Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search
IEEE Transactions on Knowledge and Data Engineering
Consumer-Centric Service-Oriented Architecture: A New Approach
SEUS-WCCIA '06 Proceedings of the The Fourth IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, and the Second International Workshop on Collaborative Computing, Integration, and Assurance (SEUS-WCCIA'06)
XACML policy integration algorithms: not to be confused with XACML policy combination algorithms!
Proceedings of the eleventh ACM symposium on Access control models and technologies
DDSOS: A Dynamic Distributed Service-Oriented Simulation Framework1
ANSS '06 Proceedings of the 39th annual Symposium on Simulation
Magpie: online modelling and performance-aware systems
HOTOS'03 Proceedings of the 9th conference on Hot Topics in Operating Systems - Volume 9
Amazon S3 for science grids: a viable solution?
DADC '08 Proceedings of the 2008 international workshop on Data-aware distributed computing
Access control policy combining: theory meets practice
Proceedings of the 14th ACM symposium on Access control models and technologies
Optimistic Synchronization of Parallel Simulations in Cloud Computing Environments
CLOUD '09 Proceedings of the 2009 IEEE International Conference on Cloud Computing
X-trace: a pervasive network tracing framework
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
SimSaaS: simulation software-as-a-service
Proceedings of the 44th Annual Simulation Symposium
QoS-Based service selection and ranking with trust and reputation management
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
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Simulation can benefit from cloud computing that often comes with thousands of processors and its software is structured as Software-as-a-Service (SaaS) with its Multi-Tenancy Architecture (MTA). To support multiple tenants, simulation SaaS models need be modeled and customized to fulfill the various functional and quality requirements of individual tenants. The multitude options of tenant-specific data have made the simulation models and execution processes rather complicated. This paper presents P4-SimSaaS that comes with an new ontology system and an innovative tenant related policy specification for Simulation SaaS. P4-SimSaaS can reduce the complexity in the MTA simulation models and consequently increase the flexibility in MTA simulation execution environment. A case study is offered to demonstrate the entire framework.