计算机科学技术学报 ›› 2018,Vol. 33 ›› Issue (6): 1152-1163.doi: 10.1007/s11390-018-1878-4

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多请求,少开销:分层计价模式下的数据中心间不确定流量传输

Xiao-Dong Dong1, Student Member, CCF, Sheng Chen1, Student Member, CCF, Lai-Ping Zhao1, Member, CCF, IEEE, Xiao-Bo Zhou1,*, Member, CCF, IEEE, Heng Qi2, Member, CCF, IEEE Ke-Qiu Li1, Senior Member, CCF, IEEE   

  1. 1. Tianjin Key Laboratory of Advanced Networking, College of Intelligence and Computing, Tianjin University Tianjin 300350, China;
    2. School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
  • 收稿日期:2017-09-13 修回日期:2018-09-23 出版日期:2018-11-15 发布日期:2018-11-15
  • 通讯作者: Xiao-Bo Zhou,E-mail:xiaobo.zhou@tju.edu.cn E-mail:xiaobo.zhou@tju.edu.cn
  • 作者简介:Xiao-Dong Dong received his Bachelor's degree in computer science and technology in 2013 and his Master's degree in computer software and theory in 2016, both from Northwestern Polytechnical University, Xi'an. He is a Ph.D. candidate at the College of Intelligence and Computing, Tianjin University, Tianjin. His research interests include computer network, future Internet and software-defined networking.
  • 基金资助:
    This work is partially supported by the National Key Research and Development Program of China under Grant No. 2016YFB1000205, the State Key Program of National Natural Science Foundation of China under Grant No. 61432002, the National Natural Science Foundation of China-Guangdong Joint Fund under Grant No. U1701263, the National Natural Science Foundation of China under Grant Nos. 61702365, 61672379, and 61772112, the Natural Science Foundation of Tianjin under Grant Nos. 17JCQNJC00700 and 17JCYBJC15500, and the Special Program of Artificial Intelligence of Tianjin Municipal Science and Technology Commission under Grant No. 17ZXRGGX00150.

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

Xiao-Dong Dong1, Student Member, CCF, Sheng Chen1, Student Member, CCF, Lai-Ping Zhao1, Member, CCF, IEEE, Xiao-Bo Zhou1,*, Member, CCF, IEEE, Heng Qi2, Member, CCF, IEEE Ke-Qiu Li1, Senior Member, CCF, IEEE   

  1. 1. Tianjin Key Laboratory of Advanced Networking, College of Intelligence and Computing, Tianjin University Tianjin 300350, China;
    2. School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
  • Received:2017-09-13 Revised:2018-09-23 Online:2018-11-15 Published:2018-11-15
  • Contact: Xiao-Bo Zhou,E-mail:xiaobo.zhou@tju.edu.cn E-mail:xiaobo.zhou@tju.edu.cn
  • About author:Xiao-Dong Dong received his Bachelor's degree in computer science and technology in 2013 and his Master's degree in computer software and theory in 2016, both from Northwestern Polytechnical University, Xi'an. He is a Ph.D. candidate at the College of Intelligence and Computing, Tianjin University, Tianjin. His research interests include computer network, future Internet and software-defined networking.
  • Supported by:
    This work is partially supported by the National Key Research and Development Program of China under Grant No. 2016YFB1000205, the State Key Program of National Natural Science Foundation of China under Grant No. 61432002, the National Natural Science Foundation of China-Guangdong Joint Fund under Grant No. U1701263, the National Natural Science Foundation of China under Grant Nos. 61702365, 61672379, and 61772112, the Natural Science Foundation of Tianjin under Grant Nos. 17JCQNJC00700 and 17JCYBJC15500, and the Special Program of Artificial Intelligence of Tianjin Municipal Science and Technology Commission under Grant No. 17ZXRGGX00150.

由于云服务提供商通常采用分层计价模式向用户收取数据中心之间数据传输的费用,为了避免传输超时,云用户通常会选择充分高的传输服务等级来保障他们的服务质量。这就引发了所谓的带宽资源"过度占用"的问题,该问题大大增加了云用户的传输成本。考虑到用户往往无法在接入网络运行期业务之前获得其传输的数据量,"过度占用"问题变得愈发严重。在本文中,我们从云用户的角度出发,旨在降低云用户的数据中心之间数据传输的成本,尤其是在用户不能预先知道其传输数据量的情况下。本文的核心思想在于首先将一个长期的传输请求分割为若干个短期请求。然后,针对每一个短期请求,选择最为合适的传输服务等级。最终,建立了一个高效的数据中心间的传输服务等级选择框架。本文将这样的传输服务等级选择问题建模为一个线性规划的问题,并通过李雅普诺夫算法进行在线求解。此外,本文还利用真实的流量数据对此方案进行了评估。实验结果表明文章所提的方法可以最多将传输成本降低65.04%。

关键词: 流量不确定性, 数据中心间数据传输, 分层计价模式

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%.

Key words: traffic uncertainty, inter-datacenter transmission, multi-tier pricing scheme

[1] Anania L, Solomon R. Flat:The minimalist BISDN rate. University of Michigan Library Journal of Electronic Publishing, 1995, 1(2):1-20.
[2] Xu H, Li B. Joint request mapping and response routing for geo-distributed cloud services. In Proc. the 32nd IEEE INFOCOM Conference, April 2013, pp.854-862.
[3] Dai W, Jordan S. ISP service tier design. IEEE/ACM Trans. Networking, 2016, 24(3):1434-1447.
[4] Laoutaris N, Sirivianos M, Yang X, Rodriguez P. Interdatacenter bulk transfers with NetStitcher. In Proc. ACM SIGCOMM 2011 Conference, August 2011, pp.74-85.
[5] Kandula S, Menache I, Schwartz R, Babbula S. Calendaring for wide area networks. In Proc. ACM SIGCOMM 2014 Conference, August 2014, pp.515-526.
[6] Spang B, Sabnis A, Sitaraman R, Towsley D, De-Cleene B. MON:Mission-optimized overlay networks. In Proc. the 36th IEEE INFOCOM Conference, May 2017.
[7] Zhang H, Chen K, Bai W, Han D, Tian C, Wang H, Guan H, Zhang M. Guaranteeing deadlines for inter-data center transfers. IEEE/ACM Trans. Networking, 2017, 25(1):579-595.
[8] Jalaparti V, Bliznets I, Kandula S, Lucier B, Menache I. Dynamic pricing and traffic engineering for timely inter-datacenter transfers. In Proc. ACM SIGCOMM 2016 Conference, August 2016, pp.73-86.
[9] Li W, Zhou X, Li K, Qi H, Guo D. More peak, less differentiation:Towards a pricing-aware online control framework for inter-datacenter transfers. In Proc. the 37th IEEE Int. Conference on Distributed Computing Systems, June 2017, pp.2105-2110.
[10] Golubchik L, Khuller S, Mukherjee K, Yao Y. To send or not to send:Reducing the cost of data transmission. In Proc. the 32nd IEEE INFOCOM Conference 2013, April 2013, pp.2472-2478.
[11] Divakaran D, Gurusamy M. Towards exible guarantees in clouds:Adaptive bandwidth allocation and pricing. IEEE Trans. Parallel Distributed System, 2015, 26(6):1754-1764.
[12] Tang S, Yuan J, Li X. Towards optimal bidding strategy for Amazon EC2 cloud spot instance. In Proc. the 5th IEEE International Conference on Cloud Computing, June 2012, pp.91-98.
[13] Yang S, Kuipers F. Traffic uncertainty models in network planning. IEEE Communications Magazine, 2014, 52(2):172-177.
[14] Aparicio-Pardo R, Pavón-Mariño P, Mukherjee B. Robust upgrade in optical networks under traffic uncertainty. In Proc. the 16th International Conference on Optical Network Design and Modelling, April 2012.
[15] Chen F, Wu C, Hong X, Lu Z, Wang Z, Lin C. Engineering traffic uncertainty in the openflow data plane. In Proc. the 35th IEEE INFOCOM Conference, April 2016.
[16] Mitra D, Wang Q. Stochastic traffic engineering for demand uncertainty and risk-aware network revenue management. IEEE/ACM Trans. Networking, 2005, 13(2):221-233.
[17] Alizadeh M, Yang S, Sharif M, Katti S, McKeown N, Prabhakar B, Shenker S. pFabric:Minimal near-optimal datacenter transport. In Proc. ACM SIGCOMM 2013 Conference, August 2013, pp.435-446.
[18] Bai W, Chen K, Wang H, Chen L, Han D, Tian C. Information-agnostic flow scheduling for commodity data centers. In Proc. the 12th USENIX Symposium on Networked Systems Design and Implementation, May 2015, pp.455-468.
[19] Wang T, Xu H, Liu F. Aemon:Information-agnostic mixflow scheduling in data center networks. In Proc. the 1st Asia-Pacific Workshop on Networking, APNet, August 2017, pp.106-112.
[20] Jin X, Li Y, Wei D, Li S, Gao J, Xu L, Li G, Xu W, Rexford J. Optimizing bulk transfers with software-defined opticalWAN. In Proc. ACM SIGCOMM 2016 Conference, August 2016, pp.87-100.
[21] Noormohammadpour M, Raghavendra C, Rao S. Dcroute:Speeding up inter-datacenter traffic allocation while guaranteeing deadlines. In Proc. the 23rd IEEE International Conference on High Performance Computing, December 2016, pp.82-90.
[22] Lin Y, Shen H, Chen L. Ecoflow:An economical and deadline-driven inter-datacenter video flow scheduling system. In Proc. the 23rd ACM Conference on Multimedia Conference, October 2015, pp.1059-1062.
[23] Hong C, Caesar M, Godfrey B. Finishing flows quickly with preemptive scheduling. In Proc. ACM SIGCOMM 2012 Conference, August 2012, pp.127-138.
[24] Munir A, Baig G, Irteza S, Qazi I, Liu A, Dogar F. Friends, not foes:Synthesizing existing transport strategies for data center networks. In Proc. ACM SIGCOMM 2014 Conference, August 2014, pp.491-502.
[25] Chen L, Chen K, Bai W, Alizadeh M. Scheduling mix-flows in commodity datacenters with Karuna. In Proc. ACM SIGCOMM 2016 Conference, August 2016, pp.174-187.
[26] Valancius V, Lumezanu C, Feamster N, Johari R, Vazirani V. How many tiers?:Pricing in the Internet transit market. In Proc. ACM SIGCOMM 2011 Conference, August 2011, pp.194-205.
[27] Li S, Huang J. Price differentiation for communication networks. IEEE/ACM Trans. Networking, 2014, 22(3):703-716.
[28] Xu H, Li B. Spot transit:Cheaper Internet transit for elastic traffic. IEEE Trans. Services Computing, 2015, 8(5):768-781.
[29] Paxson V, Floyd S. Wide-area traffic:The failure of Poisson modeling. In Proc. ACM SIGCOMM 1994 Conference, September 1994, pp.257-268.
[30] Kopetz H, Ochsenreiter W. Clock synchronization in distributed real-time systems. IEEE Trans. Computers, 1987, 36(8):933-940.
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[1] 张钹; 张铃;. Statistical Heuristic Search[J]. , 1987, 2(1): 1 -11 .
[2] 孟力明; 徐晓飞; 常会友; 陈光熙; 胡铭曾; 李生;. A Tree-Structured Database Machine for Large Relational Database Systems[J]. , 1987, 2(4): 265 -275 .
[3] 林琦; 夏培肃;. The Design and Implementation of a Very Fast Experimental Pipelining Computer[J]. , 1988, 3(1): 1 -6 .
[4] 孙成政; 慈云桂;. A New Method for Describing the AND-OR-Parallel Execution of Logic Programs[J]. , 1988, 3(2): 102 -112 .
[5] 张钹; 张恬; 张建伟; 张铃;. Motion Planning for Robots with Topological Dimension Reduction Method[J]. , 1990, 5(1): 1 -16 .
[6] 薛行; 孙钟秀; 周建强; 徐希豪;. A Message-Based Distributed Kernel for a Full Heterogeneous Environment[J]. , 1990, 5(1): 47 -56 .
[7] 许志明;. Discrete Interpolation Surface[J]. , 1990, 5(4): 329 -332 .
[8] 王鼎兴; 郑纬民; 杜晓黎; 郭毅可;. On the Execution Mechanisms of Parallel Graph Reduction[J]. , 1990, 5(4): 333 -346 .
[9] 周权; 魏道政;. A Complete Critical Path Algorithm for Test Generation of Combinational Circuits[J]. , 1991, 6(1): 74 -82 .
[10] 赵靓海; 刘慎权;. An Environment for Rapid Prototyping of Interactive Systems[J]. , 1991, 6(2): 135 -144 .
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