Cicada: Predictive Guarantees for Cloud Network Bandwidth

In cloud-computing systems, network-bandwidth guarantees have been shown to improve predictability of application performance and cost [1, 30]. Most previous work on cloud-bandwidth guarantees has assumed that cloud tenants know what bandwidth guarantees they want. However, applica-tion bandwidth demands can be complex and time-varying, and many tenants might lack sufficient information to re-quest a bandwidth guarantee that is well-matched to their needs. A tenant’s lack of accurate knowledge about its future bandwidth demands can lead to over-provisioning (and thus reduced cost-efficiency) or under-provisioning (and thus poor user experience in latency-sensitive user-facing applications). We analyze traffic traces gathered over six months from an HP Cloud Services datacenter, finding that application bandwidth consumption is both time-varying and spatially inhomogeneous. This variability makes it hard to predict requirements. To solve this problem, we develop a prediction algorithm usable by a cloud provider to suggest an appro-priate bandwidth guarantee to a tenant. The key idea in the prediction algorithm is to treat a set of previously ob-served traffic matrices as “experts ” and learn online the best weighted linear combination of these experts to make its pre-diction. With tenant VM placement using these predictive guarantees, we find that the inter-rack network utilization in certain datacenter topologies can be more than doubled. 1