Recent years witnessed the proliferation of the notion of sparsity and its applications in operations research models. To bring to the attention and raise the interest of the operations research community on this topic, we present in this tutorial a wide range of complex models that admit sparse yet effective solutions. Our examples range from compressed sensing and process flexibility to queui...

We consider a queuing network with M exponential service stations and with N customers. We study the behavior of a subsystem u, which has a single node as input and a single node as output, when the subsystem parameters are varied. An “equivalent” network is constructed in which all queues except those in subsystem u are replaced by a single composite queue. We show that for certain classes of ...

Random Neural Networks (RNNs) are a class of Neural Networks (NNs) that can also be seen as a specific type of queuing network. They have been successfully used in several domains during the last 25 years, as queuing networks to analyze the performance of resource sharing in many engineering areas, as learning tools and in combinatorial optimization, where they are seen as neural systems, and a...

Measurements of communication traffic from a wide variety of sources have suggested that correlations persist in such sources over fairly long time scales. This has called into question the use of traditional traffic models for the performance analysis of such networks, and has sparked an interest in studying novel kinds of traffic models. In particular, a suggestion has been made to build mode...

1 (abstract) We analyze a discrete-time network of queues. The unit element of the network is a 2 2 buuered switch, which we regard as a system of two queues working in parallel. We show how to transform transition probability information from the output of one switch, or network stage, to the input of the next one. This is used to carry out a Markov time series input model to predict mean queu...

The increase of energy consumption and the related costs in large data centers has stimulated new researches on techniques to optimize the power consumption of the servers. In this paper we focus on systems that should process a peak workload consisting of different classes of applications. The objective is to implement a policy of load control which allows an efficient use of the power deploye...

Queuing theory is the formal study of waiting in line and is an entire discipline in operations management. This article will give the reader a general background into queuing theory, its associated terminology, and its relationship to patient satisfaction. Queuing theory has been used in the past to assess such things as staff schedules, working environment, productivity, customer waiting time...

BACKGROUND Allocation of scarce resources presents an increasing challenge to hospital administrators and health policy makers. Intensive care units can present bottlenecks within busy hospitals, but their expansion is costly and difficult to gauge. Although mathematical tools have been suggested for determining the proper number of intensive care beds necessary to serve a given demand, the per...

by simulation is the performance of a probabilistic model of a multiprogrammed single-processor computing system operating under demand paging. Results of experiments on statistical methods .for improving the efJiciency of the simulation are presented. Estimates of the response variables in the simulation are reported for a variety of conditions of system overhead, queuing delays, and transient...