International Journal of Advanced Networking and Applications

Diwakar Shukla ¹, Sharad Gangele ², Rahul Singhai ³, Kapil Verma ⁴

Affiliations
1 Department of Mathematics and Statistics, Sagar University, Sagar-470003, M. P., IN
2 Department of Computer Science, M.P. Bhoj (Open) University, Kolar Road, Bhopal, M. P., IN
3 International Institute of Professional Studies, Devi Ahilya University, Indore, (M.P.), IN
4 Department of Computer Science, M.P. Bhoj (Open) University, Kolar Road, Bhopal, M.P., IN

Abstract

There are many browsers available in the market but only a few are liked and used by many. Every browser has a predefined level of popularity in the market. This paper considers the setup of only two browsers installed in a computer system and a user prefers to any one of them and if fails, switches to the other one. Elasticties of browser sharing are derived, index formation and graphical study are performed to compare the simulated output.

Keywords

Markov Chains (MC), Transition Probability Matrix (TPM), Quality of Service (QOS), Browser Failure (BF).

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Diwakar Shukla ¹, Rahul Singhai ²

Affiliations
1 Department of Mathematics and Statistics, Sagar University, Sagar-470003, M.P., IN
2 International Institute of Professional Studies, D.A.V.V., Indore (M.P.), IN

Abstract

In present days of growing information technology, many browsers available for surfing and web mining. A user has option to use any of them at a time to mine out the desired website. Every browser has pre-defined level of popularity and reputation in the market. This paper considers the setup of only two browsers in a computer system and a user prefers to any one, if fails, switches to the other one. The behavior of user is modeled through Markov chain procedure and transition probabilities are calculated. The quitting to browsing is treated as a parameter of variation over the popularity. Graphical study is performed to explain the inter relationship between user behavior parameters and browser market popularity parameters. If rate of a company is lowest in terms of browser failure and lowest in terms of quitting probability then company enjoys better popularity and larger user proportion.

Keywords

Markov Chains (MC), Transition Probability Matrix (TPM), Quality of Service (QOS), Browser Failure (BF).

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Diwakar Shukla ¹, Shweta Ojha ², Saurabh Jain ²

Affiliations
1 Department of Mathematics and Statistics, Sagar University, Sagar-470003, M.P., IN
2 Department of Computer Science & Applications, Sagar University, Sagar-470003, M.P., IN

Abstract

In the uniprocessor environment, the number of jobs arriving at the processor of CPU at a time is very large which causes a long waiting queue. When conflict arises due to shared resources or overlap of instructions or logical error, the deadlock state appears where further processing of jobs is blocked completely. While the scheduler jumps from one job to another in order to perform the processing the transition mechanism appears. This paper presents a general structure of transition scenario for the functioning of CPU scheduler in the presence of deadlock condition in setup of multilevel queue scheduling. A data model based Markov chain model is proposed to study the transition phenomenon and a general class of scheduling scheme is designed. Some specific and well known schemes are treated as its particular cases and are compared under the setup of model through a proposed deadlock-waiting index measure. Simulation study is performed to evaluate the comparative merits of specific schemes belonging to the class designed with the help of varying values of α and d.

Keywords

Process Scheduling, Markov Chain Model, Data Model, State of System, Rest State, Deadlock State, Process Queue, Multi-Level Queue Scheduling, Transition Probability Matrix, Deadlock Index.

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Diwakar Shukla ¹, Virendra Kumar Tiwari ², Sanjay Thakur ², Mohan Tiwari ³

Affiliations
1 Department of Mathematics and Statistics, Sagar University, Sagar-470003, M.P., IN
2 Department of Computer Science & Applications, Sagar University, Sagar-470003, M.P., IN
3 Department of Physics & Electronics, Sagar University, Sagar-470003, M.P., IN

Abstract

Naldi presented a Markov chain model based analysis for the user’s behaviour in a simple scenario of two competitors. The model is applied to predict influence of both parameters (blocking probability and initial preference) on the traffic distribution between the operators. It is also shown that smaller blocking competitors can be benefited from call-by-call basis assumption. In this paper this criteria of Call-by-call attempt is converted into two call attempts and new mathematical results are derived. A comparative study between call-attempts is made with Naldi expressions. It is found that, by two-call attempt model, the operator gains more traffic than one-call attempt.

Keywords

Blocking Probability, Call-by-call Basis, Internet Service Provider [Operators], Internet Access, Internet Traffic, Markov Chain Model, Network Congestion, Quality of Service (QOS), Transition Probability Matrix, Users Behavior.

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Diwakar Shukla ¹, Sanjay Thakur ², Arvind Kumar Deshmukh ²

Affiliations
1 Department of Mathematics and Statistics, Sagar University, Sagar-470003, M.P., IN
2 Department of Computer Science & Applications, Sagar University, Sagar-470003, M.P., IN

Abstract

The Internet is a popular electronic tool to access information around the world. It is controlled by large group of network operators and local Internet service providers. The user is a last node of this network. Billions of people around the world are in the club of internet users at present. The growing demand beyond capability is causing congestion and blocking in networks. There is a kind of inherent competition among operators in market to catch-up more and more users. This paper presents Markov chain model based study of state probability in Internet traffic sharing assuming there are only two operators in a local market in competition. Their network blocking probabilities are mutually compared and simulation study is performed over varying model parameters. It is found that some specific type of users are affected much by networks blocking probability.

Keywords

Blocking Probability, Call-by-Call Basis, Initial Preference, Internet Service Provider [Operators], Internet Access, Internet Traffic, Morkov Chain Model, Network Congestion, Quality of Service (QoS), Simulation, Transition Probability, Transition Probability Matrix, Users Behavior.

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