# Mobile Edge Computing, Metaverse, 6G Wireless Communications, Artificial Intelligence, and Blockchain: Survey and Their Convergence

arXiv: https://arxiv.org/abs/2209.14147 · HTML: https://mlsanity.com/paper/2209.14147/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 34 references that are in the map.
- First posted on arXiv 28 Sep 2022.

## Builds on (most cited first, 13 of 13)

- [Federated Machine Learning: Concept and Applications](https://mlsanity.com/paper/1902.04885/) (2019)
- [A Survey on Metaverse: Fundamentals, Security, and Privacy](https://mlsanity.com/paper/2203.02662/) (2022)
- [A Full Dive into Realizing the Edge-enabled Metaverse: Visions, Enabling Technologies,and Challenges](https://mlsanity.com/paper/2203.05471/) (2022)
- [Artificial Intelligence for the Metaverse: A Survey](https://mlsanity.com/paper/2202.10336/) (2022)
- [6G-enabled Edge AI for Metaverse: Challenges, Methods, and Future Research Directions](https://mlsanity.com/paper/2204.06192/) (2022)
- [A General Method to Find Highly Coordinating Communities in Social Media through Inferred Interaction Links](https://mlsanity.com/paper/2103.03409/) (2021)
- [Resource Allocation for Mobile Metaverse with the Internet of Vehicles over 6G Wireless Communications: A Deep Reinforcement Learning Approach](https://mlsanity.com/paper/2209.13425/) (2022)
- [Metaverse for Wireless Systems: Vision, Enablers, Architecture, and Future Directions](https://mlsanity.com/paper/2207.00413/) (2022)
- [A Survey of 6G Wireless Communications: Emerging Technologies](https://mlsanity.com/paper/2004.08549/) (2020)
- [Security of Virtual Reality Authentication Methods in Metaverse: An Overview](https://mlsanity.com/paper/2209.06447/) (2022)
- [A First Look at Zoombombing](https://mlsanity.com/paper/2009.03822/) (2020)
- [Blockchain-based Edge Resource Sharing for Metaverse](https://mlsanity.com/paper/2208.05120/) (2022)
- [Intelligent Blockchain-based Edge Computing via Deep Reinforcement Learning: Solutions and Challenges](https://mlsanity.com/paper/2206.09009/) (2022)

## Built on by (most cited first, 3 of 3)

- [HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse](https://mlsanity.com/paper/2211.03300/) (2022)
- [The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions](https://mlsanity.com/paper/2304.09240/) (2023)
- [UAV aided Metaverse over Wireless Communications: A Reinforcement Learning Approach](https://mlsanity.com/paper/2301.01474/) (2023)

## Abstract (arXiv)

With the advances of the Internet of Things (IoT) and 5G/6G wireless communications, the paradigms of mobile computing have developed dramatically in recent years, from centralized mobile cloud computing to distributed fog computing and mobile edge computing (MEC). MEC pushes compute-intensive assignments to the edge of the network and brings resources as close to the endpoints as possible, addressing the shortcomings of mobile devices with regard to storage space, resource optimisation, computational performance and efficiency. Compared to cloud computing, as the distributed and closer infrastructure, the convergence of MEC with other emerging technologies, including the Metaverse, 6G wireless communications, artificial intelligence (AI), and blockchain, also solves the problems of network resource allocation, more network load as well as latency requirements. Accordingly, this paper investigates the computational paradigms used to meet the stringent requirements of modern applications. The application scenarios of MEC in mobile augmented reality (MAR) are provided. Furthermore, this survey presents the motivation of MEC-based Metaverse and introduces the applications of MEC to the Metaverse. Particular emphasis is given on a set of technical fusions mentioned above, e.g., 6G with MEC paradigm, MEC strengthened by blockchain, etc.