Steady-state simulation of queueing processes: survey of problems and solutions
ACM Computing Surveys (CSUR)
Pattern languages of program design
MANET simulation studies: the incredibles
ACM SIGMOBILE Mobile Computing and Communications Review - Special Issue on Medium Access and Call Admission Control Algorithms for Next Generation Wireless Networks.: The Digital Library version of this issue has a corrected special issue title compared to the one in the print version of the issue.
Twisted Network Programming Essentials
Twisted Network Programming Essentials
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Enhancing the Credibility of Wireless Network Simulations with Experiment Automation
WIMOB '08 Proceedings of the 2008 IEEE International Conference on Wireless & Mobile Computing, Networking & Communication
On the automation of computer network simulators
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
STARS: A Framework for Statistically Rigorous Simulation-Based Network Research
WAINA '11 Proceedings of the 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications
On credibility of simulation studies of telecommunication networks
IEEE Communications Magazine
Proceedings of the Winter Simulation Conference
On reproducibility and traceability of simulations
Proceedings of the Winter Simulation Conference
User interfaces for the simulation automation framework for experiments
Proceedings of the Winter Simulation Conference
SESSL: A domain-specific language for simulation experiments
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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The workflow of a network simulation study requires adherence to best practices in methodology so that results are credible and reproducible by third parties. The opportunities for one to introduce errors start at model description and permeate the process through to the reporting of results. The literature indicates that even publications in respected venues include inadvertent mistakes and poor application of methodology. When experts are liable to fail, it is unreasonable to expect that students would fare any better. This paper presents a system designed to provide guidance for inexperienced users of the popular ns-3 network simulator. SAFE automates the workflow from the initialization of model parameters, to the parallelized execution of experiments, to the processing and persistent storage of output data, and to graphical visualization of results. We discuss the architecture and the implementation of the system in the context of similar contributions in the literature.