QACO:利用web服务器中的部分执行

Jinha Kim, S. Elnikety, Yuxiong He, Seung-won Hwang, Shaolei Ren
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引用次数: 6

摘要

Web服务器向用户提供内容,要求在短的响应时间内提供高质量的响应。满足这些要求是具有挑战性的,特别是在发生负载峰值的情况下。同时,我们观察到,对请求的响应可以根据服务器上当前的资源可用性进行调整或部分执行。例如,在资源竞争的情况下,web服务器可以选择发送低分辨率或中等分辨率的图像,而不是发送原始的高分辨率图像。在本文中,我们利用部分执行来公开资源消耗和服务质量之间的权衡。我们将展示如何管理服务器资源以提高服务质量和响应能力。具体来说,我们开发了一个框架,称为基于配额的控制优化(QACO)。配额表示所有挂起请求可用的资源总量。QACO由两个模块组成:(1)控制模块调整配额以满足响应时间目标。(2)优化模块利用部分执行,以提高总响应质量的方式为待挂请求分配配额。我们使用Apache Web服务器中的系统实现来评估该框架,并使用视频点播服务器的模拟研究。结果表明,在一定的响应时间目标下,QACO比传统的允许或拒绝请求的技术获得了更高的响应质量,而不需要利用部分执行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
QACO: exploiting partial execution in web servers
Web servers provide content to users, with the requirement of providing high response quality within a short response time. Meeting these requirements is challenging, especially in the event of load spikes. Meanwhile, we observe that a response to a request can be adapted or partially executed depending on current resource availability at the server. For example, a web server can choose to send a low or medium resolution image instead of sending the original high resolution image under resource contention. In this paper, we exploit partial execution to expose a trade off between resource consumption and service quality. We show how to manage server resources to improve service quality and responsiveness. Specifically, we develop a framework, called Quota-based Control Optimization (QACO). The quota represents the total amount of resources available for all pending requests. QACO consists of two modules: (1) A control module adjusts the quota to meet the response time target. (2) An optimization module exploits partial execution and allocates the quota to pending requests in a manner that improves total response quality. We evaluate the framework using a system implementation in the Apache Web server, and using a simulation study of a Video-on-Demand server. The results show that under a response time target, QACO achieves a higher response quality than traditional techniques that admit or reject requests without exploiting partial execution.
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