Adaptive WebView Materialization

Alexandros Labrinidis, N. Roussopoulos
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引用次数: 28

Abstract

Dynamic content generation poses huge resource demands on web servers, creating a scalability problem. WebView Materialization, where web pages are cached and constantly refreshed in the background, has been shown to ameliorate the scalability problem without sacrificing data freshness. In this work we present an adaptive online algorithm to select which WebViews to materialize, that realizes the trade-off between Quality of Service and Quality of Data. Our algorithm performs very close to the static, off-line optimal algorithm, and, under rapid workload changes, it outperforms the optimal.
自适应WebView物化
动态内容生成对web服务器提出了巨大的资源需求,造成了可伸缩性问题。WebView物质化,网页被缓存并在后台不断刷新,已经被证明可以在不牺牲数据新鲜度的情况下改善可伸缩性问题。在这项工作中,我们提出了一种自适应在线算法来选择要实现的webview,实现了服务质量和数据质量之间的权衡。我们的算法的性能非常接近静态的离线最优算法,并且在快速工作负载变化下,它的性能优于最优算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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