TY - GEN
T1 - DFEAM
T2 - 7th International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2019
AU - Tanaka, Fumiya
AU - Hisazumi, Kenji
AU - Fukuda, Akira
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number 15H05708.
Publisher Copyright:
Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved
PY - 2019
Y1 - 2019
N2 - There is an increasing demand for reducing the power consumption in the field of embedded-system development. A development methodology, which can change software's power consumption according to the power consumption of the hardware, can help fulfill this requirement. However, there will be a trade-off between the power consumption and service quality, which must be balanced for efficient operation. In this paper, we propose dynamic feature-oriented energy-aware adaptive modeling (DFEAM), which develops self-adaptive software through model-driven development for achieving a proper balance between the power consumption and quality of service (QoS). In this method, the application itself decides its behavior, according to the power-consumption situation, by linking the feature model describing the variability of the application with the description of its behavior, using the executable and translatable unified modeling language (xtUML). For achieving a satisfactory QoS for variations that are complex and dependent on variable points, a model is created to quantify the QoS values, which is then used as an index of comparison for finding the optimum variation. We conducted case studies on applications with multiple variable points, and evaluated them using the GQM model. The results of the evaluation showed that the adaptation incorporated provided the maximum software quality under the given power limitations, thus verifying the usefulness of the proposed DFEAM method.
AB - There is an increasing demand for reducing the power consumption in the field of embedded-system development. A development methodology, which can change software's power consumption according to the power consumption of the hardware, can help fulfill this requirement. However, there will be a trade-off between the power consumption and service quality, which must be balanced for efficient operation. In this paper, we propose dynamic feature-oriented energy-aware adaptive modeling (DFEAM), which develops self-adaptive software through model-driven development for achieving a proper balance between the power consumption and quality of service (QoS). In this method, the application itself decides its behavior, according to the power-consumption situation, by linking the feature model describing the variability of the application with the description of its behavior, using the executable and translatable unified modeling language (xtUML). For achieving a satisfactory QoS for variations that are complex and dependent on variable points, a model is created to quantify the QoS values, which is then used as an index of comparison for finding the optimum variation. We conducted case studies on applications with multiple variable points, and evaluated them using the GQM model. The results of the evaluation showed that the adaptation incorporated provided the maximum software quality under the given power limitations, thus verifying the usefulness of the proposed DFEAM method.
KW - Embedded System
KW - Feature-oriented
KW - Model-driven Development
KW - Self-adaptive Software
KW - XtUML
UR - http://www.scopus.com/inward/record.url?scp=85064698477&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064698477&partnerID=8YFLogxK
U2 - 10.5220/0007370802920299
DO - 10.5220/0007370802920299
M3 - Conference contribution
AN - SCOPUS:85064698477
T3 - MODELSWARD 2019 - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development
SP - 292
EP - 299
BT - MODELSWARD 2019 - Proceedings of the 7th International Conference on Model-Driven Engineering and Software Development
A2 - Hammoudi, Slimane
A2 - Pires, Luis Ferreira
A2 - Selic, Bran
PB - SciTePress
Y2 - 20 February 2019 through 22 February 2019
ER -