A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks-Reference-Cited by-同舟云学术

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A2T-Boost: An Adaptive Cell Selection Approach for 5G/SDN-Based Vehicular Networks

Published:2023 Issue: Volume:11 Page:7085-7108
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

AlAblani Ibtihal Ahmed¹^ORCID,Arafah Mohammed Amer²^ORCID

Affiliation:

1. Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

2. Department of Computer Technology, Technical Digital College, Technical and Vocational Training Corporation, Riyadh, Saudi Arabia

Funder

Deanship of Scientific Research at King Saud University through the Research Group

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10021319.pdf?arnumber=10021319

Reference88 articles.

1. Adaptive Resource Allocation for Interference Management in Small Cell Networks

2. User-Centric QoS-Aware Interference Coordination for Ultra Dense Cellular Networks

3. Optimal aggregated ConvergeCast scheduling with an SINR interference model

4. Vertical Handover Necessity Estimation Based on a New Dwell Time Prediction Model for Minimizing Unnecessary Handovers to a WLAN Cell

5. NFV Provisioning in Large-Scale Distributed Networks With Minimum Delay

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1. Research on collaborative edge network service migration strategy based on crowd clustering;Scientific Reports;2024-03-26

2. Optimizing cell selection for data services in mm-waves spectrum through enhanced extreme gradient boosting;Results in Engineering;2024-03

3. Self-Attention-Based Uplink Radio Resource Prediction in 5G Dual Connectivity;IEEE Internet of Things Journal;2023-11-15

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