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DC Field | Value | Language |
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dc.contributor.author | Marimuthu, C. | |
dc.contributor.author | Chandrasekaran, K. | |
dc.date.accessioned | 2020-03-30T10:18:02Z | - |
dc.date.available | 2020-03-30T10:18:02Z | - |
dc.date.issued | 2017 | |
dc.identifier.citation | Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016, 2017, Vol., , pp.773-776 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/8064 | - |
dc.description.abstract | Energy-aware software is self-adaptive in nature which dynamically changes its behaviour to save energy. Context information plays a major role in developing such self-adaptive and energy-aware software. Any changes in context information may exhibit different number of operating conditions at run-time. The software should be efficiently developed to be more energy-efficient under different operating conditions through well defined dynamic adaptation policies. Developing such energy-aware adaptive behavior is a challenging task with current programming methods. We employed feature-oriented software development (FOSD) for developing such energy-aware self-adaptive software. In this paper, as first step, domain analysis framework for energy-aware self-adaptive software is proposed. The proposed framework uses feature models to explicitly specify the energy-aware features and context information. An illustrative example is presented to show the usefulness of the proposed domain analysis framework. � 2016 IEEE. | en_US |
dc.title | Feature-Oriented Domain Analysis Framework for Energy-Aware Self-Adaptive Software | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
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