Strategy for Selecting Replica Server Spots on the Basis of Demand Fluctuations
Strategy for Selecting Replica Server Spots on the Basis of Demand Fluctuations
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DOI：
10.2197/ipsjtrans.1.28
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
M. Asahara;Akio Shimada;H. Yamada;K. Kono
中科院分区：
文献类型：
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作者：
M. Asahara;Akio Shimada;H. Yamada;K. Kono
许多服务提供商通过互联网分发各种内容。他们通常使用复制服务器来提供稳定的服务。为了适当地定位它们，服务提供商必须预测对其服务的需求，并提供足以满足需求的计算能力。不幸的是，预测需求是困难的，因为对服务的需求通常是波动的。我们的研究小组正在开发ExaPeer，这是一种基础设施，它将计算能力分配给在互联网上数百或数千台可信机器上运行的服务。ExaPeer将计算能力分配给运行在ExaPeer之上的服务。在本文中，我们描述了ExaPeer的方法来动态选择候选点的副本服务器。这种方法称为EPSS（ExaPeer Server Selection，ExaPeer服务器选择），它检测需求的波动，并动态选择应放置副本服务器的候选点，以最好地满足需求。即使对服务的需求在短期内急剧增加，EPSS也会快速响应，并快速选择许多候选副本服务器。为了处理短期波动，EPSS被设计成轻量级的;每台机器独立于其他机器决定是否成为候选点。实验结果表明，即使在需求规模快速变化的情况下，EPSS选择的候选点也比传统的方法选择的候选点更有效。对于90%的客户端访问，使用EPSS的往返时间（RTT）比随机选择的机器少23%，即使机器的数量是EPSS的6.7倍。
Many service providers distribute various kinds of content over the Internet. They often use replica servers to provide a stable service. To position them appropriately, service providers must predict the demands for their services and provide a computing capacity sufficient for servicing the demands. Unfortunately, predicting demands is difficult because the demand for a service usually fluctuates. Our research group is developing ExaPeer, an infrastructure that apportions computing capacity to services running on hundreds or thousands of trusted machines all over the Internet. ExaPeer allocates computing capacity to the services running on top of ExaPeer. In this paper, we describe ExaPeer's approach to dynamically select candidate spots for replica servers. This approach, called EPSS (ExaPeer Server Selection), detects fluctuations in the demand and dynamically selects candidate spots on which replica servers should be placed to best meet the demand. Even if the demand on a service increases dramatically within a short term, EPSS quickly responds to the situation and rapidly selects many candidates for replica servers. To deal with short-term fluctuations, EPSS is designed to be lightweight; each machine determines whether to be a candidate spot independently of others. Experimental results demonstrate that the candidate spots selected by EPSS work better than those selected by heuristics even if the scale of the demand changes rapidly. For 90% of all client accesses, the round-trip-times (RTTs) with EPSS were 23% less than those with randomly selected machines even if the number of machines is 6.7 times larger than EPSS.