Dynamic power management for portable systems

Simunic, T.; Benini, Luca; Glynn, Peter W.; Micheli, Giovanni De

doi:10.1145/345910.345914

Cited by 169 publications

(117 citation statements)

References 17 publications

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“…There have been several initiatives to design energy-efficient processors [13], [14] primarily employing dynamic voltage scaling and low-power VLSI implementations. In [15], dynamic voltage scaling is further exploited by adding a smart buffer scheme.…”

Section: Related Workmentioning

confidence: 99%

MEERA: cross-layer methodology for energy efficient resource allocation in wireless networks

Pollin

Mangharam

Bougard

et al. 2007

IEEE Trans. Wireless Commun.

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Part of the Electrical and Computer Engineering CommonsSuggested Citation: Pollin, S.; Mangharam, R.; Bougard, B.; Van der Perre, L.; Moerman, I.; Rajkumar, R.; Catthoor, F.; , "MEERA: Cross-Layer Methodology for Energy Efficient Resource Allocation in Wireless Networks," Wireless Communications, IEEE Transactions on , vol.7, no.1, pp.98-109, Jan. 2008. ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. MEERA: Cross-Layer Methodology for Energy Efficient Resource Allocation in Wireless Networks AbstractIn many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. Reducing the transceiver's power consumption to extend the system lifetime has therefore become a design goal. Our work is targated at this goal and is based on the following two observations. First, conventional energy management approaches have focused independently on minimizing the fixed energy cost (by shutdown) and on scalable energy costs (by leveraging, for example, the modulation, code-rate and transmission power). These two energy management approaches present a tradeoff. For example, lower modulation rates and transmission power minimize the variable energy component, but this shortens the sleep duration thereby increasing fixed energy consumption. Second, in order to meet the Quality of Service (QoS) timeliness requirements for multiple users, we need to determine to what extent each system in the network may sleep and scale. Therefore, we propose a two-phase methodology that resolves the sleep-scaling tradeoff across the physical, communications and link layers at design time and schedules nodes at runtime with near optimal energy-efficient configurations in the solution space. As a result, we are able to achieve very low run-time overheads. Our methodology is applied to a case study on delivering a guaranteed QoS for multiple users with MPEG-4 video over a slow-fading channel. By exploiting runtime controllable parameters of actual RF components and a modified 802.11 Medium Access Controller, system lifetime is increased by a factor of 3-to-10 in comparison with conventional techniques. Abstract-In many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. Reducing the transceiver's power consumption to extend the system lifetime has therefore become a design goal. Our work is targated at this goal and is based on the following two observations. First, conventional energy management approaches have focused independently on minimizing the fixed energy cost (by shutdown) and on scalable energy costs (by leveraging, for example, the modulation, code-rate and transmission power). These two energy management approaches present a tradeoff. For example, lower modulation rates and tran...

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Section: Related Workmentioning

confidence: 99%

MEERA: cross-layer methodology for energy efficient resource allocation in wireless networks

Pollin

Mangharam

Bougard

et al. 2007

IEEE Trans. Wireless Commun.

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“…Hwang et al [10] use exponential averages to predict idleness and shut down the device when the predicted idleness exceeds the break-even time. Several studies focus on stochastic optimization using Markov models [2,16] and generalized stochastic Petri Nets [15]. While many of these methods adapt to system behavior, some policies may adapt more quickly than others for different workloads.…”

Section: Related Workmentioning

confidence: 99%

Automatic Run-Time Selection of Power Policies for Operating Systems

Pettis

Ridenour

2006

Proceedings of the Design Automation &Amp; Test in Europe Conference

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“…see [6], [7] for a protocols and systems perspective and [8] for a stochastic optimization treatment of the problem. On the contrary, little attention is given on the transmission power aspect, as e.g.…”

Section: Related Workmentioning

confidence: 99%

“…[2], [8]. However, we control both the radio state (DPM) and the transmission power (TPC); in the following sections, we explore how the optimal control depends on the relative values of operating power (in on, sleep states) vs. transmission power.…”

Section: Related Workmentioning

confidence: 99%

Energy-efficient communication in battery-constrained portable devices

Markopoulou¹,

Li²,

Chan³

et al. 2005

2nd International Conference on Broadband Networks, 2005.

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Abstract-Portable devices (such as personal digital assistants and laptops with wireless connectivity) are becoming ubiquitous. As their functionality and capabilities increase, their energy consumption requirements also increase. Yet, these devices have to operate on limited batteries. In order to maximize the battery lifetime, it is necessary to optimize the use of energy at various components of such a device. In this paper, we consider a single portable device operating on a limited battery that transmits information over an interference-limited wireless channel. We seek to optimize the power consumption on the communication radio in this device, by controlling both the operation mode and the transmission power. We model the general problem using dynamic programming, obtain the optimal solutions for insightful special cases and explore various design tradeoffs. Our work provides an analytical framework for stochastic modeling and optimization of energy spent for communications in battery-operated portable devices.

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Dynamic power management for portable systems

Cited by 169 publications

References 17 publications

MEERA: cross-layer methodology for energy efficient resource allocation in wireless networks

MEERA: cross-layer methodology for energy efficient resource allocation in wireless networks

Automatic Run-Time Selection of Power Policies for Operating Systems

Energy-efficient communication in battery-constrained portable devices

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