Nonstationary Erlang Loss Queues and Networks

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Title: Nonstationary Erlang Loss Queues and Networks
Author: Alnowibet, Khalid Abdulaziz
Advisors: William Stewart, Committee Member
Thomas Reiland, Committee Member
Yannis Viniotis, Committee Member
Harry Perros, Committee Chair
Abstract: The nonstationary Erlang loss model is a queueing system consisting of a finite number of servers and no waiting room with a nonstationary arrival process or a time-dependent service rate. The Erlang loss model is commonly used to model and evaluate many communication systems. Often, these types of service systems encounter a change in the arrival rate over time while the service rate remains either constant or changes very little over time. In view of this, the focus in this research is the nonstationary Erlang loss queues and network with time-dependent arrival rate and constant service rate. We developed an iterative scheme referred to as the fixed point approximation (FPA) in order to obtain the time-dependent blocking probability and other measures for a single-class nonstationary Erlang loss queue and a nonstationary multi-rate Erlang loss queue. The FPA method was compared against exact numerical results, and two other methods, namely, MOL and PSA, for various nonstationary Erlang loss queues with sinusoidal arrival rates. Although we used sinusoidal functions to model the time-dependent arrival rate, the solution can be obtained for any arrival rate function. Experimental results demonstrate that the FPA algorithm provides an exact solution for nonstationary Erlang loss queue. The FPA algorithm was also applied to the case of multi-rate nonstationary Erlang loss queues and the results obtained were compared with simulation. We generalized the FPA algorithm for networks of nonstationary Erlang loss queues with Markovian branching, and compared its accuracy to simulation. Finally, FPA was used to analyze networks of nonstationary Erlang loss queues with population constraints. Numerical results showed that FPA provides a good approximation.
Date: 2004-07-22
Degree: PhD
Discipline: Operations Research
URI: http://www.lib.ncsu.edu/resolver/1840.16/4482


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