A stochastic model for space-division switches in computer networks

Shukla, Diwakar; Gadewar, Surendra; Pathak, R. K.

doi:10.1016/j.amc.2006.05.215

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…Since, we have suggested an approximate the relationship between parameter P 1 and L 1 like a straight line 11 . The COD lies between 0 to 1.…”

Section: Fitting Straight Linementioning

confidence: 99%

Least Square based Curve Fitting in Internet Access Traffic Sharing in Two Operator Environment

Shukla¹,

Verma²,

Gangele³

2012

IJCA

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In Internet service market, at many places the competition occurs among internet service providers. The network suffers from congestion and users have priority to prefer that network having lowest congestion. During the repeated connecting attempt process the user has to maintain call-by-call effort. In this paper Markov chain model is used to establish a relationship between internet access traffic sharing and blocking probability of the network. The model based relationship has been simplified into the linear relationship. The accuracy of the fitting is examined through coefficient of determination. This process has eased up the multiple parameter based complicated relationship into a much simplified form. An average linear relationship is predicted for handy applications.

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“…Since, we have suggested an approximate the relationship between parameter P 1 and L 1 like a straight line 11 . The COD lies between 0 to 1.…”

Section: Fitting Straight Linementioning

confidence: 99%

Least Square based Curve Fitting in Internet Access Traffic Sharing in Two Operator Environment

Shukla¹,

Verma²,

Gangele³

2012

IJCA

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“…Naldi [13] has opened up the problem of internet traffic sharing evaluation. Shukla, Gadewal [6] have shown the application of Markov Chain model to the modelling of space division switches. Shukla, Pathak and Thakur [7] have predicated useful contribution for modelling of internet traffic sharing phenomena between two operators in competitive markets.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Internet Traffic Distribution for user Behavior based Probability in TwoMarket Environment

Tiwari¹,

Thakur²,

Shukla³

2011

IJCA

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Consider two markets and two operators having different networks operators. Both operators are in competition for capturing more and more the internet traffic. The users have presumptive behaviour like faithful, impatient and completely impatient. This paper presented Markov chain model based analysis of user behaviour for selecting any one operator. It is found that blocking probability of network plays important role for determining the user's behaviour towards choosing an operator as internet service provider. Also it contains analysis of initial share over the blocking probability varying probability of the rest-state.

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“…We suggest an approximate the relationship between parameter P 1 and L 1 through a straight line 11 . …”

Section: Fitting the Straight Linementioning

confidence: 99%

“…Yeian and Lygeres [10] presented a work on stabilization of class of stochastic different equations with Markovian switching. Shukla et al [11] advocated for model based study for space division switches in computer network. Francini and Chiussi [7] discussed some interesting features for QoS guarantees to the unicast and multicast flow in multistage packet switch.…”

Section: A Reviewmentioning

confidence: 99%

Curve Fitting Analysis of Internet Traffic Sharing Management in Computer Network under Cyber Crime

Shukla¹,

Verma²,

Bhagwat³

et al. 2012

IJCA

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Cyber crime is growing fast day-by-day through the spreading of Internet around the world. Many under-developed countries are using dial-up-setup network where a call is connected only after a little extra effort. Some identified cyber crimes are writing abusive letters, giving threats to other, sending unwanted mails, hacking secret data, phishing attack on websites etc. The Internet traffic growth has some positive correlation with the cyber crime as justified by the Markov Chain Model based analysis of authors to examine the interrelationship between traffic sharing and blocking probability. This analysis has been extended for two-call basis also and model based relations are derived. These relations are complicated in terms of mathematical structure. This paper presents least square based curve analysis for Markov Chain model based relationship between traffic sharing and network blocking. The earlier suggested complicated relationship has been simplified in the form of straight line showing a good fitting. The Coefficient of determination has been computed showing the high value towards unity. It proves that simplified linear relationships perform well as a thumb rule for expressing the complex relationship between traffic sharing and network blocking probability. . KeywordsUser behavior, Transition Probability Matrix (TPM), Markov Chain Model (MCM), Coefficient of Determination (COD), Confidence Interval.

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A stochastic model for space-division switches in computer networks

Cited by 5 publications

References 11 publications

Least Square based Curve Fitting in Internet Access Traffic Sharing in Two Operator Environment

Least Square based Curve Fitting in Internet Access Traffic Sharing in Two Operator Environment

Analysis of Internet Traffic Distribution for user Behavior based Probability in TwoMarket Environment

Curve Fitting Analysis of Internet Traffic Sharing Management in Computer Network under Cyber Crime

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