Dynamic Service Placement in Geographically Distributed Clouds
Dynamic Service Placement in Geographically Distributed Clouds
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DOI：
10.1109/icdcs.2012.74
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发表时间：
2012-06
期刊：
影响因子：
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通讯作者：
Qi Zhang;Quanyan Zhu;M. Zhani;R. Boutaba
中科院分区：
文献类型：
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作者：
Qi Zhang;Quanyan Zhu;M. Zhani;R. Boutaba
大型在线服务提供商越来越依赖地理分布的云基础设施来托管和交付服务。在这种情况下，服务提供商面临的一个关键挑战是确定应该放置服务应用程序的位置，以便在保证关键性能要求（例如响应时间）的同时最小化托管成本。此外，需求模式和基础设施成本的动态性有利于动态解决这一问题。目前，大多数现有的服务放置解决方案要么忽略了动态，要么提供的解决方案不够充分，无法同时实现这两个目标。在本文中，我们提出了一个基于控制和博弈论模型的动态服务放置问题的框架。特别是，我们提出了一种根据需求和资源价格波动随时间动态优化期望目标的解决方案。我们进一步考虑了多个服务提供商以动态方式竞争资源的情况，并证明存在社会最优的纳什均衡解。通过基于现实拓扑、需求和资源价格的模拟，我们证明了我们的解决方案在现实环境中的有效性。
Large-scale online service providers have been increasingly relying on geographically distributed cloud infrastructures for service hosting and delivery. In this context, a key challenge faced by service providers is to determine the locations where service applications should be placed such that the hosting cost is minimized while key performance requirements (e.g. response time) are assured. Furthermore, the dynamic nature of both demand pattern and infrastructure cost favors a dynamic solution to this problem. Currently most of the existing solutions for service placement have either ignored dynamics, or provided inadequate solutions that achieve both objectives at the same time. In this paper, we present a framework for dynamic service placement problems based on control- and game-theoretic models. In particular, we present a solution that optimizes the desired objective dynamically over time according to both demand and resource price fluctuations. We further consider the case where multiple service providers compete for resource in a dynamic manner, and show that there is a Nash equilibrium solution which is socially optimal. Using simulations based on realistic topologies, demand and resource prices, we demonstrate the effectiveness of our solution in realistic settings.