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Power/Performance Analysis for Embedded Mobile Applications and Devices

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 2869
Submit your paper and select the Journal “Energies” and the Special Issue “Power/Performance Analysis for Embedded Mobile Applications and Devices” via: https://susy.mdpi.com/user/manuscripts/upload?journal=energies. Please contact the guest editor or the journal editor ([email protected]) for any queries.

Special Issue Editor


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Guest Editor
Department of Computer Science and Information Engineering, National Penghu University of Science and Technology, Penghu 880011, Taiwan
Interests: embedded systems; engineering education; Internet of Things (IoT); deep learning; Internet of Vehicles (IoV); artificial intelligence over Internet of Things (AIoT)
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Special Issue Information

Dear Colleagues,

The Guest Editor is inviting submissions to a Special Issue of Energies on the subject of “Power/Performance Analysis for Embedded Mobile Applications and Devices.” Power and performance are vital terms for power/energy-aware embedded mobile applications and devices. Recently, there have been many emerging techniques for power/energy-aware embedded mobile devices. Moreover, artificial intelligence (AI) and Internet of Things (IoT) techniques and applications are also interesting topics for power and energy researchers.

This Special Issue will deal with advanced optimization, control, analysis, and prediction techniques for power/energy-aware embedded mobile applications and devices. The topics of interest for publication include, but are not limited to:

  • Power analysis;
  • Energy analysis;
  • Performance analysis;
  • Power-aware embedded systems;
  • Energy-aware embedded systems;
  • Low-power systems design;
  • Dynamic voltage and frequency scaling (DVFS);
  • Workload prediction;
  • Power management;
  • Green electronics;
  • Internet of Things (IoT);
  • Artificial intelligence (AI);
  • Artificial intelligence over Internet of Things (AIoT)

Dr. Liang-Bi Chen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • power management
  • performance analysis
  • power-aware embedded systems
  • energy-aware embedded systems
  • battery life
  • Internet of Things (IoT)
  • artificial intelligence over Internet of Things (AIoT)
  • green electronics
  • low-power systems design

Published Papers (1 paper)

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Research

19 pages, 5350 KiB  
Article
Adaptive Color Selection to Limit Power Consumption for Multi-Object GUI Applications in OLED-Based Mobile Devices
by Yeongju Lee and Minseok Song
Energies 2020, 13(10), 2425; https://doi.org/10.3390/en13102425 - 12 May 2020
Cited by 1 | Viewed by 2215
Abstract
Recently, as OLED displays are widely used in smartphones, their power management has become an important issue. Since OLED display devices show a large difference in power consumption depending on the colors used, proper color selection is important to reduce power consumption, but [...] Read more.
Recently, as OLED displays are widely used in smartphones, their power management has become an important issue. Since OLED display devices show a large difference in power consumption depending on the colors used, proper color selection is important to reduce power consumption, but this may affect quality-of-experience (QoE) perceived by users. To address this tradeoff, this paper proposes a new power management scheme for graphical-user-interface (GUI) applications in OLED-based mobile devices. First, we examine the relationship between power consumption and color usage based on actual measurements and derive a model to express color preferences. Next, we present a dynamic programming algorithm that adaptively changes the color of the GUI objects in the applications to limit the total power consumption while effectively reflecting the color preferences of the user. The proposed scheme was implemented on a commercial smartphone, and real power measurements were conducted to examine whether it uses the given energy budget accurately under various color preference configurations. Experimental results show that color preferences significantly affect both power consumption and QoE, thereby demonstrating that personalized color selection plays an important role in reducing total power consumption of an OLED smartphone. Full article
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