Fundamentals of queueing theory (2nd ed.).
Fundamentals of queueing theory (2nd ed.).
A two-moment approximation for the mean waiting time in the GI/G/s queue
Management Science
Traffic processes in queueing networks: a Markov renewal approach
Traffic processes in queueing networks: a Markov renewal approach
Management Science
Stochastic models in queueing theory
Stochastic models in queueing theory
Commonalities in reengineered business processes: models and issues
Management Science
Exploiting process lifetime distributions for dynamic load balancing
ACM Transactions on Computer Systems (TOCS)
On Pooling in Queueing Networks
Management Science
Partitioning Customers Into Service Groups
Management Science
On choosing a task assignment policy for a distributed server system
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
Task assignment with unknown duration
Journal of the ACM (JACM)
Using quantile estimates in simulating internet queues with Pareto service times
Proceedings of the 33nd conference on Winter simulation
Allocation of service time in a two-server system
Computers and Operations Research
New directions in machine scheduling
New directions in machine scheduling
Introduction to Probability Models, Ninth Edition
Introduction to Probability Models, Ninth Edition
Surprising results on task assignment in server farms with high-variability workloads
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Why segregating short jobs from long jobs under high variability is not always a win
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Optimal allocation of servers and processing time in a load balancing system
Computers and Operations Research
Modeling Security-Check Queues
Management Science
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Reducing congestion is a primary concern in the design and analysis of queueing networks, especially in systems where sources of randomness are characterized by high variability. This paper considers a multiserver first-come, first-served (FCFS) queueing model where we arrange servers in two stations in series. All arrivals join the first service center, where they receive a maximum of T units of service. Arrivals with service requirements that exceed the threshold T join the second queue, where they receive their remaining service. For a variety of heavy tail service time distributions, characterized by large coefficient of variations, analytical and numerical comparisons show that our scheme provides better system performance than the standard parallel multiserver model in the sense of reducing the mean delay per customer in heavy traffic systems. Our model is likely to be useful in systems where high variability is a cause for degradation and where numerous service interruptions are not desired.