Energy-aware adaptation for mobile applications
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System-level power optimization: techniques and tools
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Dynamic power management using adaptive learning tree
ICCAD '99 Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design
Exploiting Fine-Grained Idle Periods in Networks of Workstations
IEEE Transactions on Parallel and Distributed Systems
Dynamic voltage scaling and power management for portable systems
Proceedings of the 38th annual Design Automation Conference
Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Critical power slope: understanding the runtime effects of frequency scaling
ICS '02 Proceedings of the 16th international conference on Supercomputing
Drowsy caches: simple techniques for reducing leakage power
ISCA '02 Proceedings of the 29th annual international symposium on Computer architecture
Comparing System-Level Power Management Policies
IEEE Design & Test
Proceedings of the conference on Design, automation and test in Europe
Program Counter Based Techniques for Dynamic Power Management
HPCA '04 Proceedings of the 10th International Symposium on High Performance Computer Architecture
Improving energy efficiency by making DRAM less randomly accessed
ISLPED '05 Proceedings of the 2005 international symposium on Low power electronics and design
Frame Buffer Energy Optimization by Pixel Prediction
ICCD '05 Proceedings of the 2005 International Conference on Computer Design
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
Dynamic power management using machine learning
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
A Quantitative analysis of disk drive power management in portable computers
WTEC'94 Proceedings of the USENIX Winter 1994 Technical Conference on USENIX Winter 1994 Technical Conference
TCON'95 Proceedings of the USENIX 1995 Technical Conference Proceedings
PowerNap: eliminating server idle power
Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
Accurate system-level performance modeling and workload characterization for mobile internet devices
Proceedings of the 9th workshop on MEmory performance: DEaling with Applications, systems and architecture
Run-time adaptive workload estimation for dynamic voltage scaling
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Recipe for efficiency: principles of power-aware computing
Communications of the ACM
IDC: an energy efficient communication scheme for connected mobile platforms
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
In search of energy-efficient mobile networking
IEEE Communications Magazine
Analysis of dynamic voltage scaling for system level energy management
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
Server workload analysis for power minimization using consolidation
USENIX'09 Proceedings of the 2009 conference on USENIX Annual technical conference
Adaptive display power management for mobile games
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
IEEE Transactions on Computers
Policy optimization for dynamic power management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Energy consumption anatomy of 802.11 devices and its implication on modeling and design
Proceedings of the 8th international conference on Emerging networking experiments and technologies
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Reducing energy consumption is one of the most important design aspects for small form-factor mobile platforms, such as smartphones and tablets. Despite its potential for power savings, optimally leveraging system low-power sleep states during active mobile workloads, such as video streaming and web browsing, has not been fully explored. One major challenge is to make intelligent power management decisions based on, among other things, accurate system idle duration prediction, which is difficult due to the non-deterministic system interrupt behavior. In this paper, we propose a novel framework, called E2S3 (Energy Efficient Sleep-State Selection), that dynamically enters the optimal low-power sleep state to minimize the system power consumption. In particular, E2S3 detects and exploits short idle durations during active mobile workloads by, (i) finding optimal thresholds (i.e., energy break-even times) for multiple low-power sleep states, (ii) predicting the sleep-state selection error probabilities heuristically, and by (iii) selecting the optimal sleep state based on the expected reward, e.g., power consumption, which incorporates the risks of making a wrong decision We implemented and evaluated E2S3 on Android-based smartphones, demonstrating the effectiveness of the algorithm. The evaluation results show that E2S3 significantly reduces the platform energy consumption, by up to 50% (hence extending battery life), without compromising system performance.