Dynamic Power Management of a System With a Two-Priority Request Queue Using Probabilistic-Model Checking

Sesic, A.; Dautovic, Stanisa; Malbaša, Veljko

doi:10.1109/tcad.2007.911342

Cited by 16 publications

(9 citation statements)

References 11 publications

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“…2. The second is a software-controlled dynamic power management (DPM) system adapted from Qiu et al (2001), Sesic et al (2008) and described on our project webpage. We performed a wide range of experiments using the system variants from Table 6.…”

Section: Methodsmentioning

confidence: 99%

Synthesis of probabilistic models for quality-of-service software engineering

Gerasimou

Călinescu

Tamburrelli³

2018

Autom Softw Eng

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An increasingly used method for the engineering of software systems with strict quality-of-service (QoS) requirements involves the synthesis and verification of probabilistic models for many alternative architectures and instantiations of system parameters. Using manual trial-and-error or simple heuristics for this task often produces suboptimal models, while the exhaustive synthesis of all possible models is typically intractable. The EvoChecker search-based software engineering approach presented in our paper addresses these limitations by employing evolutionary algorithms to automate the model synthesis process and to significantly improve its outcome. EvoChecker can be used to synthesise the Pareto-optimal set of probabilistic models associated with the QoS requirements of a system under design, and to support the selection of a suitable system architecture and configuration. EvoChecker can also be used at runtime, to drive the efficient reconfiguration of a self-adaptive software system. We evaluate EvoChecker on several variants of three systems from different application domains, and show its effectiveness and applicability. Keywords Search-based software engineering • Probabilistic model checking • Evolutionary algorithms • QoS requirements B Simos Gerasimou

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Section: Methodsmentioning

confidence: 99%

Synthesis of probabilistic models for quality-of-service software engineering

Gerasimou

Călinescu

Tamburrelli³

2018

Autom Softw Eng

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“…Irani et al 26 studied the adversarial modeling approach for power management, and stochastic model-checking for the evaluation of the effectiveness of DPM algorithms. In addition, Sesic et al 27 extended the work of Norman et al 25 with two different request priorities. Their works can be generalized to multiple request priorities and different queue length.…”

Section: Related Workmentioning

confidence: 99%

Synthesizing power management strategies for wireless sensor networks with UPPAAL-STRATEGO

Dai

Mei

Guo

2017

International Journal of Distributed Sensor Networks

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Effective power management has become a key concern in the design of wireless sensor networks. Dynamic power management refers to strategies which selectively switch between several power states of a device during the runtime in order to achieve a tradeoff between power consumption and performance. In this article, we present a novel methodology that exploits current model-checking technology for automatic synthesis for dynamic power management. The generic system model for dynamic power management is modeled as a network of timed games. And the synthesis objectives are expressed as synthesis queries. Subsequently, automatic synthesis of power management strategies is performed by UPPAAL-STRATEGO with respect to the synthesis queries. Once a strategy has been constructed, its performance can be analyzed through statistical model-checking using the same tool. The modeling and synthesizing procedures are illustrated with a running example. Finally, the applicability of the methodology is assessed by synthesizing and evaluating a range of power management strategies for a concrete sensor node. Our methodology can be employed to help designers in constructing dynamic power management strategies for wireless sensor networks in practical applications.

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“…These kinds of approaches are also known as Dynamic Power Management (DPM ) where a software program is used for measuring the power consumption of a computer system. In [24][25][26][27][28][29][30][31][32], the authors have presented a survey and various techniques for minimizing power consumption using DPM. DPM at the OS level refers to supply voltage and clock frequency adjustment schemes imp lemented while tasks are running.…”

Section: B Software-based Approachesmentioning

confidence: 99%

Minimizing Power Consumption by Personal Computers: A Technical Survey

Gupta

Singh²

2012

IJITCS

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Recently, the demand of "Green Co mputing", wh ich represents an environmentally responsible way of reducing power consumption, and involves various environmental issues such as waste management and greenhouse gases is increasing explosively. We have laid g reat emphasis on the need to minimize power consumption and heat dissipation by computer systems, as well as the requirement for changing the current power scheme options in their operating systems (OS). In this paper, we have provided a comp rehensive technical review of the existing, though challenging, work on minimizing power consumption by computer systems, by utilizing various approaches, and emphasized on the software approach by making use of dynamic power management as it is used by most of the OSs in their power scheme configurations, seeking a better understanding of the power management schemes and current issues, and future directions in this field. Herein, we review the various approaches and techniques, including hard ware, software, the central processing unit (CPU) us age and algorith mic approaches for power economy. On the basis of analysis and observations, we found that this area still requires a lot o f work, and needs to be focused towards some new intelligent approaches so that human inactivity periods for co mputer systems could be reduced intelligently. one can focus; the objective being to reduce power dissipation. The motive behind this research on minimizing power consumption by PCs derives fro m a human tendency to leave the co mputer system running in between jobs, and as to when work is likely to be resumed is not at all predictable. The running computer system consumes electricity, and it is estimated that a typical desktop PC with a 17-inch flat-panel LCD monitor requires about 65-100 watts for the co mputer, and 35 watts for the mon itor. If left on 24×7 for one year, this system will consume 874 kilo watt hours of electricityenough to release 341 kg o f carbon dio xide into the atmosphere, and can also be equated to driving 1312 km in an average car [2]. On the other hand, by turning off this co mputer system when not in use (i.e., lunch times, weekends, during meetings) for one year, one can save as much energy as it takes to wash 464 loads of washing, or to run your microwave 24 hours a day for one week [3]. Even the various options used by the power scheme in the OS are not sufficient to save power, for example, screen savers are actually power wasters because when the screen saver kicks in, more power is consumed by the hard disk drive (HDD), CPU and monitor [4]. According to a study performed by IST at the University o f Waterloo, fo r a Pentiu m 4, 1.7 GHz mach ine without the monitor, it was found that during the system boot-up, power requirement is close to 110 watts; in id le mode, it uses close to 60 watts; and in fu ll power-saving mode, with no hard disk spin and the mach ine in sleep mode, power consumption is close 35 watts [5]. P. K. Gupta g raduated in Informat ics and ComputerEngineering fro m Vladimir State...

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Dynamic Power Management of a System With a Two-Priority Request Queue Using Probabilistic-Model Checking

Cited by 16 publications

References 11 publications

Synthesis of probabilistic models for quality-of-service software engineering

Synthesis of probabilistic models for quality-of-service software engineering

Synthesizing power management strategies for wireless sensor networks with UPPAAL-STRATEGO

Minimizing Power Consumption by Personal Computers: A Technical Survey

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