Open-Source Multi-Access Edge Computing for 6G: Opportunities and Challenges

Zhao, Liqiang; Zhou, Guorong; Zheng, Gan; Chih‐Lin, I; You, Xiaohu; Hanzo, Lajos

doi:10.1109/access.2021.3130418

Cited by 30 publications

(15 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, it also identifies further research opportunities for challenges in AI-based security and privacy provision as well as feasible options to address these challenges. The author of [ 26 ] discussed an open-source MEC architecture for 6G networks based on innovative decoupling and redesign techniques. A comprehensive survey [ 27 ] reviews the benefits and challenges of integrating network green communication strategies and MEC caching methods on public health and environmental stability.…”

Section: Related Workmentioning

confidence: 99%

Cluster-Based Multi-User Multi-Server Caching Mechanism in Beyond 5G/6G MEC

Samir

El‐Hennawy

El-Badawy

2023

Sensors

View full text Add to dashboard Cite

The work on perfecting the rapid proliferation of wireless technologies resulted in the development of wireless modeling standards, protocols, and control of wireless manipulators. Several mobile communication technology applications in different fields are dramatically revolutionized to deliver more value at less cost. Multiple-access Edge Computing (MEC) offers excellent advantages for Beyond 5G (B5G) and Sixth-Generation (6G) networks, reducing latency and bandwidth usage while increasing the capability of the edge to deliver multiple services to end users in real time. We propose a Cluster-based Multi-User Multi-Server (CMUMS) caching algorithm to optimize the MEC content caching mechanism and control the distribution of high-popular tasks. As part of our work, we address the problem of integer optimization of the content that will be cached and the list of hosting servers. Therefore, a higher direct hit rate will be achieved, a lower indirect hit rate will be achieved, and the overall time delay will be reduced. As a result of the implementation of this system model, maximum utilization of resources and development of a completely new level of services and innovative approaches will be possible.

show abstract

Section: Related Workmentioning

confidence: 99%

Cluster-Based Multi-User Multi-Server Caching Mechanism in Beyond 5G/6G MEC

Samir

El‐Hennawy

El-Badawy

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…The optimal IoAV services placement at the 6G edge network is a very important problem that is not yet solved, especially for advanced autonomous driving where the autopilot is fully offloaded to MEC nodes. Moreover, we consider the following design: Autonomous vehicle architecture 100 : It should consider a controller area network (CAN) to optimize data sharing and control. Embedded autopilot software 11 : It can develop in lines with Apollo auto framework. Multi‐access edge computing platform 101 : It has end‐to‐end life cycle management for all the edge applications. It manages the network edge and application orchestration.…”

Section: G Support For Ioavmentioning

confidence: 99%

“…3. Multi-access edge computing platform 101 : It has end-to-end life cycle management for all the edge applications. It manages the network edge and application orchestration.…”

Section: G-ioav Requirementsmentioning

confidence: 99%

“…It can be applied in different IoAV applications such as edge assisted autonomous driving, 99 AI models training, 111 resources allocation, 112 and so on. It is worth mentioning that ETSI standards introduced multi‐access MEC support in different V2X use cases, as they require ultra‐low latency, ultra‐high reliability, and availability 101,113 . In 5G automotive association (5GAA), the authors highlight 6G MEC as a major element in automotive industry, and they introduce relevant V2X scenarios related to the multi network operator (MNO) management 114 .…”

Section: G Support For Ioavmentioning

confidence: 99%

“…Moreover, scalable computing is required to analyze the data of CAVs data with low latency and efficient feedbacks under large scale 121,122 . Among the main caching and computing platform, we quote ETSI MEC that assures data processing, analysis, prediction in different scenarios such as perception, path planning, localization, HD mapping, remote driving and so forth 101 . Another networking mechanism is available which is information centric networking (ICN) that can ease data caching and retrieval and therefore help CAVs to reach high levels of comfort.…”

Section: Open Issues and Future Directions For 6g‐ioavmentioning

confidence: 99%

See 2 more Smart Citations

6G‐edge support of Internet of Autonomous Vehicles: A survey

Ibn‐Khedher,

Laroui,

Alfaqawi

et al. 2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

With the commercial deployment of 5G mobile communication systems, 6G is proposed to meet the needs of new use cases including connected and autonomous vehicles (CAVs). In this article, we surveyed different 6G embracing technologies such as mobile edge computing, unmanned aerial vehicles, network function virtualization, software defined networking, and artificial intelligence that can enhance the Internet of Autonomous Vehicles (IoAV) network performance comparing to existing 5G enabled solutions. Then, we highlight the convergence path of 6G and IoAV to satisfy the next generation of CAV applications. Further, we propose 6G cellular communication to support the quality of next IoAV applications. Furthermore, the article attempts to study the serious challenges in the 6G‐IoAV research field and propose potential future directions.

show abstract

A Novel Data Offloading with Deep Learning Enabled Cyberattack Detection Model for Edge Computing in 6G Networks

Abdelrahim

2022

AI‐Enabled 6G Networks and Applications

View full text Add to dashboard Cite

Open-Source Multi-Access Edge Computing for 6G: Opportunities and Challenges

Cited by 30 publications

References 40 publications

Cluster-Based Multi-User Multi-Server Caching Mechanism in Beyond 5G/6G MEC

Cluster-Based Multi-User Multi-Server Caching Mechanism in Beyond 5G/6G MEC

6G‐edge support of Internet of Autonomous Vehicles: A survey

A Novel Data Offloading with Deep Learning Enabled Cyberattack Detection Model for Edge Computing in 6G Networks

Contact Info

Product

Resources

About