Optimization of Quality of Service in Dynamic Systems
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing 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
Skip-Over: Algorithms and Complexity for Overloaded Systems that Allow Skips
Skip-Over: Algorithms and Complexity for Overloaded Systems that Allow Skips
QoS Control Strategies for High-Quality Video Processing
ECRTS '04 Proceedings of the 16th Euromicro Conference on Real-Time Systems
Fine Grain QoS Control for Multimedia Application Software
Proceedings of the conference on Design, Automation and Test in Europe - Volume 2
QoS control for optimality and safety
Proceedings of the 5th ACM international conference on Embedded software
Two-pass MPEG-2 variable-bit-rate encoding
IBM Journal of Research and Development
A review of the minimum maximum criterion for optimal bitallocation among dependent quantizers
IEEE Transactions on Multimedia
Model-based implementation of real-time applications
EMSOFT '10 Proceedings of the tenth ACM international conference on Embedded software
A model-based approach for multiple QoS in scheduling: from models to implementation
Automated Software Engineering
Rigorous system design: the BIP approach
MEMICS'11 Proceedings of the 7th international conference on Mathematical and Engineering Methods in Computer Science
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We present a fine grain quality control method for multimedia applications. The method takes as input an application software composed of actions. The execution times of actions are unknown increasing functions of quality level parameters. The method allows the construction of a Controller which computes adequate action schedules and corresponding quality levels, so as to meet QoS requirements for a given platform. These include requirements for safety (action deadlines are met) as well optimality (maximization and smoothness of quality levels).The Controller consists of a Quality Manager and a Scheduler. For each action, the Controller uses a quality management policy for choosing a schedule and quality levels meeting the QoS requirements. The schedule is selected amongst a set of optimal schedules computed by the Scheduler.We extend and improve results of previous papers providing a solid theoretical basis for designing and implementing the Controller.We propose a symbolic quality management method using speed diagrams, a representation of the controlled system's dynamics. Instead of numerically computing a quality level for each action, the Quality Manager changes action quality levels based on the knowledge of constraints characterizing control relaxation regions. These are sets of states in which quality management for a given number of computation steps can be relaxed without degrading quality.We study techniques for efficient computation of optimal schedules.We present experimental results including the implementation of the method and benchmarks for an MPEG4 video encoder. The benchmarks show drastic performance improvement for controlled quality with respect to constant quality. They also show that symbolic quality management allows significant reduction of the overhead with respect to numeric quality management. Finally, using optimal schedules can lead to considerable performance gains.