A Minimal Access Cost-Based Multimedia Object Replacement Algorithm

Li, Keqiu; Nanya, Takashi; Qu, Wenyu

doi:10.1109/ipdps.2007.370465

Cited by 4 publications

(4 citation statements)

References 14 publications

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“…Another group of policies surveyed in [23]: GDSF, LRUThreshold, LRU-Min, SIZE, LOG2-SIZE, PSS, LRU-LSC, Partitioned Caching, HYPER-G, CSS, LRU-SP, GD-Size, GD * , TSP, MIX, HYBRID, LNC-R-W3, LUV, HARMONIC, LAT, GDSP, LRU-S, including LNC-R-W3-U [42], SE [43], R-LPV [44], Min-SAUD [45], OPT [46], LPPB-R [47], OA [48], CSP [49], GA-Based Cache Replacement Policy [50], improved GD * [51] and SzLFU(k) [52] consider object sizes in such a way that replacing big objects first, thus neither aiming for cloud scalability nor economy.…”

Section: Object Size Downloading Monetary Cost and Access Frequencymentioning

confidence: 99%

Multi-provider cloud computing network infrastructure optimization

Banditwattanawong

Masdisornchote

Uthayopas

2016

Future Generation Computer Systems

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h i g h l i g h t s• Byte-hit rate and hit rate could be optimal simultaneously in a nonuniform cost model. • i-Cloud outperformed popular LRU, GDSF and LFUDA schemes in a nonuniform cost environment.• i-Cloud's performances were stable and close to those of infinite cache size. • Window size had small performance effect when relative cache sizes were big.• Accounting data-out charge rates improved all performance aspects at small cache sizes. a b s t r a c tCloud-adopting enterprises have been increasingly employing multiple cloud providers concurrently, for example, to consume unique services and to mitigate data lock-in risk. As a consequence, the enterprises must be able to address contrasting quality-of-service degrees offered by the different providers. This paper presents an intelligent cloud cache eviction approach, namely i-Cloud, as the core component of a client-side cloud cache. i-Cloud is capable of reducing public cloud data-out expenses, improving cloud network scalability and lowering cloud service access latencies specifically in multi-provider cloud environments. Trace-driven simulations have shown that i-Cloud outperformed well-known approaches in all performance metrics. In addition, i-Cloud is not only able to achieve optimal performances in all metrics simultaneously but also delivered relatively stable performances across all performance metrics. The results have also indicated that taking the nonuniformity of data-out charge rates into cache eviction decisions improved caching performances in all metrics.

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Section: Object Size Downloading Monetary Cost and Access Frequencymentioning

confidence: 99%

Multi-provider cloud computing network infrastructure optimization

Banditwattanawong

Masdisornchote

Uthayopas

2016

Future Generation Computer Systems

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“…Our idea is different from this by the use of grading parameter worthiness, which incorporates object attributes and traffic parameters to a single factor. The worthiness parameter has advantages over the other parameters such as grade (Bian and Chen 2008), cost (Li et al 2007;Cao and Irani 2002) and popularity (Chen and Zhang 2003;Jin and Bestavros 2000) as it is comprehensive and generic. So, the worthiness parameter can be tuned for a specific form of content distribution (e.g., multimedia caching and object prefetching).…”

Section: The Proposed Content Classification Schemementioning

confidence: 99%

“…The notion of object worthiness is similar to rank (Chen and Zhang 2003;Jin and Bestavros 2000), cost (Li et al 2007;Cao and Irani 2002) and page grade (Bian and Chen 2008) but is different in definition and in the method of computation. The above parameters classify the objects according to cache-ability, popularity, size and cost of fetching and captures these parameters online.…”

Section: Object Worthinessmentioning

confidence: 99%

“…However, it is very difficult to keep track of the history of all these factors simultaneously. Hence most of the existing approaches rely upon some object grading mechanism, like popularity-rank of the object (Chen and Zhang 2003;Jin and Bestavros 2000), cost function for retrieval of an object (Li et al 2007;Cao and Irani 2002) and page grade (Bian and Chen 2008). All these approaches assume some general characteristics to define the grading parameter.…”

Section: Introductionmentioning

confidence: 99%

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A novel content classification scheme for web caches

Sajeev

Sebastian

2010

Evolving Systems

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Web caches are useful in reducing the user perceived latencies and web traffic congestion. Multi-level classification of web objects in caching is relatively an unexplored area. This paper proposes a novel classification scheme for web cache objects which utilizes a multinomial logistic regression (MLR) technique. The MLR model is trained to classify web objects using the information extracted from web logs. We introduce a novel grading parameter worthiness as a key for the object classification. Simulations are carried out with the datasets generated from real world trace files using the classifier in Least Recently Used-Class Based (LRU-C) and Least Recently Used-Multilevel Classes (LRU-M) cache models. Test results confirm that the proposed model has good online learning and prediction capability and suggest that the proposed approach is applicable to adaptive caching.

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From Web Cache to Cloud Cache

Banditwattanawong

2012

Advances in Grid and Pervasive Computing

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A Minimal Access Cost-Based Multimedia Object Replacement Algorithm

Cited by 4 publications

References 14 publications

Multi-provider cloud computing network infrastructure optimization

Multi-provider cloud computing network infrastructure optimization

A novel content classification scheme for web caches

From Web Cache to Cloud Cache

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