High Definition Map Data Optimization for Autonomous Driving in Vehicular Named Data Networks-Reference-Cited by-同舟云学术

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High Definition Map Data Optimization for Autonomous Driving in Vehicular Named Data Networks

Published:2023-05-28 Issue: Volume: Page:
ISSN:
Container-title:ICC 2023 - IEEE International Conference on Communications
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Author:

Doe Daniel Mawunyo¹,Chen Dawei²,Han Kyungtae²,Wang Haoxin³,Xie Jiang⁴,Han Zhu¹

Affiliation:

1. University of Houston,Electrical and Computer Engineering Department,Houston,TX,USA

2. Toyota Motor North America R&D,InfoTech Labs,Mountain View,CA,USA

3. Georgia State University,Department of Computer Science,GA,USA

4. The University of North Carolina at Charlotte,Department of Electrical and Computer Engineering,Charlotte,NC,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10278505/10278554/10279193.pdf?arnumber=10279193

Reference19 articles.

1. An SDN-Assisted Framework for Optimal Deployment of MapReduce Functions in WSNs

2. MapTask Scheduling in MapReduce With Data Locality: Throughput and Heavy-Traffic Optimality

3. A loosely-coupled deep reinforcement learning approach for order acceptance decision of mass-individualized printed circuit board manufacturing in industry 4.0

4. Loss-aware adaptive scalable transmission in wireless high-speed railway networks

5. Traffic-Aware Geo-Distributed Big Data Analytics with Predictable Job Completion Time

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