Towards power reduction through improved software design

Sahin, Cagri; Cayci, Furkan; Clause, James; Kiamilev, Fouad; Pollock, Lori; Winbladh, Kristina

doi:10.1109/energytech.2012.6304705

Cited by 15 publications

(8 citation statements)

References 32 publications

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“…Therefore, significant work has focused on this task at various levels. Hardware instrumentation-based approaches [18,20] measure the actual power usage of a system by using physical instrumentation. However, they can be expensive and it is not easy to use specialized hardware, although they provide accurate measurements.…”

Section: Related Workmentioning

confidence: 99%

How do code refactorings affect energy usage?

Sahin

Pollock

Clause

2014

Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

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Context: Code refactoring's benefits to understandability, maintainability and extensibility are well known enough that automated support for refactoring is now common in IDEs. However, the decision to apply such transformations is currently performed without regard to the impacts of the refactorings on energy consumption. This is primarily due to a lack of information and tools to provide such relevant information to developers. Unfortunately, concerns about energy efficiency are rapidly becoming a high priority concern in many environments, including embedded systems, laptops, mobile devices, and data centers.Goal: We aim to address the lack of information about the energy efficiency impacts of code refactorings. Method:We conducted an empirical study to investigate the energy impacts of 197 applications of 6 commonly-used refactorings.Results: We found that refactorings can not only impact energy usage but can also increase and decrease the amount of energy used by an application. In addition, we also show that metrics commonly believed to correlate with energy usage are unlikely to be able to fully predict the impact of applying a refactoring. Conclusion:The results from this and similar studies could be used to augment IDEs to help software developers build more energy efficient software.

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Section: Related Workmentioning

confidence: 99%

How do code refactorings affect energy usage?

Sahin

Pollock

Clause

2014

Proceedings of the 8th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

Self Cite

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“…The need for reflecting energy consumption of software in design models is also studied by Sahin et al [26]. However, Götz et al [19] propose a model-driven component-based approach for software systems that can be optimized w.r.t.…”

Section: Related Workmentioning

confidence: 98%

A tool-supported approach for modular design of energy-aware software

Brinke

Malakuti

Bockisch

et al. 2014

Proceedings of the 29th Annual ACM Symposium on Applied Computing

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The reduction of energy usage by software-controlled systems has many advantages, including prolonged battery life and reduction of greenhouse gas emissions. Thus, being able to implement energy optimization in software is essential. This requires a model of the energy utilization-or more general resource utilization-for each component in the system. Optimizer components, then, analyze resource utilization of other components in terms of such a model and adapt their behavior accordingly. We have devised a notation for Resource-Utilization Models (RUMs) that can be part of a component's application programming interface (API) to facilitate the modular implementation of optimizers. In this paper, we present tools for extracting such RUMs from components with an existing implementation.

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“…It is possible to identify many references that measure the energy consumption of software applications and propose ways to reduce it [9,[25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40]. In Table 7, we compare the information (listed as table columns) provided by our process along with the information provided by each of these papers (listed as table rows).…”

Section: Related Workmentioning

confidence: 99%

Methodological Guidelines for Measuring Energy Consumption of Software Applications

Ardito

Coppola

Morisio

et al. 2019

Scientific Programming

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Energy consumption information for devices, as available in the literature, is typically obtained with ad hoc approaches, thus making replication and consumption data comparison difficult. We propose a process for measuring the energy consumption of a software application. The process contains four phases, each providing a structured deliverable that reports the information required to replicate the measurement. The process also guides the researcher on a threat to validity analysis to be included in each deliverable. This analysis ensures better reliability, trust, and confidence to reuse the collected consumption data. Such a process produces a structured consumption data for any kind of electronic device (IoT devices, mobile phones, personal computers, servers, etc.), which can be published and shared with other researchers fostering comparison or further investigations. A real case example demonstrates how to apply the process and how to create the required deliverables.

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Towards power reduction through improved software design

Cited by 15 publications

References 32 publications

How do code refactorings affect energy usage?

How do code refactorings affect energy usage?

A tool-supported approach for modular design of energy-aware software

Methodological Guidelines for Measuring Energy Consumption of Software Applications

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