Fuzzy Q-Learning-Based Opportunistic Communication for MEC-Enhanced Vehicular Crowdsensing-Reference-Cited by-同舟云学术

Fuzzy Q-Learning-Based Opportunistic Communication for MEC-Enhanced Vehicular Crowdsensing

Published:2022-12 Issue:4 Volume:19 Page:5021-5033
ISSN:1932-4537
Container-title:IEEE Transactions on Network and Service Management
language:
Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Nguyen Trung Thanh¹^ORCID,Thao Nguyen Truong²^ORCID,Nguyen Thanh-Hung¹,Nguyen Phi Le¹^ORCID

Affiliation:

1. School of Information and Communication Technology, Hanoi University of Science and Technology, Hanoi, Vietnam

2. Information Technology and Human Factors, Digital Architecture Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

Funder

Vingroup Joint Stock Company (Vingroup JSC), Vingroup

Vingroup Innovation Foundation

Ministry of Education and Training of Vietnam

Trường Đại học Bách Khoa Hà Nội

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Link

http://xplorestaging.ieee.org/ielx7/4275028/10034788/09841517.pdf?arnumber=9841517

Reference27 articles.

1. Efficient Data Uploading for Mobile Crowdsensing via Team Collaborating and Matching

2. Crowd-Sensing Assisted Vehicular Distributed Computing for HD Map Update

3. Data Offloading for Mobile Crowdsensing in Opportunistic Social Networks

4. Collaborative Data Delivery for Smart City-Oriented Mobile Crowdsensing Systems

5. A Probabilistic Model for the Deployment of Human-Enabled Edge Computing in Massive Sensing Scenarios

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