Performance Analytical Modeling of Mobile Edge Computing for Mobile Vehicular Applications: A Worst-Case Perspective-Reference-Cited by-同舟云学术

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Performance Analytical Modeling of Mobile Edge Computing for Mobile Vehicular Applications: A Worst-Case Perspective

Published:2024-09 Issue:9 Volume:23 Page:8951-8964
ISSN:1536-1233
Container-title:IEEE Transactions on Mobile Computing
language:
Short-container-title:IEEE Trans. on Mobile Comput.

Author:

Miao Wang¹^ORCID,Min Geyong²^ORCID,Yu Zhengxin³^ORCID,Zhang Xu⁴^ORCID

Affiliation:

1. Department of Computer Science, University of Plymouth, Plymouth, U.K.

2. Department of Computer Science, University of Exeter, Exeter, U.K.

3. School of Computing and Communications, Lancaster University, Lancaster, U.K.

4. Department of Computer Science, University of Leeds, Leeds, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7755/10627925/10411130.pdf?arnumber=10411130

Reference39 articles.

1. Worldwide IDC global datasphere forecast, 2022–2026;Rydning,2022

2. Deep-Reinforcement-Learning-Based Offloading Scheduling for Vehicular Edge Computing

3. Cloud Computing-Based Analyses to Predict Vehicle Driving Shockwave for Active Safe Driving in Intelligent Transportation System

4. Mobility-Aware Multi-User Offloading Optimization for Mobile Edge Computing

5. Stochastic Analysis of Delayed Mobile Offloading in Heterogeneous Networks

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