Dynamic mapping of a class of independent tasks onto heterogeneous computing systems
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
IEEE Transactions on Parallel and Distributed Systems
Deadline Scheduling for Real-Time Systems: Edf and Related Algorithms
Deadline Scheduling for Real-Time Systems: Edf and Related Algorithms
Data Intensive Distributed Computing; A Medical Application Example
HPCN Europe '99 Proceedings of the 7th International Conference on High-Performance Computing and Networking
Scheduling Resources in Multi-User, Heterogeneous, Computing Environments with SmartNet
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
SAREC: A Security-Aware Scheduling Strategy for Real-Time Applications on Clusters
ICPP '05 Proceedings of the 2005 International Conference on Parallel Processing
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
A Security Middleware Model for Real-Time Applications on Grids
IEICE - Transactions on Information and Systems
Security-driven scheduling for data-intensive applications on grids
Cluster Computing
Providing Security of Real Time Data Intensive Applications on Grids Using Dynamic Scheduling
GPC '09 Proceedings of the 4th International Conference on Advances in Grid and Pervasive Computing
Enhancing security of real-time applications on grids through dynamic scheduling
JSSPP'05 Proceedings of the 11th international conference on Job Scheduling Strategies for Parallel Processing
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Real-time data-intensive applications with security concerns are arising in many disciplines of science and engineering. Scheduling algorithms play an important role in the design of real-time data-intensive applications. However, conventional real-time scheduling algorithms are inappropriate to fulfill the security requirements of real-time data-intensive applications. In this paper we have proposed a security-attentive dynamic real-time scheduling algorithm named SARDIG for scheduling real-time data-intensive applications. We have proposed a grid architecture which describes the scheduling framework of real-time data-intensive applications. In addition, we have introduced a mathematical model for providing security of the real-time data-intensive applications and a security gain function to quantitatively measure the security enhancement for applications running in the grid sites. We have also proved that the SARDIG algorithm always provides optimum security for real-time data-intensive applications. The time complexity of the SARDIG algorithm has been analyzed to show the efficiency of the algorithm. Simulation results show that the SARDIG algorithm provides better performance and security than other existing scheduling algorithms. Copyright © 2011 John Wiley & Sons, Ltd.