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A branch and price approach for deployment of multi-tier software services in clouds

机译:在云中部署多层软件服务的分支机构和价格方法

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This paper considers a service deployment problem that combines service placement and replication level decisions in a cloud computing context The services are composed of multiple components that are to be placed on nodes in the private cloud of the service provider or, if the private cloud has limited capacity, partly in a public cloud. In the service delivery, the provider has to take into account the quality of service guarantees offered to his end-users. To solve the problem, we develop a branch and price algorithm, where the subproblems both are formulated as a linear mixed integer program and a shortest path problem with resource constraints (SPPRC) on a network with a special structure. The SPPRC can be solved by an exact label-setting algorithm, but to speed up the solution process, we develop a heuristic label-setting algorithm based on a reduced network and simplified dominance rule. Our results show that using the heuristic subproblem solver is efficient Furthermore, the branch and price algorithm performs better than a previously developed pre-generation algorithm for the same problem. In addition, we analyze and discuss the differences in solutions that utilize resources in a public cloud to different degrees. By conducting this analysis we are able to identify some essential characteristics of good solutions. (C) 2016 Elsevier Ltd. All rights reserved.
机译:本文考虑了在云计算上下文中结合了服务放置和复制级别决策的服务部署问题。服务由多个组件组成,这些组件将放置在服务提供商的私有云中的节点上,或者如果私有云有限,能力,部分是在公共云中。在服务交付中,提供商必须考虑向其最终用户提供的服务质量保证。为了解决该问题,我们开发了一种分支和价格算法,其中子问题都被表示为线性混合整数程序,并且在具有特殊结构的网络上具有资源约束(SPPRC)的最短路径问题。 SPPRC可以通过精确的标签设置算法来解决,但是为了加快求解速度,我们开发了一种基于简化网络和简化的优势规则的启发式标签设置算法。我们的结果表明,使用启发式子问题求解器是有效的。此外,对于相同的问题,分支和价格算法的性能要优于先前开发的预生成算法。此外,我们分析和讨论了在不同程度上利用公共云中资源的解决方案的差异。通过进行分析,我们可以确定好的解决方案的一些基本特征。 (C)2016 Elsevier Ltd.保留所有权利。

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