A PROactive Request Distribution (PRORD) Using Web Log Mining in a Cluster-Based Web Server

Behavior studies have been conducted by scientists and philosophers who approach subjects such as star and planet trajectories, society organizations, living beings evolution and human language. With the advent of computer, new challenges have been observed in order to explore and understand the behavior variations of interactions with systems. Motivated by those challenges, this work proposes a new approach to automatically cluster, detect and identify behavior patterns. In order to validate this approach, we have modeled the knowledge embedded in interactions of handwriting signatures. The generated knowledge models were, afterwards, employed to verify signatures. Obtained results were compared to other related approaches presented in SVC2004, the First International Signature Verification Competition.

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“…There are different approaches to group, classify, evaluate and analyze user behavior [6,13,20,21,23,26].…”

Section: Related Workmentioning

confidence: 99%

“…Lee et al [20] proposed PRORD (Proactive Request Distribution), a new load balancing policy for distributed web servers. PRORD estimates future accesses by considering web cache information.…”

Section: Related Workmentioning

confidence: 99%

Variation Detection applied in User Signature Verification

Mello

Santos

Albertini

2011

RITA

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“…Some other algorithms [43,31] use the predictions to preprocess resources at the server side. Schechter et al [43] use session paths to make predictions for generating some dynamic content in advance.…”

Section: Pure Predictorsmentioning

confidence: 99%

“…Schechter et al [43] use session paths to make predictions for generating some dynamic content in advance. In the context of a distributed web server cluster, the proposal of Lee et al [31] combines a prediction algorithm with a workload distribution algorithm to prefetch objects from disk in each web server.…”

Section: Pure Predictorsmentioning

confidence: 99%

A taxonomy of web prediction algorithms

Domènech

Ossa

Sahuquillo

et al. 2012

Expert Systems with Applications

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Web prefetching techniques are an attractive solution to reduce the user-perceived latency. These techniques are driven by a prediction engine or algorithm that guesses following actions of web users. A large amount of prediction algorithms has been proposed since the first prefetching approach was published, although it is only over the last two or three years when they have begun to be successfully implemented in commercial products. These algorithms can be implemented in any element of the web architecture and can use a wide variety of information as input. This affects their structure, data system, computational resources and accuracy. The knowledge of the input information and the understanding of how it can be handled to make predictions can help to improve the design of current prediction engines, and consequently prefetching techniques.This paper analyzes fifty of the most relevant algorithms proposed along 15 years of prefetching research and proposes a taxonomy where the algorithms are classified according to the input data they use. For each group, the main advantages and shortcomings are highlighted.

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Leveraging Web Prefetching Systems with Data Deduplication

Neves

Ferreira

Barreto

2013

2013 IEEE 12th International Symposium on Network Computing and Applications

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Abstract-The continued rise in internet users and the ever-greater complexity of Web content degrade userperceived latency in the Web. Web caching, prefetching and data deduplication are techniques that are used to try to mitigate this effect. Regardless of the amount of bandwidth available for network traffic, Web prefetching has the potential to consume free bandwidth to its limits. Deduplication explores data redundancies to reduce the amount of data transferred through the network, thereby freeing occupied bandwidth. To the best of our knowledge no previous work has been done which applies these two techniques combined to Web traffic. The motivation of this work is to ask if, by combining these two techniques, it is possible to significantly reduce the amount of bytes transmitted per user request, thereby improving the user-perceived latency in the Web. In the present work, we developed and implemented a system that combines the use of Web prefetching and deduplication techniques. By testing our system using real-world user navigation traces, we show that deduplication is able to substantially reduce the network costs of prefetching (up to 34% savings in transferred bytes), without degrading the latency gains due to prefetching. By adjusting deduplication parameters it is possible to improve the latency relative to when using only prefetching.

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A PROactive Request Distribution (PRORD) Using Web Log Mining in a Cluster-Based Web Server

Cited by 3 publications

References 22 publications

Variation Detection applied in User Signature Verification

Variation Detection applied in User Signature Verification

A taxonomy of web prediction algorithms

Leveraging Web Prefetching Systems with Data Deduplication

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