Resource Optimisation in 5G and Internet-of-Things Networking

Awoyemi, Babatunde Seun; Alfa, Attahiru Sule; Maharaj, B. T.

doi:10.1007/s11277-019-07010-9

Cited by 35 publications

(19 citation statements)

References 59 publications

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“…Although the proportion of the sports tourism service industry in the gross national product is not high, it has also shown a continuous growth trend in recent years, which is directly related to the increase in the importance of the related departments to the sports tourism service industry in recent years [9]. e added value of the sports industry from 2011 to 2020 is selected for analysis, and the specific trend chart is shown in Figure 2.…”

Section: Application Of Internet Of Things and Edgementioning

confidence: 99%

Application of Internet of Things and Edge Computing Technology in Sports Tourism Services

Zheng¹,

Mei

Hou

et al. 2021

Security and Communication Networks

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Aiming at the problems of long retrieval time of sports tourism data, high integration error of sports tourism data, and high energy consumption of sports tourism service management in traditional methods, the application of Internet of Things and edge computing technology in sports tourism services is proposed. We established a sports tourism service application model based on Internet technology to realize the functions of sports tourism service internal management control, external collaboration, and information release. We calculated the similarity of sports tourism resources from the two levels of feature words and the environment where the sports tourism resources are located. According to the calculation results, the edge computing method is used to realize the integration of sports tourism service resources to improve the application effect of sports tourism service application models. The experimental results show that the minimum data retrieval time of the proposed method is only 2.35s. The sports tourism data fusion error is low. The management energy consumption is small, which significantly improves the existing problems and fully verifies the practical application value of the method.

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Section: Application Of Internet Of Things and Edgementioning

confidence: 99%

Application of Internet of Things and Edge Computing Technology in Sports Tourism Services

Zheng¹,

Mei

Hou

et al. 2021

Security and Communication Networks

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“…The simulation results validated proposed algorithms and proved that proposed algorithms outperform existing algorithms in term s of QoS and energy efficiency. A detailed study on 5G and IoT is undertaken in [33] to explore the various approaches used for addressing resource problems. These approaches are categorized, weakness and strengths of each approach is discussed along with similarities and differences between these approaches and future directions for resource allocation in 5G and IoT is provided.…”

Section: B Energy Optimization In 5gmentioning

confidence: 99%

Privacy Protection and Energy Optimization for 5G-Aided Industrial Internet of Things

et al. 2020

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The 5G is expected to revolutionize every sector of life by providing interconnectivity of everything everywhere at high speed. However, massively interconnected devices and fast data transmission will bring the challenge of privacy as well as energy deficiency. In today's fast-paced economy, almost every sector of the economy is dependent on energy resources. On the other hand, the energy sector is mainly dependent on fossil fuels and is constituting about 80% of energy globally. This massive extraction and combustion of fossil fuels lead to a lot of adverse impacts on health, environment, and economy. The newly emerging 5G technology has changed the existing phenomenon of life by connecting everything everywhere using IoT devices. 5G enabled IIoT devices has transformed everything from traditional to smart, e.g. smart city, smart healthcare, smart industry, smart manufacturing etc. However, massive I/O technologies for providing D2D connection has also created the issue of privacy that need to be addressed. Privacy is the fundamental right of every individual. 5G industries and organizations need to preserve it for their stability and competency. Therefore, privacy at all three levels (data, identity and location) need to be maintained. Further, energy optimization is a big challenge that needs to be addressed for leveraging the potential benefits of 5G and 5G aided IIoT. Billions of IIoT devices that are expected to communicate using the 5G network will consume a considerable amount of energy while energy resources are limited. Therefore, energy optimization is a future challenge faced by 5G industries that need to be addressed. To fill these gaps, we have provided a comprehensive framework that will help energy researchers and practitioners in better understanding of 5G aided industry 4.0 infrastructure and energy resource optimization by improving privacy. The proposed framework is evaluated using case studies and mathematical modelling.

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“…Due to the lengthy decision-making process, existing RRM algorithms struggle to work effectively in a dynamic network such as 5G and 6G. The authors in [16] mentioned that due to a large number of nodes in 5G networks, it is infeasible to use centralized algorithms because of high computational power and enormous cost. Therefore, enabling network nodes to make a decision based on local observation is highly preferable.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Techniques for 5G and Beyond

et al. 2021

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Wireless communication systems play a very crucial role in modern society for entertainment, business, commercial, health and safety applications. These systems keep evolving from one generation to next generation and currently we are seeing deployment of fifth generation (5G) wireless systems around the world. Academics and industries are already discussing beyond 5G wireless systems which will be sixth generation (6G) of the evolution. One of the main and key components of 6G systems will be the use of Artificial Intelligence (AI) and Machine Learning (ML) for such wireless networks. Every component and building block of a wireless system that we currently are familiar with from our knowledge of wireless technologies up to 5G, such as physical, network and application layers, will involve one or another AI/ML techniques. This overview paper, presents an up-to-date review of future wireless system concepts such as 6G and role of ML techniques in these future wireless systems. In particular, we present a conceptual model for 6G and show the use and role of ML techniques in each layer of the model. We review some classical and contemporary ML techniques such as supervised and un-supervised learning, Reinforcement Learning (RL), Deep Learning (DL) and Federated Learning (FL) in the context of wireless communication systems. We conclude the paper with some future applications and research challenges in the area of ML and AI for 6G networks. INDEX TERMS Fifth generation (5G), sixth generation (6G), artificial intelligence (AI), machine learning (ML), deep learning (DL), reinforcement learning (RL), federated learning (FL).

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Resource Optimisation in 5G and Internet-of-Things Networking

Cited by 35 publications

References 59 publications

Application of Internet of Things and Edge Computing Technology in Sports Tourism Services

Application of Internet of Things and Edge Computing Technology in Sports Tourism Services

Privacy Protection and Energy Optimization for 5G-Aided Industrial Internet of Things

Machine Learning Techniques for 5G and Beyond

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