ACM Transactions on Programming Languages and Systems (TOPLAS)
Distributed discrete-event simulation
ACM Computing Surveys (CSUR)
Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
A performance evaluation methodology for parallel simulation protocols
PADS '96 Proceedings of the tenth workshop on Parallel and distributed simulation
Perils and pitfalls of parallel discrete-event simulation
WSC '96 Proceedings of the 28th conference on Winter simulation
Performance Evaluation of Conservative Algorithms in Parallel Simulation Languages
IEEE Transactions on Parallel and Distributed Systems
SIMULATION OF PACKET COMMUNICATION ARCHITECTURE COMPUTER SYSTEMS
SIMULATION OF PACKET COMMUNICATION ARCHITECTURE COMPUTER SYSTEMS
Foundations of Jini 2 Programming
Foundations of Jini 2 Programming
Scaling time warp-based discrete event execution to 104 processors on a Blue Gene supercomputer
Proceedings of the 4th international conference on Computing frontiers
Distributed Simulation: A Case Study in Design and Verification of Distributed Programs
IEEE Transactions on Software Engineering
A Simulation Framework for Studying Economic Resource Management in Grids
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
A break in the clouds: towards a cloud definition
ACM SIGCOMM Computer Communication Review
Design and performance evaluation of a conservative parallel discrete event core for GES
Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques
A performance comparison of recent network simulators
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Distribution of parallel discrete-event simulations in GES: core design and optimizations
Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques
SP 800-145. The NIST Definition of Cloud Computing
SP 800-145. The NIST Definition of Cloud Computing
Panel on grand challenges for modeling and simulation
Proceedings of the Winter Simulation Conference
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation
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A discrete-event simulator's ability to distribute the execution of a simulation model allows one to deal with the memory limitations of a single computational resource, and thereby increase the scale or level of detail at which models can be studied. In addition, distribution has the potential to reduce the round trip time of a simulation by incorporating multiple computational cores into the simulation's execution. However, such gains can be voided by the overhead that time synchronization protocols introduce. These protocols are required to prevent the occurrence of causality errors during a parallel execution of a simulation. The overhead depends on the protocol, characteristics of the simulation model, and the architecture of the computational resources used. Recently, infrastructure-as-a-service offerings in cloud computing have introduced flexibility in acquiring computational resources on a pay-as-you-go basis. At present, it is unclear to what extent these offerings are suited for the distributed execution of discrete-event simulations, and how the characteristics of different resource types impact the runtime performance of distributed simulations. In this paper we investigate this issue, and assess the performance of different conservative time synchronization protocols on a range of cloud resource types that are currently available on Amazon EC2.