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首页> 外文会议>IEEE International Conference on Systems, Man, and Cybernetics >An Ant Colony Optimization Approach to Connection-Aware Virtual Machine Placement for Scientific Workflows
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An Ant Colony Optimization Approach to Connection-Aware Virtual Machine Placement for Scientific Workflows

机译：一种蚁群优化方法，以了解科学工作流程的无知虚拟机展示

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摘要

The virtual machine (VM) placement problem with the objective to save energy consumption and improve machine utility has been studied extensively in Cloud computing. However, the connection information among VMs during the execution of scientific workflows is seldom considered in existing studies. Therefore, this paper intends to build a novel connection-aware model for VM placement in scientific workflows. Different from existing studies, as the connection information of VMs is considered following the topology of workflows, not only the CPU capacity and memory capacity but also the transmission bandwidth among machines should be considered. An energy- aware, traffic-aware, connection-aware ant colony optimization (ETCACO) approach is developed. The proposed ETCACO combines Ant Colony Optimization (ACO) with a scheduler, namely greedy placeman. Experiments are performed to compare the proposed model with the traditional approach. It is discovered that by taking the connection information into consideration, the proposed approach can reduce energy consumption by 7%.
机译：虚拟机（VM）放置问题以节省能源消耗，并在云计算中广泛研究了能源消耗和改善机实用程序。然而，在现有研究中，在执行科学工作流程期间的VM之间的连接信息很少考虑在现有研究中。因此，本文打算在科学工作流中建立一个新的连接感知模型，用于VM放置。与现有研究不同，因为在工作流的拓扑上考虑VM的连接信息，不仅应该考虑CPU容量和存储器容量，而且应该考虑机器之间的传输带宽。开发了一种能量感知，流量感知的连接感知蚁群优化（etcaco）方法。建议的etcaco将蚁群优化（ACO）与调度员相结合，即贪婪的Placeman。进行实验以将提出的模型与传统方法进行比较。可以发现，通过考虑连接信息，所提出的方法可以将能量消耗降低7％。

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