A goal-oriented self-tuning caching algorithm

Santhanakrishnan, Ganesh; Amer, Ahmed; Chrysanthis, Panos K.

doi:10.1109/pccc.2004.1395012

Cited by 4 publications

(3 citation statements)

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“…The master algorithm proceeds with a weighted average of the experts' individual predictions. We have shown significant performance improvements utilizing this strategy in caching web documents in our earlier works [24,23]. Since the weights are updated to reflect the quality of an individual experts' likelihood estimates, STEP improves itself via feedback.…”

Section: The Master Algorithmmentioning

confidence: 93%

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Larkby-Lahet

Santhanakrishnan

Amer

et al. 2005

Proceedings of the 6th International Conference on Mobile Data Management

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Data access prediction has been proposed as a mechanism to overcome latency lag, and more recently as a means of conserving energy in mobile systems. We present a fully adaptive predictor, that can optimize itself for any arbitrary workload, while simultaneously offering simple adjustment of goals between energy conservation and latency reduction. Our algorithm, STEP, achieves power savings on mobile computers by eliminating more data fetches, which would otherwise have caused excess energy to be consumed in accessing local storage devices or using the wireless interface to fetch remote data. We have demonstrated our algorithm to perform as well as some of the best access predictors, while incurring almost none of the associated increase in I/O workloads typical of their use. Our algorithm reduced average response times by approximately 50% compared to an LRU cache, while requiring less than half the I/O operations that traditional predictors would require to achieve the same performance, thereby incurring no energy penalty.

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Section: The Master Algorithmmentioning

confidence: 93%

Step

Larkby-Lahet

Santhanakrishnan

Amer

et al. 2005

Proceedings of the 6th International Conference on Mobile Data Management

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“…The algorithm, used in the designed system, is implemented by keeping track of both frequently used and recently used cached items in conjunction with the recent eviction history. (Santhanakrishnan, Amer, Chrysanthis and Li 2004).…”

Section: Eviction Processmentioning

confidence: 99%

An Open Source Software Based Library Catalogue System Using Soundexing Retrieval and Query Caching

Pan¹,

Zhang

Huang

2010

Proceedings of the 12th International Conference on Enterprise Information Systems

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It has been a challenge to apply effective knowledge management tools in information systems for modern libraries that deliver the most up-to-date, relevant information to end users in a quick, efficient, and userfriendly manner. In this paper, the authors present the design of a library catalogue system using principally open source software. The integrated web-based library system takes client/server architecture with multiple tiers. For performance enhancement with respect to error tolerance, searching speed and scalability, techniques of soundexing retrieval and query caching were applied. With the support of an appropriately designed soundex algorithm, the catalogue system can largely increase its recall while not compromising the search precision. On the other side, the introduced query cache speeds up the system response significantly.

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“…GDS incorporates the object size in the cost function and uses an inflation value L , which is initially set to H min . Once a cached object is referenced, its H value is reset to its initial value plus L. Other variants of GreedyDual algorithms are the Popularity GreedyDualSize (PGDS) [12], the GreedyDual* (GD*) [13], and the GD Goal-Oriented Self-Tuning Caching (GD-GhOST) [14]. PGDS extends GDS by incorporating the popularity profile of objects in H value.…”

Section: Related Workmentioning

confidence: 99%

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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A goal-oriented self-tuning caching algorithm

Cited by 4 publications

References 1 publication

Step

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An Open Source Software Based Library Catalogue System Using Soundexing Retrieval and Query Caching

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

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