| Summary: | 碩士 === 國立交通大學 === 電機資訊國際學程 === 105 === Despite being industry standard, load balancing via virtual machine migration methods in modern cloud data centers still exhibit two major performance issues it has on applications: resulting system load balancing degree and total time till balanced state. Over the years research has been conducted to improve these metrics. Yet due to the fact that these issues influence each other, it has been a challenge to achieve substantial advancement in both metrics simultaneously. In this work we study the problem of VM load balancing considering effects mentioned issues have on the applications performance. We formulate this problem as a variation of multi-commodity minimum cost flow problem and show how both resulting degree of imbalance and a total migration time can be optimized together. Because such problem is NP-hard and is not realistic to solve in polynomial time for application in real data centers, we also propose a heuristic method based on Ant Colony Optimization family of algorithms. Through simulation results, we show that our heuristic gives good performance results compared to optimal solutions given by mixed integer programming formulation of minimum cost flow problem. Furthermore, we compare our method results with results from several major related works. Due to the fact that none of the related works directly focus on load balancing with consideration of both main metrics at the same time, additional reasoning on how the results of these works can be compared has been provided. The outcome of experiments show that our method achieves on average twice faster migration time compared to existing methods proposed in related works.
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