Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks (original) (raw)
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The growth of the telecommunication industry is fast-paced with groundbreaking engineering achievements. Notwithstanding the technological advancement in the industry, it had continued to cope with the phenomenon of resource constraint in portable mobile telecommunication devices compared to fixed and tethered devices. Portable mobile handheld devices have very low computational, storage and energy carrying capacity occasioned by the needs to satisfy portability, very small form factor, ergonomics, style and trends. Solutions such as cloudlets, cyber foraging, mobile cloud computing (MCC), and more recently but most applicable, multi-access edge computing (MEC) have been proffered with different application methodologies including computational offloading, distributed computing, thin clients, middleware, mobile environment cloning as well as representational state transfer. There is a need to satisfy requirements of new and emerging use cases, especially the deployments of 5G coming up with applications such as virtual reality (VR), augmented reality (AR), intelligent transport systems (ITS), connected autonomous vehicle (CAV), smart hospitals, ultra high definition multi-feed live streaming, etc. The usage patterns of most of these different applications, though not always, is ephemeral and on-demand, except that the demand will be numerous, huge, asymmetric and highly latency-sensitive in terms of needs for computation, storage and analytics while at the fringe of the network where data are being generated and results being applied. In this research, we evaluated 5G end-to-end transport for vantage location of MEC server to achieve low user plane latency.
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5G is the next generation cellular network that aspires to achieve substantial improvement on quality of service, such as higher throughput and lower latency. Edge computing is an emerging technology that enables the evolution to 5G by bringing cloud capabilities near to the end users (or user equipment, UEs) in order to overcome the intrinsic problems of the traditional cloud, such as high latency and the lack of security. In this paper, we establish a taxonomy of edge computing in 5G, which gives an overview of existing state-of-the-art solutions of edge computing in 5G on the basis of objectives, computational platforms, attributes, 5G functions, performance measures, and roles. We also present other important aspects, including the key requirements for its successful deployment in 5G and the applications of edge computing in 5G. Then, we explore, highlight, and categorize recent advancements in edge computing for 5G. By doing so, we reveal the salient features of different edge computing paradigms for 5G. Finally, open research issues are outlined. INDEX TERMS 5G, cloud computing, edge computing, fog computing.
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The emergence of Multi-Access Edge Computing (MEC) technology aims to extend cloud computing capabilities to the edge of the wireless access networks, i.e., closer to the end-users. Thus, MEC-enabled 5G wireless systems are envisaged to offer real-time, low-latency, and high-bandwidth access to the radio network resources. Thus, MEC allows network operators to open up their networks to a wide range of innovative services, thereby giving rise to a brand-new ecosystem and a value chain. Furthermore, MEC as an enabling technology will provide new insights into coherent integration of Internet of Things (IoT) in 5G wireless systems. In this context, this paper expounds the four key technologies, including Network Function Virtualization (NFV), Software Defined Networking (SDN), Network Slicing and Information Centric Networking (ICN), that will propel and intensify the integration of MEC IoT in 5G networks. Moreover, our goal is to provide the close alliance between MEC and these four driving technologies in the 5G IoT context and to identify the open challenges, future directions, and concrete integration paths. c
Deployment of edge servers in 5G cellular networks
Transactions on Emerging Telecommunications Technologies, 2020
With the rapid development of Internet of Things technology and interactive applications, the number of terminal devices in the network is increasing, and the development of interactive applications is hindered by network delay. To solve the network delay, bandwidth, and workload requirements in the new era, edge computing came into being. Edge computing aims to implement computing, storage, communication, and other services at the edge of the network by sinking cloud services from the core network to the edge of the network. Current research studies pay less attention to the impact of edge server location on the system performance, and edge server deployment is one of the key technologies for mobile edge computing. Therefore, we take 5G macrocellular/microcellular cluster as the edge server deployment scenario, propose an equivalent bandwidth-based deployment strategy, establish a mathematical model for edge server deployment, and contract a task experience function as an evaluation index from two aspects: task time and energy overhead. Based on the analysis of the experimental results, it is verified that the deployment strategy based on equivalent bandwidth is superior to other deployment strategies in terms of terminal device task overhead.
5G is the next generation cellular network that aspires to achieve substantial improvement on quality of service, such as higher throughput and lower latency. Edge computing is an emerging technology that enables the evolution to 5G by bringing cloud capabilities near to the end users (or user equipment, UEs) in order to overcome the intrinsic problems of the traditional cloud, such as high latency and the lack of security. In this paper, we establish a taxonomy of edge computing in 5G, which gives an overview of existing state-of-the-art solutions of edge computing in 5G on the basis of objectives, computational platforms, attributes, 5G functions, performance measures, and roles. We also present other important aspects, including the key requirements for its successful deployment in 5G and the applications of edge computing in 5G. Then, we explore, highlight, and categorize recent advancements in edge computing for 5G. By doing so, we reveal the salient features of different edge computing paradigms for 5G. Finally, open research issues are outlined.