Mean waiting time for a token ring with station dependent overheads
Local area and multiple access networks
Mean waiting time evaluation of packet switches for centrally controlled PB's
Performance Evaluation
Variance effects in cyclic production systems
Management Science
When should a roving server be patient?
Management Science
Queueing analysis of polling models: progress in 1990-1994
Frontiers in queueing
When Does Forced Idle Time Improve Performance in Polling Models?
Management Science
Multiclass Production Systems with Setup Times
Operations Research
Polling models: decomposition of waiting times and effects of switchover and setup times
Polling models: decomposition of waiting times and effects of switchover and setup times
Queueing Systems: Theory and Applications
A state-dependent polling model with k-limited service
Probability in the Engineering and Informational Sciences
Manufacturing & Service Operations Management
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We consider a polling model in which a number of queues are served, in cyclic order, by a single server. Each queue has its own distinct Poisson arrival stream, service time, and switchover time (the server's travel time from that queue to the next) distribution. A setup time is incurred if the polled queue has one or more customers present. This is the polling model with State-Dependent service (the SD model). The SD model is inherently complex; hence, it has often been approximated by the much simpler model with State-Independent service (the SI model) in which the server always sets up for a service at the polled queue, regardless of whether it has customers or not. We provide an exact analysis of the SD model and obtain the probability generating function of the joint queue length distribution at a polling epoch, from which the moments of the waiting times at the various queues are obtained. A number of numerical examples are presented, to reveal conditions under which the SD model could perform worse than the corresponding SI model or, alternately, conditions under which the SD model performs better than a corresponding model in which all setup times are zero. We also present expressions for a variant of the SD model, namely, the SD model with a patient server.