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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. Batching for Smart Home: Leveraging delay-insensitive workload in cloud storage
 
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Batching for Smart Home: Leveraging delay-insensitive workload in cloud storage

Author(s)
Chiu, Dah Ming  
Author(s)
Guo, S.
Chen, L.
Zhang, G.
Date Issued
2015
Publisher
IEEE
Related Publication(s)
2015 7th International Conference on Communication Systems and Networks (COMSNETS) Proceedings
Start page
56
End page
63
Abstract
We study the problem of managing high intra-datacenter traffic in a chunk-based public cloud storage service. The high traffic volume is introduced by aggregating very large files from multiple chunk servers in a single edge server. We measure a commercial cloud storage service system, and observe that peak traffic volume overwhelms the network interface cards (NICs) significantly. In the scenario of delivering content based on Smart Home network, it can be expected the file downloading service could be delay-insensitive. Thus, we propose “Batching Smooth intra-datacenter Traffic” (BST) scheme to reduce the peak load to a specified upper bound by batching and delaying users' requests. We resort to a mathematical model to understand the necessity of batching strategy. To evaluate BST's effects, we implement trace-driven simulations with different scheduling policies. In the commercial cloud storage service system, we show that BST is capable of keeping the upper bound to approximately 75% of the original peak traffic by trading off an average delay of 8 minutes.
URI
https://repository.sfu.edu.hk/handle/sfu/1707
DOI
10.1109/COMSNETS.2015.7098671
SFU Affiliated Publication
No
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