacement algorithm. The model provides formulae for the prediction of the object Hit Ratio, the byte Hit Ratio, and the delay saving ratio. The model is validated against extensive discrete event trace-driven simulations of the three popular stack-based algorithms, LRU, LFU, and SIZE, using NLANR and DEC traces. Results show that the analytical model achieves very good accuracy. The mean error deviation between analytical and simulation results is at most 6% for LRU, 6% for the LFU, and 10% for the SIZE stack-based algorithms.

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Web caching framework: analytical models and beyond

Cited by 23 publications

References 8 publications

An adaptive semantics-aware replacement algorithm for web caching

An adaptive semantics-aware replacement algorithm for web caching

Hierarchical Web caching systems: modeling, design and experimental results

An analytical model for the performance evaluation of stack‐based Web cache replacement algorithms

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