Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks leveraging mobile base stations. As a promising edge technology, it can be applied to mobile, wireless, and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end-users. MEC provides seamless integration of multiple application service providers and vendors toward mobile subscribers, enterprises, and other vertical segments. It is an important component in the 5G architecture which supports variety of innovative applications and services where ultralow latency is required. This paper is aimed to present a comprehensive survey of relevant research and technological developments in the area of MEC. It provides the definition of MEC, its advantages, architectures, and application areas; where we in particular highlight related research and future directions. Finally, security and privacy issues and related existing solutions are also discussed.

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Mobile Edge Computing: A Survey

LiMPO: lightweight mobility prediction and offloading framework using machine learning for mobile edge computing

The fifth generation (5G) of cellular networks promises to be a major step in the evolution of wireless technology. 5G is planned to be used in a very broad set of application scenarios. These scenarios have strict heterogeneous requirements that will be accomplished by enhancements on the radio access network and a collection of innovative wireless technologies. Softwarization technologies, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), will play a key role in integrating these different technologies. Network slicing emerges as a cost-efficient solution for the implementation of the diverse 5G requirements and verticals. The 5G radio access and core networks will be based on a SDN/NFV infrastructure, which will be able to orchestrate the resources and control the network in order to efficiently and flexibly and with scalability provide network services. In this paper, we present the up-to-date status of the software-defined 5G radio access and core networks and a broad range of future research challenges on the orchestration and control aspects.

/pdf/orchestration-and-control-in-software-defined-5g-networks-1tun9orre1.pdf

Orchestration and Control in Software-Defined 5G Networks: Research Challenges

With a plethora of new connections, features, and services introduced, the 5th generation (5G) wireless technology reflects the development of mobile communication networks and is here to stay for the next decade. The multitude of services and technologies that 5G incorporates have made modern communication networks very complex and sophisticated in nature. This complexity along with the incorporation of Machine Learning (ML) and Artificial Intelligence (AI) provides the opportunity for the attackers to launch intelligent attacks against the network and network devices. These attacks often traverse undetected due to the lack of intelligent security mechanisms to counter these threats. Therefore, the implementation of real-time, proactive, and self-adaptive security mechanisms throughout the network would be an integral part of 5G as well as future communication systems. Therefore, large amounts of data collected from real networks will play an important role in the training of AI/ML models to identify and detect malicious content in network traffic. This work presents 5G-NIDD, a fully labeled dataset built on a functional 5G test network that can be used by those who develop and test AI/ML solutions. The work further analyses the collected data using common ML models and shows the achieved accuracy levels.

5G-NIDD: A Comprehensive Network Intrusion Detection Dataset Generated over 5G Wireless Network

The high heterogeneity of 5G use cases requires the extension of the traditional per-component testing procedures provided by certification organizations, in order to devise and incorporate methodologies that cover the testing requirements from vertical applications and services. In this paper, we introduce an experimentation methodology that is defined in the context of the 5GENESIS project, which aims at enabling both the testing of network components and validation of E2E KPIs. The most important contributions of this methodology are its modularity and flexibility, as well as the open-source software that was developed for its application, which enable lightweight adoption of the methodology in any 5G testbed. We also demonstrate how the methodology can be used, by executing and analyzing different experiments in a 5G Non-Standalone (NSA) deployment at the University of Malaga. The key findings of the paper are an initial 5G performance assessment and KPI analysis and the detection of under-performance issues at the application level. Those findings highlight the need for reliable testing and validation procedures towards a fair benchmarking of generic 5G services and applications.

A Modular Experimentation Methodology for 5G Deployments: The 5GENESIS Approach.

The 5th generation mobile networks (5G) bring a number of new possibilities for application developers. They cut down many barriers that have potentially prevented developing new applications for mobile networks by introducing significantly higher data rates, lower delays, and better energy efficiency. 5G is not only an evolution of radio technology. The basis of the 5G concept is built upon a strong emphasis on requirements of various applications and their use scenarios. To support application development for 5G networks, test networks are playing an essential role. This paper presents a 5G test network, which is developed and deployed in Oulu, Finland, together with a number of different partners closely involved in the development and specification of the 5G technology. The test network targets to serve various application developers by providing extensive test facilities in a carrier-grade state-of-the-art network.

5GTN: A test network for 5G application development and testing

A system for testing a base station apparatus includes a circuit board frame including a plurality of interfaces for a plurality of testing modules, and a central processing circuitry. The plurality of testing modules is detachably attachable to the interfaces, and each testing module comprises hardware that is configured to connect a determined interface of the base station apparatus and a reprogrammable processing circuitry. The central processing circuitry is configured to detect testing modules attached to the circuit board frame, determine a testing program to execute, and to program reprogrammable processing circuitries of the detected testing modules to execute testing functions of the testing program.

System for testing base station

This document discloses a system for testing a base station apparatus, the system comprising: a circuit board frame comprising a plurality of interfaces for a plurality of testing modules and a central processing circuitry; said plurality of testing modules detachably attachable to the interfaces, wherein each testing module comprises hardware configured to connect a determined interface of the base station apparatus and a reprogrammable processing circuitry, wherein the central processing circuitry is configured to detect testing modules attached to the circuit board frame, determine a testing program to execute, and to program reprogrammable processing circuitries of the detected testing modules to execute testing functions of the testing program.

System for base-station testing

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5GTN: A test network for 5G application development and testing

System for testing base station

System for base-station testing