Abstract
Multimedia analytics on mobile devices is a long-term problem due to the intensive processing and energy requirements. To meet the demands of multimedia applications, it is necessary to optimise green computing methods, low bandwidth Cloud feedback, and mobile energy-efficient computing, despite the challenges that Mobile Edge Cloud presents. Green computing approaches on a Mobile Edge Cloud can reduce energy consumption, and Cloud task offloading on eligible devices can improve overall end-device performance. We conducted a methodical survey to determine the current state of the art in mobile data Cloud, green computing, and Cloud offloading. This research makes two contributions. To begin, we proposed a system taxonomy as Data, Green computing, and Cloud feedback. Second, the taxonomies are validated and analyzed. According to our findings, green computing algorithms need to be improved further to reduce energy consumption on mobile devices. Low bandwidth model-based Cloud feedback support is lacking, as is the Quality of Experience in Mobile Cloud feedback for multimedia applications.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2023 International Conference on Advances in Computing Research (ACR’23) |
| Editors | Kevin Daimi, Abeer Al Sadoon |
| Place of Publication | Switzerland |
| Publisher | Springer |
| Pages | 423-432 |
| Number of pages | 10 |
| ISBN (Electronic) | 9783031337437 |
| ISBN (Print) | 9783031337420 |
| DOIs | |
| Publication status | Published - 2023 |
Bibliographical note
Publisher Copyright:© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.