The quickhull algorithm for convex hulls
ACM Transactions on Mathematical Software (TOMS)
Queueing Dynamics and Maximal Throughput Scheduling in Switched Processing Systems
Queueing Systems: Theory and Applications
Queueing network simulation analysis: queueing-network stability: simulation-based checking
Proceedings of the 35th conference on Winter simulation: driving innovation
Queueing Networks of Random Link Topology: Stationary Dynamics of Maximal Throughput Schedules
Queueing Systems: Theory and Applications
Queueing analysis of network traffic: methodology and visualization tools
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Long range dependent trafic
Modeling, scheduling, and simulation of switched processing systems
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Achieving 100% throughput in an input-queued switch
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 1
Computational Statistics & Data Analysis
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Switched Processing Systems (SPS) represent canonical models for many communication and computer systems. Over the years, much research has been devoted to developing the best scheduling policies to optimize the various performance metrics of interest. These policies have mostly originated from the well-known MaxWeight discipline, which at any point in time switches the system into the service mode possessing "maximal matching" with the system state (e.g., queue-length, workload, etc.). However, for simplicity it is often assumed that the switching times between service modes are "negligible"--but this proves to be impractical in some applications. In this study, we propose a new scheduling strategy (called the Dynamic Cone Policy) for SPS, which includes substantial service-mode switching times. The goal is to maximize throughput and maintain system stability under fairly mild stochastic assumptions. For practical purposes, an extended scheduling strategy (called the Practical Dynamic Cone Policy) is developed to reduce the computational complexity of the Dynamic Cone Policy and at the same time mitigate job delay. A simulation study shows that the proposed practical policy clearly outperforms another throughput-maximizing policy called BatchAdapt, both in terms of the average and the 95th percentile of job delay for various types of input traffic.