A practitioner's handbook for real-time analysis
A practitioner's handbook for real-time analysis
Resource kernels: a resource-centric approach to real-time and multimedia systems
Readings in multimedia computing and networking
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
User Focus in Consumer Terminals and Conditionally Guaranteed Budgets
IWQoS '01 Proceedings of the 9th International Workshop on Quality of Service
On Quality of Service Optimization with Discrete QoS Options
RTAS '99 Proceedings of the Fifth IEEE Real-Time Technology and Applications Symposium
Skip-Over: algorithms and complexity for overloaded systems that allow skips
RTSS '95 Proceedings of the 16th IEEE Real-Time Systems Symposium
Design and Evaluation of a Feedback Control EDF Scheduling Algorithm
RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
Dynamic Programming
Quality-Assuring Scheduling-Using Stochastic Behavior to Improve Resource Utilization
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
Quality Control for Scalable Media Processing Applications
Journal of Scheduling
QoS-based resource management for ambient intelligence
Ambient intelligence
Quality Aware MPEG-2 Stream Adaptation in Resource Constrained Systems
ECRTS '04 Proceedings of the 16th Euromicro Conference on Real-Time Systems
SEM'02 Proceedings of the 3rd international conference on Software engineering and middleware
Performance specifications and metrics for adaptive real-time systems
RTSS'10 Proceedings of the 21st IEEE conference on Real-time systems symposium
Video quality-of-service for consumer terminals - a novel system for programmable components
IEEE Transactions on Consumer Electronics
Computational-complexity scalable motion estimation for mobile MPEG encoding
IEEE Transactions on Consumer Electronics
Human perception of jitter and media synchronization
IEEE Journal on Selected Areas in Communications
CoMPSoC: A template for composable and predictable multi-processor system on chips
ACM Transactions on Design Automation of Electronic Systems (TODAES)
ACM Transactions on Embedded Computing Systems (TECS)
Multi-level feedback control for quality of service management
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Control strategies for H.264 video decoding under resources constraints
Proceedings of the Fifth International Workshop on Feedback Control Implementation and Design in Computing Systems and Networks
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Run-time Task Overlapping on Multiprocessor Platforms
Journal of Signal Processing Systems
Control strategies for H.264 video decoding under resources constraints
ACM SIGOPS Operating Systems Review
A Robust Mechanism for Adaptive Scheduling of Multimedia Applications
ACM Transactions on Embedded Computing Systems (TECS)
Adaptive real-time scheduling for legacy multimedia applications
ACM Transactions on Embedded Computing Systems (TECS)
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Video processing in software is often characterized by highly fluctuating, content-dependent processing times, and a limited tolerance for deadline misses. We present an approach that allows close-to-average-case resource allocation to a single video processing task, based on asynchronous, scalable processing, and QoS adaptation. The QoS adaptation balances different QoS parameters that can be tuned, based on user-perception experiments: picture quality, deadline misses, and quality changes. We model the balancing problem as a discrete stochastic decision problem, and propose two solution strategies, based on a Markov decision process and reinforcement learning, respectively. We enhance both strategies with a compensation for structural (non-stochastic) load fluctuations. Finally, we validate our approach by means of simulation experiments, and conclude that both enhanced strategies perform close to the theoretical optimum.