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Virtual Machine Placement for Predictable and Time-Constrained Peak Loads

机译:虚拟机放置可预测和受时间限制的峰值负载

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We present an approach to optimal virtual machine placement within datacenters for predicable and time-constrained load peaks. A method for optimal load balancing is developed, based on binary integer programming. For tradeoffs between quality of solution and computation time, we also introduce methods to pre-process the optimization problem before solving it. Upper bound based optimizations are used to reduce the time required to compute a final solution, enabling larger problems to be solved. For further scalability, we also present three approximation algorithms, based on heuristics and/or greedy formulations. The proposed algorithms are evaluated through simulations based on synthetic data sets. The evaluation suggests that our algorithms are feasible, and that these can be combined to achieve desired tradeoffs between quality of solution and execution time.
机译:我们提出了一种可预测的和受时间限制的负载峰值的最佳虚拟机放置在数据中心内的方法。基于二进制整数规划,提出了一种优化负载均衡的方法。为了在解决方案质量和计算时间之间进行权衡,我们还介绍了在解决优化问题之前对其进行预处理的方法。基于上限的优化用于减少计算最终解决方案所需的时间,从而可以解决更大的问题。为了进一步扩展,我们还基于启发式和/或贪婪公式提出了三种近似算法。通过基于合成数据集的仿真对提出的算法进行评估。评估表明我们的算法是可行的,并且可以将这些算法组合在一起以实现解决方案质量和执行时间之间的所需折衷。

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