Cicada: Predictive Guarantees for Cloud Network Bandwidth
Venue
MIT (2014), MIT-CSAIL-TR-2014-004
Publication Year
2014
Authors
Katrina LaCurts, Jeffrey C Mogul, Hari Balakrishnan, Yoshio Turner
BibTeX
Abstract
In cloud-computing systems, network-bandwidth guarantees have been shown to improve
predictability of application performance and cost. Most previous work on
cloud-bandwidth guarantees has assumed that cloud tenants know what bandwidth
guarantees they want. However, application bandwidth demands can be complex and
time-varying, and many tenants might lack sufficient information to request 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 appropriate
bandwidth guarantee to a tenant. The key idea in the prediction algorithm is to
treat a set of previously observed traffic matrices as "experts" and learn online
the best weighted linear combination of these experts to make its prediction. 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.
