Xu Gaochao, Ding Yan, Zhao Jia, Hu Liang, Fu Xiaodong
College of Computer Science and Technology, Jilin University, Changchun, Jilin 130000, China ; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin 130000, China.
ScientificWorldJournal. 2013 Dec 9;2013:369209. doi: 10.1155/2013/369209. eCollection 2013.
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.
绿色云数据中心已成为虚拟化云计算架构的研究热点。由于实时虚拟机（VM）迁移技术在云计算中得到广泛应用和研究，我们专注于为节能而进行的实时迁移的VM放置选择。我们提出了一种新颖的启发式方法，称为PS-ABC。其算法包括两个部分。一是将人工蜂群（ABC）思想与均匀随机初始化思想、二分搜索思想和玻尔兹曼选择策略相结合，以实现一种改进的基于ABC的方法，具有更好的全局探索能力和局部开发能力。另一个是使用贝叶斯定理进一步优化基于ABC的改进过程，以更快地获得最终最优解。结果，整个方法实现了更长期的节能高效优化。实验结果表明，与现有研究相比，PS-ABC明显降低了总增量功耗，并更好地保护了VM运行和迁移的性能。它使实时VM迁移的结果更高效且更有意义。
