Article information

2018 , Volume 23, ¹ 3, p.81-91

Pristavka P.A., Ryabko B.Y.

An analytic method of efficiency estimation of multimedia content distribution networks

Purpose. Development and investigation of the method for analytical estimation for the efficiency of data transmission networks basing on the details of the supposed network parameters. This method allow us to evaluate a priori comprehensive estimation of efficiency of the network being designed without the necessity of collecting and analyzing real world network operational data.

Methodology. A set of files to be downloaded by the network node is considered as a subsequence of letters generated by stationary and ergodic process. Basing on the fundamentals of Information theory the entropy efficiency was defined to characterize a capacity of data transmission network. Informally, the value actually indicates the growth rate of the amount of files that can be transmitted via the network depending on a certain unit of time. To model the distribution of the probability of access to files, Zipf’s law was used.

Findings. A general description of a method for efficiency estimation of data transmission networks was presented in the paper. Detailed guidelines to apply the method to the estimation of multimedia content delivery networks and file sharing P2P networks, i.e. systems of two wide spread classes, were shown. The method was also investigated on the software models of the systems to show the possibility of using the method as a tool for optimal selection of network parameters.

Originality/value. The suggested information-theoretic method is aimed to analytically estimate the efficiency of the data transmission networks. It can be used as a strong tool to construct both new multimedia data transmission systems and optimization of the existing services.

[full text]
Keywords: content delivery networks, CDN, peer-to-peer, efficiency estimation, entropy efficiency, information theory

doi: 10.25743/ICT.2018.3.16007

Author(s):
Pristavka Pavel Anatolyevich
Office: Siberian State University of Telecommunications and Computer Sciences
Address: 630120, Russia, Novosibirsk
E-mail: ppa.official@gmail.com

Ryabko Boris Yakovlevich
Dr. , Professor
Position: Head of Laboratory
Office: Federal Research Center for Information and Computational Technologies, Novosibirsk State University
Address: 630090, Russia, Novosibirsk, Academician M.A. Lavrentiev avenue, 6
Phone Office: (383) 334-91-24
E-mail: boris@ryabko.net
SPIN-code: 5580-5794

References:
[1] The Zettabyte Era — Trends and Analysis – Cisco. Available at: http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networkingindex-vni/vni-hyperconnectivity-wp.html (accessed: 11.04.2017)

[2] Internet growth statistics. Available at: http://www.internetworldstats.com/emarketing.htm (accessed: 11.04.2017)

[3] Application Usage & Threat Report. Available at: http://researchcenter.paloaltonetworks.com/appusage-risk-report-visualization/ (accessed: 11.04.2017)

[4] Triukose, S., Wen, Z., Rabinovich, M. Measuring a commercial content delivery network. Proceedings of the 20th international conference on World wide web. ACM. 2011:467-476.

[5] Qiu, D., Srikant, R. Modeling and performance analysis of BitTorrent-like peer-to-peer networks. Computer Communication Review. 2004; 34(4):367-377.

[6] Veglia, P., Rossi, D. Performance evaluation of P2P-TV diffusion algorithms under realistic settings. Peer-to-Peer Networking and Applications. 2013; 6(1):26-45.

[7] Ryabko, B. An information-theoretic approach to estimate the capacity of processing units. Performance Evaluation. 2012; (69):267–273.

[8] Ryabko, B. Using Information theory to study the efficiency and capacity of caching in the computer networks. Available at: https://arxiv.org/pdf/1310.3482.pdf (accessed: 12.04.2017).

[9] Cover, T.M., Thomas J.A. Elements of information theory. Wiley; 2006: 792.

[10] Kechedzhy, K. E., Usatenko, O. V., Yampol’skii, V.A. Rank distributions of words in additive many-step Markov chains and the Zipf law. Available at: https://arxiv.org/pdf/physics/0406099.pdf (accessed: 12.04.2017).

[11] Gupta, M., Kumar, D. State-of-the-art of Content Delivery Network. International Journal of Computer Science and Information Technologies. 2014; 5(4):5441-5446.

[12] Gustavson, F. G. Cache blocking. Applied Parallel and Scientific Computing. Springer-Verlag Berlin Heidelberg; 2012: 22–32. Available at: https://doi.org/10.1007/978-3-642-28151-8_3.

[13] Ji, M., Caire, G., Molisch A. F. Wireless Device-to-Device Caching Networks: Basic Principles and System Performance. Available at: http://arxiv.org/abs/1305.5216 (accessed: 12.04.2017).

[14] Niesen, U., Shah, D., Wornell, G. Caching in wireless networks. Proc. IEEE Int. Symp. Inf. Theory. 2009: 2111–2115.

[15] Shanmugam, K., Golrezaei, N., Dimakis, A. G., Molisch, A. F., Caire, G. FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers. IEEE Transactions on Information Theory. 2012; 59(12):8402-8413.

[16] Navimipour, N. J., Milani, F. S. A comprehensive study of the resource discovery techniques in Peer-to-Peer networks. Peer-to-Peer Networking and Applications. 2015; 8(3):474-492.

[17] Androutsellis-Theotokis, S., Spinellis, D. A survey of peer-to-peer content distribution technologies. ACM Computing Surveys (CSUR). 2004; 36(4):335-371.

[18] Witten, I. H., Neal R. M., Cleary, J. G. Arithmetic coding for data compression. Communications of the ACM. 1987; 30(6):520-540.

Bibliography link:
Pristavka P.A., Ryabko B.Y. An analytic method of efficiency estimation of multimedia content distribution networks // Computational technologies. 2018. V. 23. ¹ 3. P. 81-91
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