| A case study of a system-level approach to power-aware computing |
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ACM Transactions on Embedded Computing Systems (TECS)
archive
Volume 2 , Issue 3 (August 2003)
table of contents
Pages: 255 - 276
Year of Publication: 2003
ISSN:1539-9087
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Authors
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Thomas L. Martin
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Virginia Tech, Blacksburg, VA
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Daniel P. Siewiorek
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Carnegie Mellon University, Pittsburgh, PA
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Asim Smailagic
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Carnegie Mellon University, Pittsburgh, PA
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Matthew Bosworth
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Carnegie Mellon University, Pittsburgh, PA
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Matthew Ettus
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Carnegie Mellon University, Pittsburgh, PA
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Jolin Warren
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Carnegie Mellon University, Pittsburgh, PA
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| Bibliometrics |
Downloads (6 Weeks): 10, Downloads (12 Months): 81, Citation Count: 3
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ABSTRACT
This paper introduces a systematic approach to power awareness in mobile, handheld computers. It describes experimental evaluations of several techniques for improving the energy efficiency of a system, ranging from the network level down to the physical level of the battery. At the network level, a new routing method based upon the power consumed by the network subsystem is shown to improve power consumption by 15% on average and to reduce latency by 75% over methods that consider only the transmitted power. At the boundary between the network and the processor levels, the paper presents the problem of local versus remote processing and derives a figure of merit for determining whether a computation should be completed locally or remotely, one that involves the relative performance of the local and remote system, the transmission bandwidth and power consumption, and the network congestion. At the processor level, the main memory bandwidth is shown to have a significant effect on the relationship between performance and CPU frequency, which in turn determines the energy savings of dynamic CPU speed-setting. The results show that accounting for the main memory bandwidth using Amdahl's law permits the performance speed-up and peak power versus the CPU frequency to be estimated to within 5%. The paper concludes with a technique for mitigating the loss of battery energy capacity with large peak currents, showing an improvement of up to 10% in battery life, albeit at some cost to the size and weight of the system.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Kinshuk Govil , Edwin Chan , Hal Wasserman, Comparing algorithm for dynamic speed-setting of a low-power CPU, Proceedings of the 1st annual international conference on Mobile computing and networking, p.13-25, November 13-15, 1995, Berkeley, California, United States
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INDEX TERMS
Primary Classification:
C.
Computer Systems Organization
C.4
PERFORMANCE OF SYSTEMS
Subjects:
Design studies
Additional Classification:
C.
Computer Systems Organization
C.2
COMPUTER-COMMUNICATION NETWORKS
C.2.1
Network Architecture and Design
Subjects:
Wireless communication
C.4
PERFORMANCE OF SYSTEMS
Subjects:
Performance attributes;
Modeling techniques
C.5
COMPUTER SYSTEM IMPLEMENTATION
C.5.3
Microcomputers
Subjects:
Portable devices (e.g., laptops, personal digital assistants)
General Terms:
Design,
Experimentation,
Measurement,
Performance
Keywords:
Power-aware,
battery properties,
dynamic power management,
energy-aware,
handheld computers,
multihop wireless network
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