Towards bandwidth guaranteed energy efficient data center networking

The data center network connecting the servers in a data center plays a crucial role in orchestrating the infrastructure to deliver peak performance to users. In order to meet high performance and reliability requirements, the data center network is usually constructed of a massive number of network devices and links to achieve 1:1 oversubscription for peak workload. However, traffic rarely ever hits the peak capacity in practice and the links are underutilized most of the time, which results in an enormous waste of energy. Therefore, aiming to achieve an energy proportional data center network without compromising throughput and fault tolerance too much, in this paper we propose two efficient schemes from the perspective of resource allocation, routing and flow scheduling. We mathematically formulate the energy optimization problem as a multi-commodity minimum cost flow problem, and prove its NP-hardness. Then we propose a heuristic solution with high computational efficiency by applying an AI resource abstraction technique. Additionally, we design a practical topology-based solution with the benefit of Random Packet Spraying consistent with multipath routing protocols. Both simulations and theoretical analysis have been conducted to demonstrate the feasibility and convincing performance of our frameworks.