GreenCrowd: Toward a Holistic Algorithmic Crowd Charging Framework-Reference-Cited by-同舟云学术

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GreenCrowd: Toward a Holistic Algorithmic Crowd Charging Framework

Published:2023-10 Issue:4 Volume:22 Page:58-65
ISSN:1536-1268
Container-title:IEEE Pervasive Computing
language:
Short-container-title:IEEE Pervasive Comput.

Author:

Raptis Theofanis P.¹^ORCID,Bedogni Luca²^ORCID

Affiliation:

1. National Research Council, Pisa, Italy

2. University of Modena and Reggio Emilia, Modena, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/7756/10345383/10242117.pdf?arnumber=10242117

Reference18 articles.

1. Distributed and Energy-Efficient Mobile Crowdsensing with Charging Stations by Deep Reinforcement Learning

2. Exploiting peer-to-peer wireless energy sharing for mobile charging relief

3. UBAR

4. Pay On-Demand: Dynamic Incentive and Task Selection for Location-Dependent Mobile Crowdsensing Systems

5. A Blockchain-Based Reward Mechanism for Mobile Crowdsensing

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