Quantitative Analysis of Zipf’s Law on Web Cache

Shi, Lei; Gu, Zhimin; Wei, Lin; Shi, Yun

doi:10.1007/11576235_84

Cited by 40 publications

(31 citation statements)

References 9 publications

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“…For example, Breslau et al [3] gave six traces ranging from academic, corporate to ISP environments and this evidence supported that Web accessed pattern followed the Zipf-like distribution. In order to assure that the measured popularity is reliable, Shi et al [4] suggested a time interval which is the most appropriate length to collect the Web accessed information. In IPTV system, the characteristics of VOD have some minor variances with Web objects, such as average file size, object life cycle, and user behavior.…”

Section: Content Prefetchingmentioning

confidence: 99%

Window-Based Popularity Caching for IPTV On-Demand Services

Chiu

Chang

Tseng

et al. 2011

ISRN Communications and Networking

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In recent years, many telecommunication companies have regarded IP network as a new delivery platform for providing TV services because IP network is equipped with two-way and high-speed communication abilities which are appropriate to provide on-demand services and linear TV programs. However, in this IPTV system, the requests of VOD (video on demand) are usually aggregated in a short period intensively and user preferences are fluctuated dynamically. Moreover, the VOD content is updated frequently under the management of IPTV providers. Thus, an accurate popularity prediction method and an effective cache system are vital because they affect the IPTV performance directly. This paper proposed a new window-based popularity mechanism which automatically responds to the fluctuation of user interests and instantly adjusts the popularity of VOD. Further, we applied our method to a commercial IPTV system and the results illustrated that our mechanism indeed offers a significant improvement.

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Section: Content Prefetchingmentioning

confidence: 99%

Window-Based Popularity Caching for IPTV On-Demand Services

Chiu

Chang

Tseng

et al. 2011

ISRN Communications and Networking

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“…Employed in other research ( [20], [21], and [22]) and written in C, this application readily facilitated the simulation of the LRU replacement policy. The simulator was enhanced by implementing the LFU policy as well as the adaptive policy, LFRU3, in order to simulate these policies along with the already available LRU.…”

Section: Preliminary Resultsmentioning

confidence: 99%

Adaptive Cache Replacement:A Novel Approach

Elfayoumy¹,

Warden²

2014

ijacsa

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Abstract-Cache replacement policies are developed to help insure optimal use of limited resources. Varieties of such algorithms exist with relatively few that dynamically adapt to traffic patterns. Algorithms that are tunable typically utilize offline training mechanisms or trial-and-error to determine optimal characteristics.Utilizing multiple algorithms to establish an efficient replacement policy that dynamically adapts to changes in traffic load and access patterns is a novel option that is introduced in this article. A simulation of this approach utilizing two existing, simple, and effective policies; namely, LRU and LFU was studied to assess the potential of the adaptive policy. This policy is compared and contrasted to other cache replacement policies utilizing public traffic samples mentioned in the literature as well as a synthetic model created from existing samples. Simulation results suggest that the adaptive cache replacement policy is beneficial, primarily in smaller cache sizes.

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“…Popularity-based models, such as distributed high-speed caching based on spatial and temporal locality (DCST) [29] and bandwidth hierarchy-based replication (BHR) [30], calculate the popularities of all of the tiles and cache the tiles with higher popularities [31]. DCST uses the election scheme of the United States Congress to select the tiles to cache and uses a steady-state cache hit ratio parameter to limit the tile selection range, thus saving cache space.…”

Section: Related Workmentioning

confidence: 99%

An enhanced active caching strategy for data-intensive computations in distributed GIS

et al. 2017

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Caching can prepare data for computational tasks in advance by tracking the requirements and behaviors of distributed geographical information systems to reduce network latency and improve computational performance. This paper presents an enhanced method to actively cache data for data-intensive computations that considers both data relationships and the timeliness of those relationships. First, the access correlations, the correlation steps and the times of the correlations are computed based on the behaviors of the computational tasks. Because the influence of historically accessed records will decrease gradually over time, only recently accessed records are used. To track changes in the relationships and prevent cache waste problems, each record is given a different age-based weight. A conditional caching probability can then be computed based on the timeliness relationships, which can be used to find the appropriate data to compute simultaneously. Finally, we present several experiments that compare the proposed method with techniques that use other data placement strategies, active caching strategies and passive caching algorithms. The results show that the proposed model has better performance than other algorithms in all respects. In addition, the proposed model results in a lower cache replacement ratio. The experiments with different data sets on different data scales indicate that the proposed algorithm can also be used in large-scale distributed environments. B Shaoming Pan

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Quantitative Analysis of Zipf’s Law on Web Cache

Cited by 40 publications

References 9 publications

Window-Based Popularity Caching for IPTV On-Demand Services

Window-Based Popularity Caching for IPTV On-Demand Services

Adaptive Cache Replacement:A Novel Approach

An enhanced active caching strategy for data-intensive computations in distributed GIS

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