Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/8064
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMarimuthu, C.
dc.contributor.authorChandrasekaran, K.
dc.date.accessioned2020-03-30T10:18:02Z-
dc.date.available2020-03-30T10:18:02Z-
dc.date.issued2017
dc.identifier.citationProceedings - 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.773-776en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8064-
dc.description.abstractEnergy-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.titleFeature-Oriented Domain Analysis Framework for Energy-Aware Self-Adaptive Softwareen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.