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5G & Multi Access Edge Computing

Authors: Wasif Arshad;

5G & Multi Access Edge Computing

Abstract

This paper explains about 5G technology and the growing number of Internet of Things (IoT) devices that are changing the way we communicate and process data. 5G is designed to improve not only the communication speed but also control, computing, and content delivery. It enables the users to use new applications like mobile gaming, augmented reality (AR), virtual reality (VR), as well as industrial & building automation systems that require bulk amount of data. Recent forecasts show that IoT devices would exceed 50 billion and create enormous amounts of data, much more than what many devices can handle. Traditional cloud computing, known as Mobile Cloud Computing (MCC), has struggled to keep up with these demands. MCC faces problems like high latency, data privacy concerns, and limited bandwidth because it relies on centralized servers. This makes it unsuitable for the fast and secure data processing needed for 5G and IoT. To solve these problems, Mobile Edge Computing (MEC) was introduced by the European Telecommunications Standards Institute (ETSI). MEC moves computing resources closer to the users, usually to base stations on the edge of the network. This ensures low latency in data transfer and related services. Soon after the launching MEC was renamed as Multi-access Edge Computing to show its use beyond just mobile networks. There are several technologies that enhance Mobile Edge Computing (MEC) for improved 5G experiences which involves cloud computing, software-defined networking (SDN), network function virtualization (NFV) network slicing, and computation offloading. So, by using these techniques MEC ensures, the significant reduction in latency as compared to cloud computing having single central server for data applications.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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