A Reinforcement Learning Framework for Vehicular Network Routing Under Peak and Average Constraints
Author:
Affiliation:
1. Tsinghua University, Beijing, China
2. Purdue University, West Lafayette, IN, USA
3. George Washington University, Washington, DC, USA
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Cisco, Inc.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/10124808/10015040.pdf?arnumber=10015040
Reference38 articles.
1. Channel Prediction Based Scheduling for Data Dissemination in VANETs
2. Link Stability Based Optimized Routing Framework for Software Defined Vehicular Networks
3. A novel vehicular location prediction based on mobility patterns for routing in urban VANET
4. Hierarchical Routing for Vehicular Ad Hoc Networks via Reinforcement Learning
5. Minimizing transmission delays in vehicular ad hoc networks by optimized placement of road-side unit
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