| Title |
GreenCrowd: Toward a Holistic Algorithmic Crowd Charging Framework |
| ID_Doc |
7950 |
| Authors |
Raptis, TP; Bedogni, L |
| Title |
GreenCrowd: Toward a Holistic Algorithmic Crowd Charging Framework |
| Year |
2023 |
| Published |
Ieee Pervasive Computing, 22, 4 |
| DOI |
10.1109/MPRV.2023.3308014 |
| Abstract |
Crowd charging represents an alternative peer-to-peer energy replenishment option for mobile users to align with the circular economy paradigm. Following this option, users bound by finite resource capacity utilize the energy from external to the crowd wireless or wired energy sources (such as shared chargers), and internal to the crowd energy sources (such as mobile devices, via wireless power transfer). If designed carefully, such utilization can boost the energy availability of users and provide energy ubiquitously to their devices for making them functional for longer. This article proposes the GreenCrowd framework, introducing a privacy-by-design in the digital domain crowd charging process, the architecture of which incorporates multiple crowd-* components, such as online social information exploitation, algorithmic battery aging mitigation, user reward mechanisms, and advanced decision making. The primary aim of article is to present the technological and applicative requirements and constraints of GreenCrowd, and provide practical evidence on its feasibility. |
| Author Keywords |
Batteries; Aging; Peer-to-peer computing; Wireless communication; Quality of experience; Threshold voltage; Task analysis |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001064539600001 |
| WoS Category |
Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications |
| Research Area |
Computer Science; Engineering; Telecommunications |
| PDF |
https://ieeexplore.ieee.org/ielx7/7756/5210084/10242117.pdf
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