“…And, as the CAVE is a power-hungry installation, we also plan to measure how different coding practices affect its power consumption. Here, we consider adapting approaches used for other devices, for example [31].…”
LIRKIS CAVE is a contemporary Cave Automatic Virtual Environment, developed and built at the home institution of the authors. Its walls, ceiling and floor are covered by stereoscopic LCD panels, user movement is tracked by OptiTrack cameras and scene rendering is carried out by a cluster of seven computers. The most unique feature is a portable design. It allows for disassembly of the whole CAVE to transport it to another location. The paper describes the hardware and software of the CAVE and presents results of several performance evaluation experiments. It also deals with current and future applications of the CAVE, which fall into the area of cognitive infocommunications and are primarily aimed toward impaired people.
“…And, as the CAVE is a power-hungry installation, we also plan to measure how different coding practices affect its power consumption. Here, we consider adapting approaches used for other devices, for example [31].…”
LIRKIS CAVE is a contemporary Cave Automatic Virtual Environment, developed and built at the home institution of the authors. Its walls, ceiling and floor are covered by stereoscopic LCD panels, user movement is tracked by OptiTrack cameras and scene rendering is carried out by a cluster of seven computers. The most unique feature is a portable design. It allows for disassembly of the whole CAVE to transport it to another location. The paper describes the hardware and software of the CAVE and presents results of several performance evaluation experiments. It also deals with current and future applications of the CAVE, which fall into the area of cognitive infocommunications and are primarily aimed toward impaired people.
“…As mobile software applications operate in resource-constrained environments, guidelines to build energy efficient applications are of utmost importance. In the context of this task, we performed extensive studies on whether or not a set of best performance-based practices have an impact on the energy consumed by Android applications [6,14,64,15,16,11,50]. The paper [15] won the best paper award at CIbSE'18.…”
Section: Task T2: Methods For Software Energy Optimizationmentioning
This report describes the research goals and results of the Green Software Lab (GSL) research project. This was a project funded by Fundação para a Ciência e a Tecnologia (FCT) -the Portuguese research foundation -under reference POCI-01-0145-FEDER-016718, that ran from January 2016 till July 2020. This report includes the complete document reporting the results achieved during the project execution, which was submitted to FCT for evaluation on July 2020. It describes the goals of the project, and the different research tasks presenting the deliverables of each of them. It also presents the management and result dissemination work performed during the project's execution. The document includes also a self assessment of the achieved results, and a complete list of scientific publications describing the contributions of the project. Finally, this document includes the FCT evaluation report.
“…Mobile software platforms are targeted by a valuable research activity [6,11,13], mainly because of the speed of reaction of stakeholders as device battery drain is a much faster indicator than the energy bill integrating power consumption over days or months. The development is therefore also focusing on tool usage and research, which are capable to determine "energy leaks" or evaluate energy efficiency improvements between versions of software [1].…”
Energy consumption is a key performance indicator of any software run on mobile devices. Working or application software is the main category of software where such energy (in)efficient performance becomes accelerated between users and other stakeholders. Measuring energy efficiency is becoming a part of automated and manual performance testing as well-both answering to the increasing usage requirements and addressing acceptance testing optimization. In this paper, we select three software tools-an e-mail client and two social network applications, those energy consumption is being measured and analyzed. We decided to apply very generic profiles during our measurements, where the actions were performed all manually. Our results show that besides the difference in the number of features covered by the software, also their implementation plays an important role in energy consumption. Focusing on a specific feature within the working software does not imply that all quality indicators of it are the best among the software group's implementations.
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