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Regular Paper

CDM: Content Diffusion Model for Information-Centric Networks

Bo Chen1,2Liang Liu1,2( )Hua-Dong Ma1,2
Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing, 100876, China
School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China
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Abstract

This paper proposes the Content Diffusion Model (CDM) for modeling the content diffusion process in information-centric networking (ICN). CDM is inspired by the epidemic model and it provides a method of theoretical quantitative analysis for the content diffusion process in ICN. Specifically, CDM introduces the key functions to formalize the key factors that inuence the content diffusion process, and thus it can construct the model via a simple but efficient way. Further, we derive CDM by using different combinations of those key factors and put them into several typical ICN scenarios, to analyze the characteristics during the diffusion process such as diffusion speed, diffusion scope, average fetching hops, changing and final state, which can greatly help to analyze the network performance and application design. A series of experiments are conducted to evaluate the efficacy and accuracy of CDM. The results show that CDM can accurately illustrate and model the content diffusion process in ICN.

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References

[1]

Ahlgren B, Dannewitz C, Imbrenda C, Kutscher D, Ohlman B. A survey of information-centric networking. IEEE Communications Magazine, 2012, 50(7): 26-36. DOI: 10.1109/MCOM.2012.6231276.

[2]

Dan A, Towsley D. An approximate analysis of the LRU and FIFO buffer replacement schemes. ACM SIGMETRICS Performance Evaluation Review, 1990, 19(1): 143-152. DOI: 10.1145/98460.98525.

[3]
Rosensweig E J, Menasche D S, Kurose J. On the steady-state of cache networks. In Proc. the 2013 IEEE INFOCOM, April 2013, pp.863-871. DOI: 10.1109/INFCOM.2013.6566874.
[4]
Carofiglio G, Gallo M, Muscariello L, Perino D. Modeling data transfer in content-centric networking. In Proc. the 23rd International Teletraffic Congress, Sept. 2011, pp.111-118.
[5]

Zhang G Q, Li Y, Lin T. Caching in information centric networking: A survey. Computer Networks, 2013, 57(16): 3128-3141. DOI: 10.1016/j.comnet.2013.07.007.

[6]
Psaras I, Clegg R G, Landa R, Chai W K, Pavlou G. Modelling and evaluation of CCN-caching trees. In Proc. the 10th International IFIP TC 6 Networking Conference, May 2011, pp.78-91. DOI: 10.1007/978-3-642-20757-0_7.
[7]

Rodriguez P, Spanner C, Biersack E W. Analysis of web caching architectures: Hierarchical and distributed caching. IEEE/ACM Transactions on Networking, 2001, 9(4): 404-418. DOI: 10.1109/90.944339.

[8]

Laoutaris N, Che H, Stavrakakis I. The LCD interconnection of LRU caches and its analysis. Performance Evaluation, 2006, 63(7): 609-634. DOI: 10.1016/j.peva.2005.05.003.

[9]
Laoutaris N, Syntila S, Stavrakakis I. Meta algorithms for hierarchical web caches. In Proc. the 2004 IEEE International Conference on Performance, Computing, and Communications, April 2004, pp.445-452. DOI: 10.1109/PCCC.2004.1395054.
[10]

Kermack W O, McKendrick A G. A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 1927, 115(772): 700-721. DOI: 10.1098/rspa.1927.0118.

[11]
Khelil A, Becker C, Tian J, Rothermel K. An epidemic model for information diffusion in MANETs. In Proc. the 5th ACM International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems, Sept. 2002, pp.54-60. DOI: 10.1145/570758.570768.
[12]
Van Jacobson, Mosko M, Smetters D, Garcia-Luna-Aceves J. Content-centric networking. Whitepaper, Palo Alto Research Center, 2007, pp.2-4. http://bnrg.cs.berkeley.edu/randy/Courses/CS294.S13/14.2b.pdf, Dec. 2019.
[13]
Koponen T, Chawla M, Chun B G, Ermolinskiy A, Kim K H, Shenker S, Stoica I. A data-oriented (and beyond) network architecture. In Proc. the 2007 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, August 2007, pp.181-192. DOI: 10.1145/1282380.1282402.
[14]

Raychaudhuri D, Nagaraja K, Venkataramani A. MobilityFirst: A robust and trustworthy mobility-centric architecture for the future internet. ACM SIGMOBILE Mobile Computing and Communications Review, 2012, 16(3): 2-13. DOI: 10.1145/2412096.2412098.

[15]
Liu L, Ma H, Chen B, Yang W. GlobeSen: An open interconnection frame-work based on named sensory date for IoT. In Proc. the ACM Turing 50th Celebration Conference, May 2017, Article No. 43. DOI: 10.1145/3063955.3063999
[16]

Zhang L X, Afanasyev A, Burke J et al. Named data networking. ACM SIGCOMM Comput. Commun. Rev., 2014, 44(3): 66-73. DOI: 10.1145/2656877.2656887.

[17]
Chen B, Liu L, Wang H, Ma H. On content diffusion modelling in information-centric networks. In Proc. the 2017 IEEE Global Communications Conference, December 2017. DOI: 10.1109/GLOCOM.2017.8254725.
[18]
Tsilopoulos C, Xylomenos G. Supporting diverse traffic types in information centric networks. In Proc. the ACM SIGCOMM Workshop on Information-Centric Networking, August 2011, pp.13-18. DOI: 10.1145/2018584.2018588.
[19]

Chlebus E, Brazier J. Nonstationary Poisson modeling of web browsing session arrivals. Information Processing Letters, 2007, 102(5): 187-190. DOI: 10.1016/j.ipl.2006.12.015.

[20]

Wang B, Sen S, Adler M, Towsley D. Optimal proxy cache allocation for efficient streaming media distribution. IEEE Transactions on Multimedia, 2004, 6(2): 366-374. DOI: 10.1109/TMM.2003.822788.

[21]

Stern T E, Elwalid A I. Analysis of separable Markov-modulated rate models for information-handling systems. Advances in Applied Probability, 1991, 23(1): 105-139. DOI: 10.2307/1427514.

[22]
Kimiyama H, Itoh S. Method of predicting number of on-demand video requests using time series data for video cache system. In Proc. the 6th International Conference on Advances in Mobile Computing and Multimedia, November 2008, pp.200-205. DOI: 10.1145/1497185.1497227.
[23]
Chai W K, He D L, Psaras I, Pavlou G. Cache “less for more” in information-centric networks. In Proc. the 11th International IFIP TC 6 Networking Conference, May 2012, pp.27-40. DOI: 10.1007/978-3-642-30045-5_3.
[24]

Newman M. Power laws, Pareto distributions and Zipf’s law. Contemporary Physics, 2005, 46(5): 323-351. DOI: 10.1080/00107510500052444.

[25]
Wang H Z. The design and implementation of information-centric Internet of Things simulator [Master Thesis]. School of Computer Science, Beijing University of Posts and Telecommunications, 2018.
[26]
Kephart J O, White S R. Directed-graph epidemiological models of computer viruses. In Proc. the 1991 IEEE Computer Society Symposium on Research in Security and Privacy, May 1991, pp.343-359. DOI: 10.1109/RISP.1991.130801.
[27]
Kephart J O, White S R. Measuring and modeling computer virus prevalence. In Proc. the 1993 IEEE Computer Society Symposium on Research in Security and Privacy, May 1993, pp.2-15. DOI: 10.1109/RISP.1993.287647.
[28]

Pastor-Satorras R, Vespignani A. Epidemic dynamics and endemic states in complex networks. Phys. Rev. E, 2001, 63(6): Article No. 066117. DOI: 10.1103/PhysRevE.63.066117.

[29]

Baldoni R, Beraldi R, Piergiovanni S T, Virgillito A. On the modelling of publish/subscribe communication systems. Concurrency and Computation: Practice and Experience, 2005, 17(12): 1471-1495. DOI: 10.1002/cpe.879.

[30]
Rosensweig E J, Kurose J, Towsley D. Approximate models for general cache networks. In Proc. the 2010 IEEE INFOCOM, March 2010, pp.1100-1108. DOI: 10.1109/INFCOM.2010.5461936.
[31]
Jacobson V, Smetters D K, Briggs N H, Plass M F, Stewart P, Thornton J D, Braynard R L. VoCCN: Voice-over content-centric networks. In Proc. the 2009 Workshop on Re-Architecting the Internet, December 2009. DOI: 10.1145/1658978.1658980.
Journal of Computer Science and Technology
Pages 1431-1451
Cite this article:
Chen B, Liu L, Ma H-D. CDM: Content Diffusion Model for Information-Centric Networks. Journal of Computer Science and Technology, 2021, 36(6): 1431-1451. https://doi.org/10.1007/s11390-021-0205-7

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Received: 05 December 2019
Accepted: 07 November 2021
Published: 30 November 2021
© Institute of Computing Technology, Chinese Academy of Sciences 2021
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