Scalable constraint-based virtual data center allocation

摘要

Constraint-based techniques can solve challenging problems arising in highly diverse applications. This paper considers the problem of virtual data center (VDC) allocation, an important, emerging challenge for modern data center operators. To address this problem, we introduce Netsolver, a system for VDC allocation that is based on constraint solving. Netsolver represents a major improvement over existing approaches: it is sound, complete, and scalable, providing support for end-to-end, multi-path bandwidth guarantees across all the layers of hosting infrastructure, from servers to top-of-rack switches to aggregation switches to access routers. Netsolver scales to realistic data center sizes and VDC topologies, typically requiring just seconds to allocate VDCs of 5–15 virtual machines to physical data centers with 1000+ servers, maintaining this efficiency even when the data center is nearly saturated. In many cases, Netsolver can allocate 150%−300% as many total VDCs to the same physical data center as previous methods. Finally, we show how Netsolver can be extended with additional optimization constraints, such as VM affinity and hotspot minimization, demonstrating the flexibility of our approach.