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More Requests, Less Cost: Uncertain Inter-Datacenter Traffic Transmission with Multi-Tier Pricing

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Abstract

With the multi-tier pricing scheme provided by most of the cloud service providers (CSPs), the cloud users typically select a high enough transmission service level to ensure the quality of service (QoS), due to the severe penalty of missing the transmission deadline. This leads to the so-called over-provisioning problem, which increases the transmission cost of the cloud user. Given the fact that cloud users may not be aware of their traffic demand before accessing the network, the over-provisioning problem becomes more serious. In this paper, we investigate how to reduce the transmission cost from the perspective of cloud users, especially when they are not aware of their traffic demand before the transmission deadline. The key idea is to split a long-term transmission request into several short ones. By selecting the most suitable transmission service level for each short-term request, a cost-efficient inter-datacenter transmission service level selection framework is obtained. We further formulate the transmission service level selection problem as a linear programming problem and resolve it in an on-line style with Lyapunov optimization. We evaluate the proposed approach with real traffic data. The experimental results show that our method can reduce the transmission cost by up to 65.04%.

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Authors and Affiliations

  1. Tianjin Key Laboratory of Advanced Networking, College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China

    Xiao-Dong Dong, Sheng Chen, Lai-Ping Zhao, Xiao-Bo Zhou & Ke-Qiu Li

  2. School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, China

    Heng Qi

Authors
  1. Xiao-Dong Dong
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  2. Sheng Chen
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  3. Lai-Ping Zhao
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  4. Xiao-Bo Zhou
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  5. Heng Qi
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  6. Ke-Qiu Li
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Correspondence to Xiao-Bo Zhou.

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Dong, XD., Chen, S., Zhao, LP. et al. More Requests, Less Cost: Uncertain Inter-Datacenter Traffic Transmission with Multi-Tier Pricing. J. Comput. Sci. Technol. 33, 1152–1163 (2018). https://doi.org/10.1007/s11390-018-1878-4

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  • DOI: https://doi.org/10.1007/s11390-018-1878-4

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