Open, Closed, and Mixed Networks of Queues with Different Classes of Customers
Journal of the ACM (JACM)
The Operational Analysis of Queueing Network Models
ACM Computing Surveys (CSUR)
Approximate Methods for Analyzing Queueing Network Models of Computing Systems
ACM Computing Surveys (CSUR)
Computational algorithms for closed queueing networks with exponential servers
Communications of the ACM
An exact solution method for the general class of closed separable queueing networks
SIGMETRICS '79 Proceedings of the 1979 ACM SIGMETRICS conference on Simulation, measurement and modeling of computer systems
Survey of analytic queueing network models of computer systems
SIGMETRICS '79 Proceedings of the 1979 ACM SIGMETRICS conference on Simulation, measurement and modeling of computer systems
On the convolution algorithm for separable queuing networks
SIGMETRICS '76 Proceedings of the 1976 ACM SIGMETRICS conference on Computer performance modeling measurement and evaluation
Robustness of queuing network formulas
Journal of the ACM (JACM)
Error bounds for performance prediction in queuing networks
ACM Transactions on Computer Systems (TOCS)
Using regression splines for software performance analysis
Proceedings of the 2nd international workshop on Software and performance
Queueing Network Models for Parallel Processing with Asynchronous Tasks
IEEE Transactions on Computers
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The effect that parameter estimation errors have on performance in closed product form queueing networks is investigated. In particular, the effects of errors in the relative utilization estimates of the servers are analyzed. It is shown that in single class load independent networks, the resulting errors in throughput and utilizations are of approximately the same percentage as the errors in the relative utilization estimates. This result does not hold in networks with load dependent servers or multiple customer classes. The percentage errors in mean queue length depend upon the degree of multiprogramming in the network. Errors in mean queue lengths can become unbounded as the degree of multiprogramming becomes unbounded. Implications of these results to computer system modeling are discussed.