Virtual Machine Power Accounting with Shapley Value
Weixiang Jiang, Fangming Liu, Guoming Tang, Kui Wu and Hai Jin
Huazhong University of Science & Technology, Huazhong University of Science and Technology, University of Victoria, University of Victoria, Huazhong University of Science & Technology

The ever-increasing power consumption of datacenters has eaten up a large portion of their profit. One possible solution is to charge datacenter users for their actual power usage. However, it poses a great technical challenge as the power of VMs co-existing in a physical machine cannot be measured directly. It is thus critical to develop a fair method to disaggregate the power of a physical machine to individual VMs. We tackle the above challenge by modeling the power disaggregation problem as a cooperative game and propose non-deterministic Shapley value to discover the fair power share of VMs (in the sense of satisfying four desired axiomatic principles), while compensating the negative impact of VM power variation. We demonstrate that the results from existing power model-based solution can deviate from the “ground truth” by 25.22% ~ 46.15%. And compared with the exact Shapley value, our non-deterministic Shapley value can achieve less than 5% error for 90% of the time.