A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art (1906.08452v2)

Abstract: Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.

Overview of Multi-Access Edge Computing in 5G and Beyond

Introduction

The paper provides a comprehensive survey on Multi-Access Edge Computing (MEC) within the context of 5G networks and beyond. It explores the potential of MEC to address the computational demands and data traffic pressures driven by advancements such as the Internet of Things (IoT) and compute-intensive applications. The document focuses on the fundamentals of MEC, its integration with emerging technologies, and explores the current state of research including experimental results and ongoing challenges.

Core Principles of MEC

MEC positions IT service environments at the network edge, closely located to end-users, thereby reducing latency and enhancing real-time data processing capabilities essential for applications like augmented reality, autonomous vehicles, and smart cities. The edge computing model offloads tasks from centralized data centers, enabling lower latency and better handling of local data.

Architecture and Integration

The architecture integrates MEC with the 5G network through core components like the MEC orchestrator, platform manager, and virtualization infrastructure. This architecture is crucial for supporting the dynamic and diverse service requirements of 5G networks. Specific enablers, such as network slicing, QoS management, and traffic steering, facilitate seamless integration into 5G systems.

Coverage of State-of-the-art Research

The paper surveys a wide spectrum of research focused on the intersection of MEC with various 5G technologies and scenarios:

1. Non-Orthogonal Multiple Access (NOMA): Focus on utilizing NOMA to enhance connectivity and resource allocation efficiency in MEC scenarios. This integration promises significant improvements in spectral efficiency and reduced latency.
2. Energy Harvesting and Wireless Power Transfer: Research highlights include frameworks for enabling sustainable operation of MEC systems through energy harvesting techniques and wireless power transfer concepts.
3. Unmanned Aerial Vehicle (UAV) Communications: By leveraging UAVs as mobile edge servers or users, various studies demonstrate benefits in flexibility, mobility, and coverage extension in MEC networks.
4. Internet of Things: The paper identifies MEC's role in enhancing IoT systems through offloading and data analytics capabilities, thereby expanding the applications range from smart homes to industrial IoT.
5. Heterogeneous Cloud Radio Access Networks (H-CRAN): By collocating MEC with H-CRAN, the research aims at reducing deployment costs while improving operational efficiency and network reconfigurability.
6. Machine Learning Applications: The integration of ML techniques to optimize MEC functions such as resource allocation, computation offloading, data analytics, and security enhancements is thoroughly reviewed.

Implications and Future Directions

The integration of MEC with cutting-edge technologies holds profound implications for both practical applications and theoretical advancements in the 5G and beyond networks. MEC facilitates distributed computing, leading to enhanced application performance and user experience. It also poses challenges such as resource management, reliability, security, and seamless network integration that require ongoing research and development.

Looking forward, the paper underscores the significance of exploring areas such as collaborative edge computing, federated learning for privacy-preserving data analytics, and efficient resource sharing strategies in resource-constrained settings. These areas are vital for realizing the full potential of MEC in next-generation networks.

Conclusion

This survey encapsulates the transformative role of MEC in 5G and beyond, urging continued efforts from both academia and industry to address the challenges and harness the full potential of MEC-enabled networks. The synthesis of MEC with emerging technologies is pivotal for advancing network capabilities and supporting innovative applications across various domains.