Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Dynamic Power Management: Design Techniques and CAD Tools
Dynamic Power Management: Design Techniques and CAD Tools
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Frame-based dynamic voltage and frequency scaling for a MPEG decoder
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Leakage aware dynamic voltage scaling for real-time embedded systems
Proceedings of the 41st annual Design Automation Conference
GRACE-1: Cross-Layer Adaptation for Multimedia Quality and Battery Energy
IEEE Transactions on Mobile Computing
DVSleak: combining leakage reduction and voltage scaling in feedback EDF scheduling
Proceedings of the 2007 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
Approximation algorithm for the temperature-aware scheduling problem
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
A Queuing Theoretic Approach to Processor Power Adaptation for Video Decoding Systems
IEEE Transactions on Signal Processing
Traffic models in broadband networks
IEEE Communications Magazine
Proceedings of the 16th ACM/IEEE international symposium on Low power electronics and design
Optimality and improvement of dynamic voltage scaling algorithms for multimedia applications
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Energy-aware complexity adaptation for mobile video calls
MM '11 Proceedings of the 19th ACM international conference on Multimedia
International Journal of Communication Networks and Distributed Systems
Hi-index | 0.00 |
The time-varying workload for multimedia applications poses a great challenge for the efficient performance of dynamic voltage scaling (DVS) algorithms. While many DVS algorithms have been proposed for real-time applications, there does not yet exist a systematic method for evaluating the optimality of such DVS algorithms. In this paper, we propose an offline linear programming (LP) method to determine the minimum energy consumption for processing multimedia tasks under stringent delay deadlines. Based on this lower bound, we evaluate the efficiency of various existing DVS algorithms. Furthermore, we modify the LP formulation to construct an online robust sequential linear programming DVS algorithm for real-time multimedia processing. Simulation results from decoding over a wide range of video sequences shows that on average, our online algorithm consumes less than 1% more energy than the optimal lower bound while dropping only 0.1% of all scheduled decoding jobs, while the existing best algorithm consumes roughly 3% more energy at the same miss rate.