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Improving Web Prefetching by Making Predictions at Prefetch

机译:通过在预取时进行预测来改进Web预取

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Most of the research attempts to improve Web prefetching techniques have focused on the prediction algorithm with the objective of increasing its precision or, in the best case, to reduce the user''s perceived latency. In contrast, to improve prefetching performance, this work concentrates in the prefetching engine and proposes the Prediction at Prefetch (P@P) technique. This paper explains how a prefetching technique can be extended to include our P@P proposal on real world conditions without changes in the web architecture or HTTP protocol. To show how this proposal can improve prefetching performance an extensive performance evaluation study has been done and the results show that P@P can considerably reduce the user''s perceived latency with no additional cost over the basic prefetch mechanism.
机译:大多数旨在改进Web预取技术的研究都集中在预测算法上,目的是提高预测精度,或者在最佳情况下,减少用户的感知等待时间。相反,为了提高预取性能,这项工作集中在预取引擎上,并提出了预取预测(P @ P)技术。本文解释了如何在不更改Web架构或HTTP协议的情况下将预取技术扩展到包括我们在实际条件下的P @ P建议。为了显示该提议如何改善预取性能,已经进行了广泛的性能评估研究,结果表明P @ P可以大大减少用户的感知延迟,而无需花费比基本预取机制更多的费用。

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