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Modeling of miss-probability in content-centric networking

内容中心网络未命中概率建模研究

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Abstract

Content-Centric Networking (CCN), one of the most promising Future Internet architectures, is ahot research topic because of its advantages of content delivery over the Internet. Based on the Least RecentlyUsed (LRU) replacement policy in CCN, the closed-form expression of the miss-probability is first derived byconsidering the sequence of arriving requests under single cache scenario, and then extended to linear andbinary tree topologies. Consequently, the virtual round trip time (VRTT) is determined to be influenced bycache capacity and link bandwidth. The simulation results show that the proposed miss-probability modelaccords with realistic CCN network conditions, being much better than the existing model.

概要

本文建立了内容中心网络数据传输模型, 基于最近使用更新 (LRU) 缓存策略, 推导出线型和二叉树型拓扑结构中各内容在节点的未命中概率解析公式, 并研究了虚拟往返时延与存储和带宽资源之间的关系。本文首次考虑了请求在节点处的两种未命中情形, 即两个请求相同内容的相邻请求之间有大于缓存容量种不同内容请求到达和未命中之后的虚拟往返时延内请求到达。仿真显示本文的模型比现有仅考虑一种未命中情形的模型拥有更好的性能。

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References

  1. Anand A, Muthukrishnan C, Akella A, et al. Redundancy in network traffic: findings and implications. In: Proceedings of the 11th International Joint Conference on Measurement and Modeling of Computer Systems, Seattle, 2009. 37–48

    Google Scholar 

  2. Lee U, Rimac I, Hilt V. Greening the Internet with content-centric networking. In: Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking, Passau, 2010. 179–182

    Chapter  Google Scholar 

  3. Kilper D, Atkinson G, Korotky S, et al. Power trends in communication networks. IEEE J Sel Top Quantum Electron, 2011, 17: 275–284

    Article  Google Scholar 

  4. Jacobson V, Smetters D, Thornton J, et al. Networking named content. In: Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies, Rome, 2009. 1–12

    Chapter  Google Scholar 

  5. Lee U, Rimac I, Kilper D, et al. Toward energy-efficient content dissemination. IEEE Netw Mag, 2011, 25: 14–19

    Google Scholar 

  6. Psaras I, Clegg R, Landa R, et al. Modelling and evaluation of ccn-caching trees. In: Proceedings of the 10th International IFIP TC 6 Conference on Networking, Valencia, 2011. 78–91

    Google Scholar 

  7. Carofiglio G, Gehlen V, Perino D. Experimental evaluation of memory management in content-centric networking. In: Proceedings of the IEEE International Conference on Communications, Kyoto, 2011. 1–6

    Google Scholar 

  8. Carofiglio G, Gehlen V, Perino D. Modeling data transfer in content-centric networking. In: Proceedings of the 23rd International Teletraffic Congress, Anaheim, 2011. 111–118

    Google Scholar 

  9. Wong W, Giraldi M, Magalhaes M, et al. Content routers: fetching data on network path. In: Proceedings of the IEEE International Conference on Communications, Kyoto, 2011. 1–6

    Google Scholar 

  10. Li Z, Simon G. Time-shifted tv in content centric networks: the case for cooperative in-network caching. In: Proceedings of the IEEE International Conference on Communications, Kyoto, 2011. 1–6

    Google Scholar 

  11. Fang C, Yu F R, Huang T, et al. An energy-efficient distributed in-network caching scheme for green content-centric networks. Comput Netw, 2015, 78: 119–129

    Article  Google Scholar 

  12. Xylomenos G, Ververidis C, Siris V, et al. A survey of information-centric networking research. Commun Surv Tuts, 2013, 99: 1–26

    Google Scholar 

  13. Jacobson V. Congestion avoidance and control. SIGCOMM Comput Commun Rev, 1998, 18: 314–329

    Article  Google Scholar 

  14. Jelenkovi´c P R, Kang X. Characterizing the miss sequence of the LRU cache. SIGMETRICS Perform Eval Rev, 2008, 36: 119–121

    Article  Google Scholar 

  15. Tofis Y, Psaras I, Pavlou G. Modeling queuing delays in content-centric networks. UCL Technical Report. 2011

    Google Scholar 

  16. Carofiglio G, Gallo M, Muscariello L, et al. Modeling data transfer in content centric networking (extended version). Research report. 2011

    Google Scholar 

  17. Muscariello L, Carofiglio G, Gallo M. Bandwidth and storage sharing performance in information centric networking. In: Proceedings of the ACM SIGCOMM Workshop on Information-centric Networking, Toronto, 2011. 26–31

    Chapter  Google Scholar 

  18. Jelenkovíc P R. Asymptotic approximation of the move-to-front search cost distribution and least-recently used caching fault probabilities. Ann Appl Probab, 1991, 9: 430–464

    Google Scholar 

  19. Chen L, Jiang Z G, Feng H. Parts-probability-based vehicle detection. Sci China Inf Sci, 2014, 57: 112108

  20. Yi C, Afanasyev A, Moiseenko I, et al. A case for stateful forwarding plane. Technical Report. 2012

    Google Scholar 

  21. Stern T E, Elwalid A I. Analysis of separable Markov-modulated rate models for information-handling systems. Adv Appl Probab, 1991, 23: 105–139

    Article  MATH  MathSciNet  Google Scholar 

  22. Massouli´e L, Roberts J. Bandwidth sharing: objectives and algorithms. In: Proceedings of the 8th Annual Joint Conference of the IEEE Computer and Communications Societies, New York, 1999. 1395–1403

    Google Scholar 

  23. Ahlgren B, Dannewitz C, Imbrenda C, et al. A survey of information-centric networking (draft). Internet draft, Information-centric networking 10492. 2011

    Google Scholar 

  24. Wang G, Huang T, Liu J, et al. Modeling in-network caching and bandwidth sharing performance in information-centric networking. J China Univ Posts Telecommun, 2013, 20: 99–105

    Article  MathSciNet  Google Scholar 

Download references

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Authors and Affiliations

  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Tao Huang, GuoQing Wang, Chao Fang & YunJie Liu

  2. Department of Systems and Computer Engineering, Carleton University, Ottawa ON, K1S 5B6, Canada

    Chao Fang & F. Richard Yu

Authors
  1. Tao Huang
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  2. GuoQing Wang
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  3. Chao Fang
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  4. F. Richard Yu
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  5. YunJie Liu
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Correspondence to Chao Fang.

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Huang, T., Wang, G., Fang, C. et al. Modeling of miss-probability in content-centric networking. Sci. China Inf. Sci. 58, 1–13 (2015). https://doi.org/10.1007/s11432-015-5279-9

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