Queueing Petri nets are a powerful formalism that can be exploited for modeling distributed systems and analyzing their performance and scalability. By combining the modeling power and expressiveness of queueing networks and stochastic Petri nets, queueing Petri nets provide a number of advantages. In this paper, we present our tool QPME (Queueing Petri net Modeling Environment) for modeling an...

Fair queueing is a well-studied problem in modern computer networks. There are two classes of queueing algorithms. One focuses on bounded delay and good fairness properties. The other focuses on the performance of the scheduling algorithm itself. However in embedded networks working under real time constraints, equally important is the deadline imposed by the application. Modern queueing algori...

Large networks of queueing systems model important real-world systems such as MapReduce clusters, web-servers, hospitals, call-centers and airport passenger terminals. To model such systems accurately we must infer queueing parameters from data. Unfortunately, for many queueing networks there is no clear way to proceed with parameter inference from data. Approximate Bayesian computation could o...

Distributed fair queueing in shared-medium ad hoc wireless networks is non-trivial because of the unique design challenges in such networks, such as location-dependent contention, distributed nature of ad hoc fair queueing, channel spatial reuse, and scalability in the presence of node mobility. In this paper, we seek to devise new distributed, localized, scalable and efficient solutions to thi...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy STOCHASTIC OPTIMIZATION AND ITS APPLICATION TO COMMUNICATION NETWORKS AND THE SMART GRID By Zongrui Ding August 2012 Chair: Dapeng Wu Major: Electrical and Computer Engineering The scheduling of some practical systems is highly affected ...

We obtain equivalencies between closed queueing networks with blocking with respect to buffer capacities and the number of customers in the network. These results can be used in approximations, in the buffer allocation problem as well as to explain the behavior of closed queueing networks with finite buffers. We also present exact efficient solutions for special cases.

This paper gives an overview of those aspects of simulation methodology that are (to some extent) peculiar to the simulation of queueing systems. A generalized semi-Markov process framework for describing queueing systems is used through much of the paper. The main topics covered are: output analysis for simulation of transient and steady-state quantities, variance reduction methods that exploi...