scholarly journals Artificial Intelligence and Machine Learning in 5G and beyond: A Survey and Perspectives

2021 ◽  
Author(s):  
Abdelfatteh Haidine ◽  
Fatima Zahra Salmam ◽  
Abdelhak Aqqal ◽  
Aziz Dahbi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Mobile Networks ◽  
Network Architecture ◽  
Mobile Network ◽  
Cost Effective ◽  
Mobile Internet ◽  
Network Function ◽  
New Radio ◽  
4G Lte

The deployment of 4G/LTE (Long Term Evolution) mobile network has solved the major challenge of high capacities, to build real broadband mobile Internet. This was possible mainly through very strong physical layer and flexible network architecture. However, the bandwidth hungry services have been developed in unprecedented way, such as virtual reality (VR), augmented reality (AR), etc. Furthermore, mobile networks are facing other new services with extremely demand of higher reliability and almost zero-latency performance, like vehicle communications or Internet-of-Vehicles (IoV). Using new radio interface based on massive MIMO, 5G has overcame some of these challenges. In addition, the adoption of software defend networks (SDN) and network function virtualization (NFV) has added a higher degree of flexibility allowing the operators to support very demanding services from different vertical markets. However, network operators are forced to consider a higher level of intelligence in their networks, in order to deeply and accurately learn the operating environment and users behaviors and needs. It is also important to forecast their evolution to build a pro-actively and efficiently (self-) updatable network. In this chapter, we describe the role of artificial intelligence and machine learning in 5G and beyond, to build cost-effective and adaptable performing next generation mobile network. Some practical use cases of AI/ML in network life cycle are discussed.

An overview of the 5G mobile network architecture

2018 ◽  
Author(s):  
Phanidra Palagummi ◽  
Vedant Somani ◽  
Krishna M. Sivalingam ◽  
Balaji Venkat
Keyword(s):  
Wireless Network ◽  
Mobile Networks ◽  
Network Architecture ◽  
Mobile Network ◽  
Communication Technologies ◽  
Future Generation ◽  
Network Function Virtualization ◽  
Low Latency ◽  
High Bandwidth ◽  
Network Technologies

Networking connectivity is increasingly based on wireless network technologies, especially in developing nations where the wired network infrastructure is not accessible to a large segment of the population. Wireless data network technologies based on 2G and 3G are quite common globally; 4G-based deployments are on the rise during the past few years. At the same time, the increasing high-bandwidth and low-latency requirements of mobile applications has propelled the Third Generation Partnership Project (3GPP) standards organization to develop standards for the next generation of mobile networks, based on recent advances in wireless communication technologies. This standard is called the Fifth Generation (5G) wireless network standard. This paper presents a high-level overview of the important architectural components, of the advanced communication technologies, of the advanced networking technologies such as Network Function Virtualization and other important aspects that are part of the 5G network standards. The paper also describes some of the common future generation applications that require low-latency and high-bandwidth communications.

scholarly journals Urban living environment assessment index system based on psychological security

2019 ◽  
Author(s):  
Xia Huiyi ◽  
◽  
Nankai Xia ◽  
Liu Liu ◽  
◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Collection ◽  
Urban Environment ◽  
Evaluation System ◽  
Living Environment ◽  
Mobile Internet ◽  
Practical Significance ◽  
Human Beings ◽  
Urban Living

With the development of urbanization and the continuous development, construction and renewal of the city, the living environment of human beings has also undergone tremendous changes, such as residential community environment and service facilities, urban roads and street spaces, and urban public service formats. And the layout of the facilities, etc., and these are the real needs of people in urban life, but the characteristics of these needs or their problems will inevitably have a certain impact on the user's psychological feelings, thus affecting people's use needs. Then, studying the ways in which urban residents perceive changes in the living environment and how they perceive changes in psychology and emotions will have practical significance and can effectively assist urban management and builders to optimize the living environment of residents. This is also the long-term. One of the topics of greatest interest to urban researchers since then. In the theory of demand hierarchy proposed by American psychologist Abraham Maslow, safety is the basic requirement second only to physiological needs. So safety, especially psychological security, has become one of the basic needs of people in the urban environment. People's perception of the psychological security of the urban environment is also one of the most important indicators in urban environmental assessment. In the past, due to the influence of technical means, the study of urban environmental psychological security often relied on the limited investigation of a small number of respondents. Low-density data is difficult to measure the perceptual results of universality. With the leaping development of the mobile Internet, Internet image data has grown geometrically over time. And with the development of artificial intelligence technology in recent years, image recognition and perception analysis based on machine learning has become possible. The maturity of these technical conditions provides a basis for the study of the urban renewal index evaluation system based on psychological security. In addition to the existing urban visual street furniture data obtained through urban big data collection combined with artificial intelligence image analysis, this paper also proposes a large number of urban living environment psychological assessment data collection strategies. These data are derived from crowdsourcing, and the collection method is limited by the development of cost and technology. At present, the psychological security preference of a large number of users on urban street images is collected by forced selection method, and then obtained by statistical data fitting to obtain urban environmental psychology. Security sense training set. In the future, when the conditions are mature, the brainwave feedback data in the virtual reality scene can be used to carry out the machine learning of psychological security, so as to improve the accuracy of the psychological security data.

scholarly journals Network Amelioration, AI Automation and Future Integration in Wireless Networks

2021 ◽  
Vol 9 (8) ◽  
pp. 2607-2613
Author(s):  
Marzook Khatri
Keyword(s):  
Artificial Intelligence ◽  
Communication Networks ◽  
Mobile Networks ◽  
Network Virtualization ◽  
Mobile Network ◽  
Data Access ◽  
Detailed Comparison ◽  
Mobile Industry ◽  
Generation Network ◽  
Network Operations

Abstract: The deployment of 5G mobile communication networks is just getting started right now. There are numerous technologies available today, each capable of fulfilling activities such as enabling voice traffic via voice over IP (VoIP), providing broadband data access in mobile environments, and so on. However, there is a pressing need to implement technology that can bring all of these systems together into a single unified system. Because it is all about smoothly integrating terminals, networks, and applications, 8G presents a solution to this dilemma. In this work, an attempt is made to provide a study of various cellular technologies, such as 4G, 5G, 6G, 7G, and FG, as well as a detailed comparison between them. With the introduction of network virtualization and the implementation of 5G/IoT, mobile networks will become more complicated and offer more diverse services. This raises concerns about a considerable increase in the workload of network operations. Meanwhile, artificial intelligence (AI) is advancing rapidly and is projected to alleviate human resource shortages in a variety of industries. Similarly, the mobile industry is gaining traction in the application of artificial intelligence (AI) to network operations in order to improve the efficiency of mobile network operations. This paper will address the idea of using AI technology to network operations and will give various use examples to demonstrate that AI-driven network operations have a bright future. Keywords: 5G & 6G networks, Artificial Intelligence, Next generation network, Future Advancement.

A robust intrusion detection system using machine learning techniques for MANET

2020 ◽  
Vol 24 (3) ◽  
pp. 253-260
Author(s):  
N. Ravi ◽  
G. Ramachandran
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Mobile Computing ◽  
Mobile Networks ◽  
Intrusion Detection System ◽  
Detection System ◽  
Mobile Network ◽  
Machine Learning Techniques ◽  
Test Bed ◽  
Learning Techniques

Recent advancement in technologies such as Cloud, Internet of Things etc., leads to the increase usage of mobile computing. Present day mobile computing are too sophisticated and advancement are reaching great heights. Moreover, the present day mobile network suffers due to external and internal intrusions within and outside networks. The existing security systems to protect the mobile networks are incapable to detect the recent attacks. Further, the existing security system completely depends on the traditional signature and rule based approaches. Recent attacks have the property of not fluctuating its behaviour during attack. Hence, a robust Intrusion Detection System (IDS) is desirable. In order to address the above mentioned issue, this paper proposed a robust IDS using Machine Learning Techniques (MLT). The key of using MLT is to utilize the power of ensembles. The ensembles of classifier used in this paper are Random Forest (RF), KNN, Naïve Bayes (NB), etc. The proposed IDS is experimentally tested and validated using a secure test bed. The experimental results also confirms that the proposed IDS is robust enough to withstand and detect any form of intrusions and it is also noted that the proposed IDS outperforms the state of the art IDS with more than 95% accuracy.

scholarly journals Framework towards the Process of Estimating or Predicting Perceived QoE Based on the Datasets Obtained the Mobile Network

2019 ◽  
Vol 9 (2) ◽  
pp. 3627-3631
Keyword(s):  
Artificial Intelligence ◽  
Consumer Satisfaction ◽  
Quality Of Experience ◽  
Research Study ◽  
Mobile Network ◽  
Mobile Internet ◽  
Software Defined Network ◽  
Network Functionality ◽  
Mobile Network Operators

Nowadays, the research study community visualizes a standard shift that is going to put the focus on Quality of Experience metrics, which relate directly to complete consumer satisfaction. Yet, determining QoE coming from QoS sizes is a daunting job that powerful Software Defined Network operators are currently able to tackle through artificial intelligence strategies. In this paper, our experts pay attention to a few essential QoE factors, and we to begin with proposing a Bayesian Network design to anticipate re-buffering proportion. This paper suggested a structure for modeling mobile network QoE, making use of the vast records analytics approach. The planned platform explains the method of estimating or forecasting perceived QoE based upon the datasets obtained or collected from the mobile network to enable the mobile network operators efficiently to deal with the network functionality as well as supply the individuals an adequate mobile Internet QoE.

scholarly journals A machine learning-based system for detecting leishmaniasis in microscopic images

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Mojtaba Zare ◽  
Hossein Akbarialiabad ◽  
Hossein Parsaei ◽  
Qasem Asgari ◽  
Ali Alinejad ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Visual Detection ◽  
Detection System ◽  
Cost Effective ◽  
Leishmania Parasite ◽  
Parasitic Disease ◽  
Integral Image ◽  
Parasite Detection ◽  
Image Creation

Abstract Background Leishmaniasis, a disease caused by a protozoan, causes numerous deaths in humans each year. After malaria, leishmaniasis is known to be the deadliest parasitic disease globally. Direct visual detection of leishmania parasite through microscopy is the frequent method for diagnosis of this disease. However, this method is time-consuming and subject to errors. This study was aimed to develop an artificial intelligence-based algorithm for automatic diagnosis of leishmaniasis. Methods We used the Viola-Jones algorithm to develop a leishmania parasite detection system. The algorithm includes three procedures: feature extraction, integral image creation, and classification. Haar-like features are used as features. An integral image was used to represent an abstract of the image that significantly speeds up the algorithm. The adaBoost technique was used to select the discriminate features and to train the classifier. Results A 65% recall and 50% precision was concluded in the detection of macrophages infected with the leishmania parasite. Also, these numbers were 52% and 71%, respectively, related to amastigotes outside of macrophages. Conclusion The developed system is accurate, fast, easy to use, and cost-effective. Therefore, artificial intelligence might be used as an alternative for the current leishmanial diagnosis methods.

scholarly journals Effects of fixed and roaming CN on MIPv6 networks

2017 ◽  
Vol 7 (3) ◽  
pp. 145-152
Author(s):  
Papa Djassi
Keyword(s):  
Mobile Networks ◽  
Mobile Network ◽  
Mobile Internet ◽  
Mobile Nodes ◽  
Foreign Agent ◽  
Mobile Internet Protocol ◽  
Ipv6 Network ◽  
Correspondent Node ◽  
Handover Process ◽  
Better Than

Mobile Internet protocol version 6 (MIPv6) is a protocol that allows mobile nodes (MNs) to remain accessible while moving in the IPv6 network, providing users with a form of transparency in spite of the mobility. Mobile networks consist of different nodes such as the MN, correspondent node (CN), home agent (HA), foreign agent or router (FA or FR) and mobile router (MR). One of the vital nodes in a mobile network is CN, a node that communicates with the MN. In the future, in times of need, for instance, during wars, disasters or natural hazards, an MN may require the services of a CN in order to roam. In this paper, we analyse the effect of fixed and roaming CN on MIPv6 networks. The results show that, with a fixed CN, the delay variation performance, end-to-end delay and packet received are better than having a roaming CN in the mobile networks. This requires the attention of researchers, especially when all the communicating nodes (i.e., MN and CN) are roaming in the mobile networks to reduce the delay and packet drop, especially during the handover process. Keywords: MIPv6, fixed CN, roaming CN, MN, HA and FA.      

scholarly journals Network Selection Strategies and Resource Management Schemes in Integrated Heterogeneous Wireless and Mobile Networks

2010 ◽  
pp. 1066-1083
Author(s):  
Wei Shen ◽  
Qing-An Zeng
Keyword(s):  
Resource Management ◽  
Mobile Networks ◽  
Network Architecture ◽  
Mobile Network ◽  
Network Selection ◽  
Selection Strategies ◽  
Different Types ◽  
Management Schemes ◽  
Strong Candidate ◽  
Multiple Network

Integrated heterogeneous wireless and mobile network (IHWMN) is introduced by combing different types of wireless and mobile networks (WMNs) in order to provide more comprehensive service such as high bandwidth with wide coverage. In an IHWMN, a mobile terminal equipped with multiple network interfaces can connect to any available network, even multiple networks at the same time. The terminal also can change its connection from one network to other networks while still keeping its communication alive. Although IHWMN is very promising and a strong candidate for future WMNs, it brings a lot of issues because different types of networks or systems need to be integrated to provide seamless service to mobile users. In this chapter, the authors focus on some major issues in IHWMN. Several noel network selection strategies and resource management schemes are also introduced for IHWMN to provide better resource allocation for this new network architecture.

scholarly journals Network Selection Strategies and Resource Management Schemes in Integrated Heterogeneous Wireless and Mobile Networks

2010 ◽  
pp. 718-737
Author(s):  
Wei Shen ◽  
Qing-An Zeng
Keyword(s):  
Resource Management ◽  
Mobile Networks ◽  
Network Architecture ◽  
Mobile Network ◽  
Network Selection ◽  
Selection Strategies ◽  
Different Types ◽  
Management Schemes ◽  
Strong Candidate ◽  
Multiple Network

Integrated heterogeneous wireless and mobile network (IHWMN) is introduced by combing different types of wireless and mobile networks (WMNs) in order to provide more comprehensive service such as high bandwidth with wide coverage. In an IHWMN, a mobile terminal equipped with multiple network interfaces can connect to any available network, even multiple networks at the same time. The terminal also can change its connection from one network to other networks while still keeping its communication alive. Although IHWMN is very promising and a strong candidate for future WMNs, it brings a lot of issues because different types of networks or systems need to be integrated to provide seamless service to mobile users. In this chapter, the authors focus on some major issues in IHWMN. Several noel network selection strategies and resource management schemes are also introduced for IHWMN to provide better resource allocation for this new network architecture.

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