Memory-based architecture for distributed WWW caching proxy

Nishikawa, Norifumi; Hosokawa, Takafumi; Mori, Yasuhide; Yoshida, Kenichi; Tsuji, Hiroshi

doi:10.1016/s0169-7552(98)00117-2

Cited by 32 publications

(14 citation statements)

References 5 publications

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“…Cunha et al [33] suggested a value of 0.986 and Nishikawa et al [34] suggested 0.75 which is based on their 2000000 requests access log. Objects lifetime is also another characteristics that affects hit rate and bandwidth consumption.…”

Section: B Characteristic Of Web Objectmentioning

confidence: 99%

HitBand: A Prefetching Model to Increase Hit Rate and Reduce Bandwidth Consumption

Anik¹,

Arifa²,

Abdul³

2017

IJIEEB

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Abstract-Caching is a very important issue in distributed web system in order to reduce access latency and server load. A request is a hit if it is available in the cache and if not then it will fetch from the server in order to cache and serve the request. Researches have shown that generic algorithms of caching can increase hit rate up to 40−50%, but adding prefetching scheme can increase this rate to 20%. Prefetching is a technique to fetch documents before they are requested. This paper proposes a process model for prefetching named HitBand which will balance hit rate bandwidth in every scenario with the combination of "Roulette-wheel selection". Roulettewheel selection is a very popular selection based algorithm which selects objects according to their fitness. We have compared our HitBand with the generic algorithms of prefetching like prefetching by popularity, apl characteristic, good Fetch and lifetime. Generic algorithms did not take web object size into consideration and in limited bandwidth scenario object size has a big impact on bandwidth consumption. Though prefetching by lifetime algorithm shows little concern about bandwidth consumption by getting the object with changes happening less frequently but this compromises the hit rate. But our proposed HitBand not only considers bandwidth but also hit rate during prefetching. Performance evaluation of HitBand along with other algorithms is provided in our paper. We have tested our HitBand with the testing engine which is built using JavaScript and maintained under AngularJS framework. From the performance evaluation, our HitBand shows better results both in high and low bandwidth.

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Section: B Characteristic Of Web Objectmentioning

confidence: 99%

HitBand: A Prefetching Model to Increase Hit Rate and Reduce Bandwidth Consumption

Anik¹,

Arifa²,

Abdul³

2017

IJIEEB

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“…After that the Zipf-like behavior (for β = 1 and 0 < β ≤ 1) was gradually confirmed by empirical analyses (e.g., [7]). In fact, different traces, which come from various web sites and have a sufficiently large number of access records, unanimously exhibit the Zipf-like behavior (e.g., β = 0.77 for Digital Equipment Ltd. USA [11], β = 0.69 for UC Berkeley USA [12] and β = 0.69 for Hitachi Ltd. Japan [13]). However, there are also apparently some exceptions.…”

Section: Related Workmentioning

confidence: 99%

CACHERP: A novel dynamic cache size tuning model working with relative object popularity for fast web information retrieval

Wong

Dillon

2006

J Supercomput

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The CACHE RP framework leverages the relative object popularity as the sole parameter for dynamic cache size tuning. In the process it consistently maintains the prescribed cache hit ratio on the fly by deriving the popularity ratio from the current statistics. As a result the accuracy of the statistical CACHE RP operation is independent of changes in the Internet traffic pattern that may switch suddenly. The contribution by the novel CACHE RP framework is that by adaptively maintaining the given hit ratio it effectively reduces the end-to-end information retrieval roundtrip time (RTT) and frees more bandwidth for sharing. This bandwidth would otherwise be consumed in transferring large amounts of data from remote data sources to the proxy server before it is given to the client or requestor.

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“…Nishikawa et al [11] studied an access log of 2, 000, 000 requests and found that the request distribution follows the Zipf's law with α = 0.75, which we use as a default parameter in this paper.…”

Section: Related Workmentioning

confidence: 99%

MMC01-2: A Replica-Conscious Load Balancing Strategy for Large-Scale Multimedia Storage Systems

Zeng

Veeravalli

2006

IEEE Globecom 2006

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In distributed multimedia storage systems where client requests for different multimedia objects may have different demands, placement and replication of the objects is an important factor, as it may result in an imbalance in server loading across the system. Replica management and load balancing is all the more a crucial issue for large-scale multimedia systems. We design and analyze a heuristic static strategy to determine the placement, number of replicas of the objects, and balance the client requests among the servers, to minimize the average waiting time (AWT) of the requests. Our strategy exploits clever virtual routing technique to strike a balance among the servers for load balancing. We validate the performance via rigorous simulations with respect to several influencing factors and compare with a system that uses hashing function only for load balancing.

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Memory-based architecture for distributed WWW caching proxy

Cited by 32 publications

References 5 publications

HitBand: A Prefetching Model to Increase Hit Rate and Reduce Bandwidth Consumption

HitBand: A Prefetching Model to Increase Hit Rate and Reduce Bandwidth Consumption

CACHERP: A novel dynamic cache size tuning model working with relative object popularity for fast web information retrieval

MMC01-2: A Replica-Conscious Load Balancing Strategy for Large-Scale Multimedia Storage Systems

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