A taxonomy of scientific workflow systems for grid computing
ACM SIGMOD Record
Analysis-by-synthesis distortion computation for rate-distortion optimized multimedia streaming
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Falkon: a Fast and Light-weight tasK executiON framework
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Amazon S3 for science grids: a viable solution?
DADC '08 Proceedings of the 2008 international workshop on Data-aware distributed computing
Seeking supernovae in the clouds: a performance study
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Comparison of resource platform selection approaches for scientific workflows
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Scalability limits of Bag-of-Tasks applications running on hierarchical platforms
Journal of Parallel and Distributed Computing
Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing
IEEE Transactions on Parallel and Distributed Systems
Cloud resource usage: extreme distributions invalidating traditional capacity planning models
Proceedings of the 2nd international workshop on Scientific cloud computing
Experiences using cloud computing for a scientific workflow application
Proceedings of the 2nd international workshop on Scientific cloud computing
Towards Intelligent Data Placement for Scientific Workflows in Collaborative Cloud Environment
IPDPSW '11 Proceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Rate-distortion hint tracks for adaptive video streaming
IEEE Transactions on Circuits and Systems for Video Technology
Moving Multimedia Simulations into the Cloud: A Cost-effective Solution
ISPA '12 Proceedings of the 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications
An E-learning System Based on Secure Data Storage Services in Cloud Computing
International Journal of Information Technology and Web Engineering
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Multimedia communication research and development often requires computationally intensive simulations in order to develop and investigate the performance of new optimization algorithms. Depending on the simulations, they may require even a few days to test an adequate set of conditions due to the complexity of the algorithms. The traditional approach to speed up this type of relatively small simulations, which require several develop-simulate-reconfigure cycles, is indeed to run them in parallel on a few computers and leaving them idle when developing the technique for the next simulation cycle. This work proposes a new cost-effective framework based on cloud computing for accelerating the development process, in which resources are obtained on demand and paid only for their actual usage. Issues are addressed both analytically and practically running actual test cases, i.e., simulations of video communications on a packet lossy network, using a commercial cloud computing service. A software framework has also been developed to simplify the management of the virtual machines in the cloud. Results show that it is economically convenient to use the considered cloud computing service, especially in terms of reduced development time and costs, with respect to a solution using dedicated computers, when the development time is longer than one hour. If more development time is needed between simulations, the economic advantage progressively reduces as the computational complexity of the simulation increases.