Presenter: Hongqiang Harry Liu
Co-authors: Xin Wu, Ming Zhang, Lihua Yuan, Roger Wattenhofer, David A. Maltz
Network updates(e.g, switch updates, VM migration) in Data Centers can be painful and lead to possible disruptions, because of transient link load spikes and congestion. The goal of this paper is to do congestion free/low latency network updates to ensure that services are not disrupted. This paper introduces zUpdate, which aims to compute a transition free update plan and executes it in a two-phase commit.
In zUpdate, when an operator wants to perform a DCN update, she will submit
a request containing the update requirements to the update scenario
translator. The latter converts the operator’s request into the formal update constraints. The zUpdate engine takes the update
constraints together with the current network topology, traffic matrix, and flow rules and attempts to produce a lossless transition
plan. The zUpdate plan is formulated as a linear program subject to the constraints of flow conservation and traffic delivery.
Evaluation consists of tests on a testbed of 22-switches using Openflow and compare zUpdate with other solutions (zUpdate-onestep, ECMP-onestep, ECMP-planned). For larger topologies, they use trace driven simulations on a production-level data center topology.
====================Q/A=========================
Q: If the network resources are limited, and the network update is done, how do you handle this situation?
A: In such a situation we can not guarantee a congestion free transition, instead we recommend network operators to do updates in off-peak times.
Q: Can you guarantee you can find a congestion free update, is your LP formulation optimal?
In certain scenarios, we can only guarantee best-effort solution.
A: In such a situation we can not guarantee a congestion free transition, instead we recommend network operators to do updates in off-peak times.
Q: Can you guarantee you can find a congestion free update, is your LP formulation optimal?
In certain scenarios, we can only guarantee best-effort solution.
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