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    Felizberta Lo Padilla Tong School of Social SciencesIp Ying To Lee Yu Yee School of Humanities and LanguagesRita Tong Liu School of Business and Hospitality ManagementS.K. Yee School of Health SciencesYam Pak Charitable Foundation School of Computing and Information Sciences
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  4. DST: Leveraging delay-insensitive workload in cloud storage for smart home network
 
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DST: Leveraging delay-insensitive workload in cloud storage for smart home network

Author(s)
Chiu, Dah Ming  
Author(s)
Guo, S.
Chen, L.
Date Issued
2015
Publisher
IEEE
Related Publication(s)
2015 24th International Conference on Computer Communication and Networks (ICCCN) Proceedings
Start page
850
End page
857
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.
URI
https://repository.sfu.edu.hk/handle/sfu/1704
DOI
10.1109/ICCCN.2015.7288401
SFU Affiliated Publication
No
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