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A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem

机译:基于贝叶斯定理的实时虚拟机迁移策略的人工蜂群新方法

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摘要

Green cloud data center has become a research hotspot of virtualized cloud computing architecture. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on the VM placement selection of live migration for power saving. We present a novel heuristic approach which is called PS-ABC. Its algorithm includes two parts. One is that it combines the artificial bee colony (ABC) idea with the uniform random initialization idea, the binary search idea, and Boltzmann selection policy to achieve an improved ABC-based approach with better global exploration's ability and local exploitation's ability. The other one is that it uses the Bayes theorem to further optimize the improved ABC-based process to faster get the final optimal solution. As a result, the whole approach achieves a longer-term efficient optimization for power saving. The experimental results demonstrate that PS-ABC evidently reduces the total incremental power consumption and better protects the performance of VM running and migrating compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.
机译:绿云数据中心已经成为虚拟化云计算架构的研究热点。由于实时虚拟机(VM)迁移技术已在云计算中得到广泛使用和研究,因此我们专注于实时迁移的VM位置选择以节省功耗。我们提出了一种新颖的启发式方法,称为PS-ABC。其算法包括两部分。一种是将人工蜂群(ABC)思想与统一的随机初始化思想,二元搜索思想和Boltzmann选择策略相结合,以实现一种改进的基于ABC的方法,同时具有更好的全球勘探能力和局部开发能力。另一个是它使用贝叶斯定理进一步优化了改进的基于ABC的过程,以更快地获得最终的最优解。结果,整个方法实现了长期有效的节能优化。实验结果表明,与现有研究相比,PS-ABC明显降低了总的增量功耗,并更好地保护了VM运行和迁移的性能。它使实时VM迁移的结果更加高效和有意义。

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