AI-Based Mobility-Aware Energy Efficient Resource Allocation and Trajectory Design for NFV Enabled Aerial Networks-Reference-Cited by-同舟云学术

AI-Based Mobility-Aware Energy Efficient Resource Allocation and Trajectory Design for NFV Enabled Aerial Networks

Published:2023-03 Issue:1 Volume:7 Page:281-297
ISSN:2473-2400
Container-title:IEEE Transactions on Green Communications and Networking
language:
Short-container-title:IEEE Trans. on Green Commun. Netw.

Author:

Pourghasemian Mohsen¹^ORCID,Abedi Mohammad Reza²,Hosseini Shima Salar¹^ORCID,Mokari Nader¹^ORCID,Javan Mohammad Reza¹^ORCID,Jorswieck Eduard A.³^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran

2. Department of Electrical Engineering, Shahrood University of Technology, Shahrud, Iran

3. Department of Information Theory and Communication Systems, TU Braunschweig, Braunschweig, Germany

Funder

joint Iran National Science Foundation

German Research Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Renewable Energy, Sustainability and the Environment

Link

http://xplorestaging.ieee.org/ielx7/7511293/10045559/09809985.pdf?arnumber=9809985

Reference47 articles.

1. E2E QoS Guarantee for the Tactile Internet via Joint NFV and Radio Resource Allocation

2. Delay-Aware Scheduling and Resource Optimization With Network Function Virtualization

3. Resource Efficiency: A New Paradigm on Energy Efficiency and Spectral Efficiency Tradeoff

4. Age of Information Aware VNF Scheduling in Industrial IoT Using Deep Reinforcement Learning

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