IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Interior point algorithms: theory and analysis
Interior point algorithms: theory and analysis
A predictive system shutdown method for energy saving of event-driven computation
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
A survey of design techniques for system-level dynamic power management
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
Quantitative comparison of power management algorithms
DATE '00 Proceedings of the conference on Design, automation and test in Europe
Comparing System-Level Power Management Policies
IEEE Design & Test
Dynamic Power Management for Nonstationary Service Requests
IEEE Transactions on Computers
Adaptive Disk Spin-down Policies for Mobile Computers
MLICS '95 Proceedings of the 2nd Symposium on Mobile and Location-Independent Computing
Analysis of Self-Similarity in I/O Workload Using Structural Modeling
MASCOTS '99 Proceedings of the 7th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Self-Similarity in I/O Workload: Analysis and Modeling
WWC '98 Proceedings of the Workload Characterization: Methodology and Case Studies
Energy-Efficient Real-Time Scheduling in IEEE 802.11 Wireless LANs
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Online strategies for dynamic power management in systems with multiple power-saving states
ACM Transactions on Embedded Computing Systems (TECS)
Hierarchical Adaptive Dynamic Power Management
IEEE Transactions on Computers
PowerNap: An Efficient Power Management Scheme for Mobile Devices
IEEE Transactions on Mobile Computing
Dynamic power management using machine learning
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
EURASIP Journal on Embedded Systems
Improving IEEE 802.11 power saving mechanism
Wireless Networks
A Self-Similarity Frame Traffic Model Based on the Frame Components in 802.11 Networks
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 02
Adaptive power management using reinforcement learning
Proceedings of the 2009 International Conference on Computer-Aided Design
Policy optimization for dynamic power management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Stochastic modeling of a power-managed system-construction and optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
An analysis of system level power management algorithms and their effects on latency
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Battery-aware power management based on Markovian decision processes
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Online learning of timeout policies for dynamic power management
ACM Transactions on Embedded Computing Systems (TECS)
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We propose a novel power efficient adaptive hybrid dynamic power management (AH-DPM) algorithm. To adapt well to bursty request arrival patterns with self-similarity and a service provider (SP, i.e., hard disk or WLAN NIC, in this paper) with multiple inactive states, the proposed AH-DPM first derives the average idle time of the SP in the bursty (ON) period and non-bursty (OFF) period separately. Then, to achieve better power saving, we use the average idle time in the ON period to adjust the timeout value more precisely and use the average idle time in the OFF period to decide which inactive state the SP should be switched to. Experimental results based on real traces show that, for the hard disk, the average power consumption of the proposed AH-DPM is better than that of the Adaptive Timeout (ATO), Machine Learning (ML), Predictive, Static Timeout (STO), and Stochastic algorithms. In addition, the average response time of the proposed AH-DPM algorithm is still lower than that specified in a typical hard disk specification. As to the WLAN NIC, experimental results show that the average power consumption of the proposed AH-DPM is comparable to that of the Oracle (theoretically optimal), ATO, and Predictive algorithms, and is better than that of the ML, STO, and Stochastic algorithms. However, the average packet transmission delay of the proposed AH-DPM is better than that of the ATO and Predictive algorithms. Therefore, by providing a better tradeoff between average power consumption and average response time (or average packet transmission delay), the proposed AH-DPM algorithm is very feasible for extending the battery lifetime of ever increasing mobile devices that are equipped with hard disks and WLAN NICs.