More Peak, Less Differentiation: Towards A Pricing-aware Online Control Framework for Inter-Datacenter Transfers
Wenxin Li, Xiaobo Zhou, Keqiu Li, Heng Qi, Deke Guo · 2017
The emerging deployment of geographically distributed data centers (DCs) incurs a significant amount of data transfers over the Internet. Such transfers are typically charged by Internet Service Providers (ISPs) with the widely adopted q-th percentile charging model. In such charging model, the time slots with top 100-q percent of data transmission do not affect the total transmission cost, and can be viewed as free. This brings the opportunity to optimize the scheduling of inter-DC transfers to minimize the entire transmission cost. However, very little work has been done to exploit those free time slots for scheduling inter-DC transfers. The crux is that existing work either lacks a mechanism to accumulate traffic to free time slots, or inevitably relies on prior knowledge of traffic arrival patterns. In this paper, we attempt to exploit those free time slots by leveraging diverse time-sensitivities among inter-DC transfers, so as to reduce or even minimize the transmission cost. Specifically, we advocate that a simple principle should be followed: more traffic peaks should be scheduled in free time slots, while less traffic differentiation should be maintained among the remaining time slots. To this end, we take advantage of the Lyapunov optimization techniques to design a pricing-aware control framework. This framework efficiently makes online decisions for inter-DC transfers without requiring a prior knowledge of traffic arrivals. To verify our proposed framework, we conduct small-scale testbed implementation. The results show that our framework can realistically reduce the transmission cost by up to 19.38%.