DST: Leveraging Delay-Insensitive Workload in Cloud Storage for Smart Home Network

Abstract

We study the problem of how to manage the high intra-datacenter traffic in a chunk-based public cloud storage service serving primarily smart home devices. The large volume of traffic is introduced by delivering very large content during busy hours in the cloud. Measurement of a commercial cloud service shows that the peak traffic volume (at its edge servers) overwhelms the network interface cards (NICs), resulting in serious congestion and packet losses. Since it can be expected the large content downloading requests in smart home environment could be delay-insensitive, we propose DST to keep the peak load under a specified upper bound, by delaying users' requests when necessary. By modelling DST as a queueing system, we derive the relation between the mean delay and the traffic upper bound. With trace-driven simulations, we evaluate the system performance and validate the analysis results. For the commercial cloud service we study, we show that it is possible to keep the traffic upper bound to about 80% of peak traffic rate by introducing a mean delay of around 48 minutes.