ANN model for multi channel infinite buffer queue under N-policy

Madhu Jain, G.C. Sharma and Ragini Mittal

International Journal of Operational Research, 2015, vol. 24, issue 1, 59-82

Abstract: In the present investigation, a multi channel infinite buffer queue under N-policy has been analysed. The concept of N-policy is taken into consideration according to which the server initiates the service only when N jobs are accumulated in the system. The arriving pattern of the traffic (voice/data packets) to the queues in front of different channels follows the Poisson distribution whereas the service times are exponentially distributed. Matrix geometric method is employed to obtain the queue size distribution at equilibrium. Various performance indices such as blocking probabilities, throughput, average delay, etc,. are obtained. The usefulness of the proposed approach is illustrated by taking a specific example. Neuro fuzzy approach and the numerical procedure to compute various state probabilities and other performance indices are outlined. The sensitivity analysis has also been carried out to facilitate the insights of the controllable parameters for the improvement of real-time system.

Keywords: N-policy; multi-channel queues; queue length; blocking; matrix geometric method; MGM; artificial neural networks; ANNs; infinite buffer queues; fuzzy logic; blocking probabilities; throughput; average delay. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=70862 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:24:y:2015:i:1:p:59-82

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().