Quantitative Examination of Internet Traffic Dynamics at Ghana Communication Technology University | Chapter 5 | Research Updates in Mathematics and Computer Science Vol. 7

We seek to unearth which distribution best describes traffic behaviour to help solve the problem of congestion on campus from a mathematical point of view. Telecommunications traffic engineering (i.e. Tele -traffic engineering) is the application of traffic engineering theory to telecommunications. Tele-traffic engineers use their cognition of statistics including queuing theory, the nature of traffic, their practical fashion model, and their mensuration and computer simulation to make predictions and to program telecommunication networks such as a telephone network or the Internet. Internet traffic is a flow of data across the internet. This flow exhibits certain behaviour in accordance with a Probability distribution.  Statistical analysis was performed to understand the characteristics of the traffic population. The empirical cumulative distribution process (CDF) together with essential statistical parameters were benchmarked. The goodness of Fit (GOF) test using the Anderson-Darling (AD) estimation method was applied to establish the best probability distribution model which describes the situation alongside with Probability plot. Deep-down opinion or analysis hints that if the period of time (or space) of grouping is increased well enough, the degree of data relationships will eventually become unimportant by scaling. The N-Flow traffic model was used to determine the burstiness of internet traffic in finite sessions. The Empirical and Theoretical CDF graph was used to determine the discrepancies between them. In the end, it was discovered that the data best fit normal distribution. From experimental and theoretical analysis, it is clear that the internet traffic behaviour in Ghana Technology University College is normally distributed.

 

 

Author(s) Details

Emmanuel Kwame Mensah

Department of Computer and Telecommunication Engineering, Faculty of Engineering, Ghana Communication Technology, PMB 100 Accra-North, Ghana.

 

Please see the book here:- https://doi.org/10.9734/bpi/rumcs/v7/2039G

 

Analyzing Traffic Share Loss in Competitive Internet Networks Using a Markov Chain Model | Chapter 4 | Mathematics and Computer Science: Contemporary Developments Vol. 10

In today's digital era, the internet has become an essential tool for information access and data communication, with a rapidly expanding user base globally. Concurrently, the proliferation of commercial Internet Service Providers (ISPs) has intensified competition and led to an increased load on network infrastructures. This rising demand has driven networks to operate near capacity, resulting in frequent congestion and a high probability of service blocking. This paper investigates the dynamics of internet traffic distribution in a competitive market environment, focusing on share loss when two ISPs compete across distinct markets with varying service quality. A Markov chain model is employed to perform share loss analysis, with iso-share curves illustrating how traffic share distribution shifts because of network congestion and service quality competition.

Through a comprehensive simulation study, the research reveals that blocking probabilities significantly impact an ISP's ability to retain initial traffic share, highlighting the role of Quality of Service (QoS) in user retention. The Markov chain approach effectively models user behaviors in scenarios where traffic congestion influences the shift in market share, particularly under high network demand conditions. This study underscores the critical importance of efficient traffic management and resource allocation in minimizing service interruptions and maintaining competitive QoS in multi-operator markets. The findings have implications for ISPs seeking to optimize resource distribution and manage network congestion, with a particular focus on enhancing the reliability and performance of internet services.

 

Author (s) Details

 

Virendra Kumar Tiwari|
Lakshmi Narain College of Technology (MCA), Bhopal, India.

 

Ashish Jain
LNCT University, Bhopal, India.

 

Ripusoodan Sharma
Lakshmi Narain College of Technology (MCA), Bhopal, India.

 

Dev Kumar Chouhan
LNCT University, Bhopal, India.

 

Pramod Kumar Saket
Lakshmi Narain College of Technology (MCA), Bhopal, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mcscd/v10/3411  

A Comparative Study of Call-By-Call and Two-Call Traffic Distribution Models in Computer Networks | Chapter 8 | Mathematics and Computer Science: Research Updates Vol. 1

Naldi's Markov chain model offers an analytical framework to understand user behaviors in competitive environments involving two operators, such as Internet Service Providers (ISPs). The model investigates the influence of blocking probability and initial user preferences on traffic distribution between operators. In its original form, the model assumes a "call-by-call" basis, where users switch operators after a failed call attempt, favoring operators with lower blocking probabilities.

This paper extends the model by introducing a "two-call" attempt framework, allowing users to make two consecutive attempts with the same operator before switching. Results show that this modification significantly enhances traffic share for operators, particularly those with higher blocking probabilities, as it reduces immediate traffic loss following a single failure.

A comparative analysis between the call-by-call and two-call models reveals that the latter improves traffic retention, increases connection success rates, and decreases churn. This study underscores the critical impact of blocking probabilities on user behaviors and demonstrates how the two-call model mitigates these challenges to optimize traffic distribution.

The findings highlight the value of user behaviors modelling for network optimization, providing actionable insights for ISPs and operators. By adopting the two-call approach, operators can improve quality of service (QoS), manage congestion effectively, and retain users more successfully in competitive markets.

 

Author (s) Details

 

Virendra Kumar Tiwari
Department of Computer Applications, Lakshmi Narain College of Technology (MCA), Bhopal, M.P. 462022, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mcsru/v1/3863

Quantitative Examination of Internet Traffic Dynamics at Ghana Communication Technology University | Chapter 6 | Research Updates in Mathematics and Computer Science Vol. 7

 

We seek to unearth which distribution best describes traffic behaviour to help solve the problem of congestion on campus from a mathematical point of view. Telecommunications traffic engineering (i.e. Tele -traffic engineering) is the application of traffic engineering theory to telecommunications. Tele-traffic engineers use their cognition of statistics including queuing theory, the nature of traffic, their practical fashion model, and their mensuration and computer simulation to make predictions and to program telecommunication networks such as a telephone network or the Internet. Internet traffic is a flow of data across the internet. This flow exhibits certain behaviour in accordance with a Probability distribution.  Statistical analysis was performed to understand the characteristics of the traffic population. The empirical cumulative distribution process (CDF) together with essential statistical parameters were benchmarked. The goodness of Fit (GOF) test using the Anderson-Darling (AD) estimation method was applied to establish the best probability distribution model which describes the situation alongside with Probability plot. Deep-down opinion or analysis hints that if the period of time (or space) of grouping is increased well enough, the degree of data relationships will eventually become unimportant by scaling. The N-Flow traffic model was used to determine the burstiness of internet traffic in finite sessions. The Empirical and Theoretical CDF graph was used to determine the discrepancies between them. In the end, it was discovered that the data best fit normal distribution. From experimental and theoretical analysis, it is clear that the internet traffic behaviour in Ghana Technology University College is normally distributed.

 

Author(s)details:-

 

Emmanuel Kwame Mensah
Department of Computer and Telecommunication Engineering, Faculty of Engineering, Ghana Communication Technology, PMB 100 Accra-North, Ghana.

 

Please See the book here :-  https://doi.org/10.9734/bpi/rumcs/v7/2039G

A Cyber Crime Analysis of Two Call Dimensional Effects in Internet Traffic | Chapter 1 | Research and Applications Towards Mathematics and Computer Science Vol. 1

 The stuff of computer network users growing with the every importance of time, on account of this huge lead of traffic grows on the expansive area networks. Some consumers have crime classification behavior and have attitudes of convicts like hacking the location, blocking the mail, talking unauthorized users etc. Every internet access provider wants to increase his traffic share and habit, which creates the contest among the providers. When consumers get the relatedness he initiates the crime exercise. In this paper invested the effect of various categories corruption users on the internet traffic giving under the Markov Chain model. There are two groups of users (i) Crime consumers (ii) Noncrime users. Further crime consumers divided into two group Fully-misdemeanor users and Partially Crime consumers. Simulation study is performing to analysis the better dimension of traffic by the consumers.

Author(s) Details:

Virendra Kumar Tiwari,
Department of Computer Applications, Lakshmi Narain College of Technology (MCA), Bhopal (M.P.), India.

D. Shukla,
Department of Mathematics and Statistics, Dr. H.S. Gour University, Sagar (M.P.), India.

Please see the link here: https://stm.bookpi.org/RATMCS-V1/article/view/10684