Theory of Modeling and Simulation
Theory of Modeling and Simulation
Service-Oriented Architecture: Concepts, Technology, and Design
Service-Oriented Architecture: Concepts, Technology, and Design
Modeling Non-Functional Aspects in Service Oriented Architecture
SCC '06 Proceedings of the IEEE International Conference on Services Computing
QoS-Resource Graph Model for Web Service Composition in Service Oriented Computing
GCC '07 Proceedings of the Sixth International Conference on Grid and Cooperative Computing
Towards Peer-to-Peer Based Distributed Simulations on a Grid Infrastructure
ANSS-41 '08 Proceedings of the 41st Annual Simulation Symposium (anss-41 2008)
Model Driven Development of Context-aware Service Oriented Architecture
CSEWORKSHOPS '08 Proceedings of the 2008 11th IEEE International Conference on Computational Science and Engineering - Workshops
DS-RT '08 Proceedings of the 2008 12th IEEE/ACM International Symposium on Distributed Simulation and Real-Time Applications
DS-RT '08 Proceedings of the 2008 12th IEEE/ACM International Symposium on Distributed Simulation and Real-Time Applications
Model-driven generative techniques for scalable performabality analysis of distributed systems
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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Recent advances in Service Oriented Architecture (SOA) provides many exciting opportunities for developing next-generation of distributed simulation frameworks and tools. At the mean time, Peer-to-Peer (P2P) based network technique also challenges the traditional view of distributed simulations. Indeed, the integration of SOA and P2P techniques can potentially help on developing more flexible, scalable distributed simulation framework. In this paper, we present our design and implementation of a real-time distributed simulation framework based on SOA concept and JXTA P2P technique. Our simulation framework can be effectively used for evaluating most of SOA related algorithms and schema including but not limited to: dynamic service composition, service path selection, load-balancing algorithms, and etc. Meanwhile our framework can also be applied to emergency preparedness class of applications to identify the critical parameters for designing more efficient emergency response systems.