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 cloudbandwidth
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.



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