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Optimizing Virtual Machine Migration in Multi-Clouds

机译:优化多云中的虚拟机迁移

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Cloud computing is susceptible to failures. Allocating Virtual machine (VM) in a reliable fashion is considered as one of the crucial problems in Cloud computing environment. Most researchers choose the optimal VM allocation based on resource utilization and cost minimization. However, to protect the reputation of cloud providers, service reliability should be addressed appropriately. In this paper, we propose a Markov-based failure prediction model to anticipate the failure of Cloud servers. Our model anticipates a deteriorating server state based on historical data. Server reliability prediction is then integrated into a VM re-allocation approach in a Multi-Cloud setting to optimize fault tolerance by maximizing Cloud reliability while reducing communication delay. The optimization problem is solved optimally and heuristically using the Artificial Bee Colony (ABC) algorithm. The results show that our model enhances reliability and minimizes communication delay between the VMs following service migration.
机译:云计算易于失败。以可靠的方式分配虚拟机(VM)被认为是云计算环境中的关键问题之一。大多数研究人员根据资源利用率和成本最小化选择最佳VM分配。但是,为了保护云提供商的声誉,应适当地解决服务可靠性。在本文中,我们提出了基于马尔可夫的失效预测模型,以期望云服务器的失败。我们的模型基于历史数据预测服务器状态恶化。然后,服务器可靠性预测被集成到多云设置中的VM重新分配方法中,以通过最大化云可靠性来优化容错性,同时降低通信延迟。使用人造蜜蜂菌落(ABC)算法在最佳地和启发式解决优化问题。结果表明,我们的模型增强了可靠性并最大限度地减少了服务迁移后VM之间的通信延迟。

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