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Improving Queuing System Throughput Using Distributed Mean Value Analysis to Control Network Congestion

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http://www.scirp.org/journal/PaperInformation.aspx?PaperID=53719#.VNByFSzQrzE

ABSTRACT
In this paper, we have used the distributed mean value analysis (DMVA) technique with the help of random observe property (ROP) and palm probabilities to improve the network queuing system throughput. In such networks, where finding the complete communication path from source to destination, especially when these nodes are not in the same region while sending data between two nodes. So, an algorithm is developed for single and multi-server centers which give more interesting and successful results. The network is designed by a closed queuing network model and we will use mean value analysis to determine the network throughput (b) for its different values. For certain chosen values of parameters involved in this model, we found that the maximum network throughput for <span "=""><span "="">β≥0.7 remains consistent in a single server case, while in multi-server case for β≥ 0.5 throughput surpass the Marko chain queuing system.
 
Cite this paper
Shahzad, F. , Mushtaq, M. , Ullah, S. , Siddique, M. , Khurram, S. and Saher, N. (2015) Improving Queuing System Throughput Using Distributed Mean Value Analysis to Control Network Congestion. Communications and Network, 7, 21-29. doi: 10.4236/cn.2015.71003.
 
References
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[2]Zhao, W., Ammar, M. and Zegura, E. (2005) Controlling the Mobility of Multiple Data Transport Ferries in a Delay-Tolerant Network. INFOCOM, 1407-1418.
 
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[4]Kawanishi, K. (2005) On the Counting Process for a Class of Markovian Arrival Processes with an Application to a Queueing System. Queueing Systems, 49, 93-122.
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[10]Knadler Jr., C.E. (1991) The Robustness of Separable Queueing Network Models. In: Nelson, B.L., David Kelton, W. and Clark, G.M., Eds., Proceedings of the 1991 Winter Simulation Conference, 661-665.     eww150203lx
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