Green software requirements and measurement: random decision forests-based software energy consumption profiling. Issue 1 (March 2017)

• Record Type: Journal Article
• Authors: Beghoura, Mohamed; Boubetra, Abdelhak; Boukerram, Abdallah
• Is Part Of: Requirements engineering. Volume 22:Issue 1(2017)
• Page Start: 27
• Page End: 40
• Publication Date: 2017-03
• Subjects: Software engineering -- Energy consumption model -- Green software -- Green requirements -- Software development -- Green software engineering -- Random decision forests -- Multiple regression model; Requirements engineering -- Periodicals; Software engineering -- Periodicals; Computer software -- Development -- Periodicals; Logiciels -- Développement -- Périodiques; Génie logiciel -- Périodiques; 005.12
• DOI: 10.1007/s00766-015-0234-2
• Languages: English
• ISSNs: 0947-3602

Abstract

Abstract This paper proposes an explicit definition of green software requirements and a tool to support their evaluation . The proposed evaluation tool describes the green efficiency by considering the energy consumption as the main aspect to be studied during the development stage. This approach consists of building a multiple regression model, by using a supervised learning algorithm, in order to reproduce the energy consumption pattern of devices at different workload circumstances. The energy consumption model is then deployed to estimate the impact of software applications based on their resource usage. Our work has been validated on desktop and mobile devices. The experiments show the effectiveness of the proposed energy profiling tool that provided relevant information on the energy consumption of software applications.