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Share Loss Analysis of Internet Traffic Distribution in Computer Networks
Diwakar Shukla, Virendra kumar Tiwari, Sanjay Thakur, Arvind Kumar Deshmukh
Pages - 414 - 426     |    Revised - 16-09-2009     |    Published - 16-10-2009
Volume - 3   Issue - 5    |    Publication Date - November 2009  Table of Contents
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KEYWORDS
Markov chain model, Call-by-call basis, Internet service providers [op, Quality of service (QoS), Transition probability matrix, Transition probability, Blocking probability
ABSTRACT
In present days, the Internet is one of the most required tools of getting information and communicating data. A large number of users through out the world are joining the family of internet in huge proportion. At the same time commercial groups of Internet service provider are also growing in the market. Networks are being overloaded in terms of their capacity and probability of blocking being high day-by-day. This paper presents a share loss analysis of internet traffic when two operators are in competition in respect of quality of service in two markets. The analysis is performed by drawing Iso-share curves through a Markov chain model. The effected over initial traffic share (when final fixed) is examined through simulation study. It is found that network blocking probability highly affects to the initial share amount of traffic of a network operator.
CITED BY (22)  
1 Verma, K., Shukla, D., & Gangele, S. (2015). Approximating the Probability of Traffic Sharing by Numerical Analysis Techniques between Two Operators in a Computer Network. Open Journal of Computer Science and Information Technology, 3(1), 026-039.
2 Shukla, D., & Verma, K. (2014). Bounded Area Estimation Using Simpson 3/8 Rule in Traffic Sharing Scenario in Computer Network.
3 Gangele, S., Verma, K., & Shukla, D. (2014). Bounded Area Estimation of Internet Traffic Share Curve. International Journal of Computer Science and Business Informatics (IJCSBI), 10(1), 54-67.
4 Shukla, D., Verma, K., & Gangele, S. (2012). Iso-Failure in Web Browsing using Markov chain model and curve fitting analysis. International journal of modern engineering research (IJMER), 2(02), 512-517.
5 Shukla, D., Verma, K., & Gangele, S. (2012). Curve Fitting Approximation In Internet Traffic Distribution In Computer Network In Two Market Environment. International Journal of Computer Science and Information Security, 10(4), 71.
6 Shukla, D., Verma, K., & Gangele, S. (2012). Least square curve fitting applications under rest state environment in internet traffic sharing in computer network. International Journal of Computer Science and Telecommunications (IJCST), 3(05), 43-51.
7 Shukla, D., Gangele, S., Verma, K., & Trivedi, M. (2011). Two call based cyber-crime elasticity analysis of Internet traffic sharing in computer network. International Journal of Computer Application (IJCA), 2(1), 27-38.
8 Shukla, D. (2011). elasticity of internet traffic distribution in computer network in two market environment. Journal of Global Research in Computer Science, 2(6), 6-12.
9 Shukla, D., Gangele, S., Singhai, R., & Verma, K. (2011). Elasticity analysis of web-browsing behavior of users. International Journal of Advanced Networking And Application (IJANA), 3(3), 1162-1168.
10 Shukla, D., & Singhai, R. (2011). Analysis of user web browsing behavior using Markov chain model. International Journal of Advanced Networking And Application (IJANA), 2(5), 824-830.
11 Shukla, D., Gangele, S., Verma, K., & Thakur, S. (2011). A Study on Index Based Analysis of Users of Internet Traffic Sharing in Computer Networking. World Applied Programming (WAP), 1(04), 278-287.
12 Shukla, D., Gangele, S., Verma, K., & Trivedi, M. (2011). Elasticity variation under rest state environment in case of Internet traffic sharing in computer network. International Journal of Computer Technology and Application (IJCTA), 2, 2052-2060.
13 Tiwari, V. K., Thakur, S., & Shukla, D. (2011). Analysis of Internet Traffic Distribution for user Behavior based Probability in Two-Market Environment. International Journal of Computer Applications, 30(8).
14 Jain, S., & Ojha, S. (2011). elasticity of internet traffic distribu behaviorial study of single level tree network with the help of markov chain modeltion in computer network in two market environment. Computer Science & Telecommunications, 30(1).
15 D. Shukla, S. Ojha and S. Jain, “Effect of Data Model Approach in State Probability Analysis of Multi-Level Queue Scheduling”, Int. J. of Advanced Networking and Application, 02(01), pp. 419-427, 2010.
16 D. Shukla and A. Jain, “Estimation of Ready Queue Processing Time Under Systematic Lottery Scheduling Scheme”, International Journal of Computer Science and Security (IJCSS), 4(1), pp. 74 – 81, 2010.
17 S. Saxena , A. S. Pandya , R. Stone , S. Rajput and S. Hsu, “Knowledge Discovery Through Data Visualization Of Drive Test Data”, International Journal of Computer Science and Security (IJCSS), 3(6), pp. 559 – 568, 2010.
18 Sanjay, T., & Diwakar, S. (2010). Iso-Share Analysis of Internet Traffic Sharing in the Presence of Favoured Disconnectivity. Computer Science & Telecommunications, 27(4).
19 Shukla, D., & Thakur, S. (2010). Stochastic Analysis of Marketing Strategies in internet Traffic. INTERSTAT (June 2010).
20 Sarma, S. K., Choudhury, S. D., Ahmed, F. U., & Hannan, A. (2010). Efficiency analysis of routing protocols for mobile ad hoc networks for heterogeneity. International Journal of Computer Networks, 2(1), 1-8.
21 Saxena, S., Pandya, A. S., Stone, R., Rajput, S., & Hsu, S. (2010). Knowledge Discovery through Data Visualization of Drive Test Data. International Journal of Computer Science and Security (IJCSS), 3(6), 559.
22 Shukla, D., & Jain, A. (2010). Estimation of Ready Queue Processing Time Under Systematic Lottery Scheduling Scheme.
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Mr. Diwakar Shukla
Deptt. of Mathematics and Statistics, Sagar University, Sagar (M.P.), 470003, INDIA - India
Mr. Virendra kumar Tiwari
Deptt. of Computer Sc. and Applications, Sagar University, Sagar (M.P.), 470003, INDIA - India
virugama@gmail.com
Mr. Sanjay Thakur
- India
Mr. Arvind Kumar Deshmukh
- India