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Decentralized Resource Coordination across Service Workflows in a Cloud Environment

机译:云环境中跨服务工作流的分散式资源协调

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As Cloud computing becomes one of the mainstream distributed computing paradigms, cloud users are generating more intricate business processes and scientific jobs which involve the use of service workflows. Efficient management of those workflows' resources can help save cost and improve QoS. In this paper, we investigate the problem of coordinating resources beyond the boundary of a single workflow. An agent-based decentralized algorithm is proposed to match resource supply and demand from different workflows. The proposed algorithm uses multiple phases of information exchange and local adjustments to produce conflict free resource reallocation decisions. Experiments are conducted using simulation programs and synthetic data. Comparisons with a centralized method demonstrate the effectiveness of the proposed algorithm.
机译:随着云计算成为主流的分布式计算范例之一,云用户正在生成涉及服务工作流使用的更复杂的业务流程和科学工作。对这些工作流程资源的有效管理可以帮助节省成本并提高QoS。在本文中,我们调查了超出单个工作流边界的资源协调问题。提出了一种基于Agent的分散算法,以匹配不同工作流的资源供需。所提出的算法使用信息交换和本地调整的多个阶段来产生无冲突的资源重新分配决策。实验是使用模拟程序和综合数据进行的。与集中式方法的比较证明了该算法的有效性。

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