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GreenCrowd: Toward a Holistic Algorithmic Crowd Charging Framework

delete2023-10-01
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OA
AI
T
Theofanis P. Raptis *
L
Luca Bedogni
DOI:10.1109/MPRV.2023.3308014delete
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Abstract

Abstract

En 中文
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.
Keywords:
Batteries
Aging
Peer-to-peer computing
Wireless communication
Quality of experience
Threshold voltage
Task analysis

Journal

I
IEEE PERVASIVE COMPUTING
IF:
1.8
Papers:
26
Citations:
1.7K

Organization

U
universita di modena e reggio emilia
Scholars:
1.6W
Papers: 1.2W
Citations: 12
C
consiglio nazionale delle ricerche (cnr)
Scholars:
6.2W
Papers: 5.7W
Citations: 48
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