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

DOI: 10.4236/cn.2015.71003   PDF   HTML   XML   5,597 Downloads   6,450 Views   Citations

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 β0.7 remains consistent in a single server case, while in multi-server case for β≥ 0.5 throughput surpass the Marko chain queuing system.

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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.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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