A continuous media application supporting dynamic QOS control on real-time Mach
MULTIMEDIA '94 Proceedings of the second ACM international conference on Multimedia
A hierarchial CPU scheduler for multimedia operating systems
OSDI '96 Proceedings of the second USENIX symposium on Operating systems design and implementation
Adaptive rate-controlled scheduling for multimedia applications
IEEE/ACM Transactions on Networking (TON)
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Digital Control Systems
A processor reservation system supporting dynamic QOS control
RTCSA '95 Proceedings of the 2nd International Workshop on Real-Time Computing Systems and Applications
HARTIK 3.0: a portable system for developing real-time applications
RTCSA '97 Proceedings of the 4th International Workshop on Real-Time Computing Systems and Applications
Adaptive Bandwidth Reservation for Multimedia Computing
RTCSA '99 Proceedings of the Sixth International Conference on Real-Time Computing Systems and Applications
A proportional share resource allocation algorithm for real-time, time-shared systems
RTSS '96 Proceedings of the 17th IEEE Real-Time Systems Symposium
A resource allocation model for QoS management
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
Elastic Task Model for Adaptive Rate Control
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Integrating Multimedia Applications in Hard Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
CPU Service Classes for Multimedia Applications
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Constant Bandwidth vs Proportional Share Resource Allocation
ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02
Application of fuzzy logic to real-time scheduling
RTC'05 Proceedings of the 14th IEEE-NPSS conference on Real time
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A remarkable class of soft-real time applications exhibits a very dynamical behaviour due to the variations in the treated data. Moreover, such programs have to be able to run on hundreds of different platforms. As a consequence classical real-time scheduling algorithms are not flexible enough since they are based on the exact knowledge of the tasks' timing parameters. Some of the approaches proposed so far in the literature guarantee temporal isolation, but they make a static assignment of resources to each task, which, once again, is based on an a priori knowledge. In this paper we propose a closed loop method for on-line adapting the fraction of assigned resource to the task requirements. The approach is based on adaptive control techniques and has resulted to be effective in a significant set of real-life experiments.