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IEEE Transactions on Computers
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IEEE Transactions on Computers
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Dynamic task allocation strategies in MPSoC for soft real-time applications
Proceedings of the conference on Design, automation and test in Europe
RTCSA '08 Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Utility accrual real-time scheduling for multiprocessor embedded systems
Journal of Parallel and Distributed Computing
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RTAS '10 Proceedings of the 2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium
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ECRTS '10 Proceedings of the 2010 22nd Euromicro Conference on Real-Time Systems
Utility Accrual Dynamic Routing in Real-Time Parallel Systems
IEEE Transactions on Parallel and Distributed Systems
Utility Accrual Object Distribution in Real-Time Systems
ICPADS '10 Proceedings of the 2010 IEEE 16th International Conference on Parallel and Distributed Systems
Multiprocessor System-on-Chip (MPSoC) Technology
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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This paper considers object-based real-time embedded systems on MPSoCs. Objects provide system services to the real-time tasks. Each task is subject to a time/utility function (TUF) which determines the accrued utility of the task according to its completion time. One major problem in such systems is to place the objects on the processing elements (PEs) in the MPSoC so as to maximize the total accrued utility. In this regard, we propose a utility accrual object distribution (UAOD) algorithm consisting of two phases. In the first phase, the PEs are reserved for the most beneficial tasks in an offline manner. The reservation is constituted of some proposed methods for object placement, object replication, deadline decomposition, and deadline adaptation. For the objects which are not placed in the reservation, UAOD follows a load-balancing approach to place them on the PEs. As the second phase, UAOD performs an online scheduling over the tasks assigned to each PE in the offline object placement. An extension of this algorithm, namely UAOD^@? is also proposed for the situations where the exact task execution-times are not known a priori. Simulation results reveal that the total accrued utility is improved with the proposed algorithms comparing to the traditional object placement methods.