scholarly journals Comparative Analysis of 5G Mobile Communication Network Architectures

2020 ◽  
Vol 10 (7) ◽  
pp. 2478 ◽  
Author(s):  
Woosik Lee ◽  
Eun Suk Suh ◽  
Woo Young Kwak ◽  
Hoon Han
Keyword(s):  
Cloud Computing ◽  
Mobile Communication ◽  
Network Architecture ◽  
Discrete Event ◽  
Autonomous Driving ◽  
Edge Computing ◽  
Handheld Devices ◽  
Network Architectures ◽  
Advantages And Disadvantages ◽  
Multi Access

Mobile communication technology is evolving from 4G to 5G. Compared to previous generations, 5G has the capability to implement latency-critical services, such as autonomous driving, real-time AI on handheld devices and remote drone control. Multi-access Edge Computing is one of the key technologies of 5G in guaranteeing ultra-low latency aimed to support latency critical services by distributing centralized computing resources to networks edges closer to users. However, due to its high granularity of computing resources, Multi-access Edge Computing has an architectural vulnerability in that it can lead to the overloading of regional computing resources, a phenomenon called regional traffic explosion. This paper proposes an improved communication architecture called Hybrid Cloud Computing, which combines the advantages of both Centralized Cloud Computing and Multi-access Edge Computing. The performance of the proposed network architecture is evaluated by utilizing a discrete-event simulation model. Finally, the results, advantages, and disadvantages of various network architectures are discussed.

scholarly journals ZONE-Based Multi-Access Edge Computing Scheme for User Device Mobility Management

2019 ◽  
Vol 9 (11) ◽  
pp. 2308 ◽  
Author(s):  
Juyong Lee ◽  
Daeyoub Kim ◽  
Jihoon Lee
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Mobility Management ◽  
Mobile Network ◽  
Edge Computing ◽  
Mobile Users ◽  
Long Distance ◽  
Cloud Server ◽  
Multi Access ◽  
User Device

Recently, new mobile applications and services have appeared thanks to the rapid development of mobile devices and mobile network technology. Cloud computing has played an important role over the past decades, providing powerful computing capabilities and high-capacity storage space to efficiently deliver these mobile services to mobile users. Nevertheless, existing cloud computing delegates computing to a cloud server located at a relatively long distance, resulting in significant delays due to additional time to return processing results from a cloud server. These unnecessary delays are inconvenient for mobile users because they are not suitable for applications that require a real-time service environment. To cope with these problems, a new computing concept called Multi-Access Edge Computing (MEC) has emerged. Instead of sending all requests to the central cloud to handle mobile users’ requests, the MEC brings computing power and storage resources to the edge of the mobile network. It enables the mobile user device to run the real-time applications that are sensitive to latency to meet the strict requirements. However, there is a lack of research on the efficient utilization of computing resources and mobility support when mobile users move in the MEC environment. In this paper, we propose the MEC-based mobility management scheme that arranges MEC server (MECS) as the concept of Zone so that mobile users can continue to receive content and use server resources efficiently even when they move. The results show that the proposed scheme reduce the average service delay compared to the existing MEC scheme. In addition, the proposed scheme outperforms the existing MEC scheme because mobile users can continuously receive services, even when they move frequently.

scholarly journals Optimising Differentiated Services Strategies under IMS

2018 ◽  
Vol 2 (3) ◽  
pp. 1-10
Author(s):  
David K. Osei-Aboagye ◽  
Peter S. Excell
Keyword(s):  
Mobile Communications ◽  
Network Architecture ◽  
Discrete Event ◽  
Differentiated Services ◽  
Main Concern ◽  
Network Architectures ◽  
Network Simulator ◽  
Core Network ◽  
Network Technologies

The evolving standards of mobile communications, the wide variety of services they offer and the rapid growth of the Internet have made a merger of the two network technologies inevitable. One of the most prominent platforms that has been developed to facilitate this is the IP Multimedia Subsystem (IMS) concept. Many mobile communications standards integrate IMS as the main core network architecture and Quality of Service (QoS) is the main concern for customer satisfaction. A major approach to optimisation of QoS is the Differentiated Services scheme, and a simulation study of implementations of this is presented. The study covered an IMS core network architecture modelled with discrete-event network simulator software, with a Differentiated Services QoS scheme run over it with differing bearer traffic scenarios. Implications for core network architectures are discussed.

scholarly journals Risk Control Management of New Rural Cooperative Financial Organizations Based on Mobile Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Fanrong Kong ◽  
Hongxia Lu
Keyword(s):  
Cloud Computing ◽  
Mutual Fund ◽  
Network Architecture ◽  
Financial Institution ◽  
Risk Control ◽  
Edge Computing ◽  
Experimental Simulation ◽  
Mobile Edge Computing ◽  
Financial Organization ◽  
Rural Enterprises

Rural cooperative financial organization is a new type of cooperative financial organization in recent years. It is a community financial institution created by farmers and small rural enterprises to voluntarily invest in shares in order to meet the growing demand for rural financing. However, this financial organization has many flaws in the design of the system; it has not promoted the better development of rural mutual fund assistance. In addition, mobile edge computing (MEC) can be used as an effective supplement to mobile cloud computing and has been proposed. However, most of the current literature studies on cloud computing provide computing offload just to propose a network architecture, without modeling and solving to achieve. In this context, this paper focuses on the practical application of MEC in the risk control of new rural cooperative financial organizations. This paper proposes a collaborative LECC mechanism based on machine learning under the MEC architecture. The experimental simulation shows that the HR under the LECC mechanism is about 17%–23%, 46%–69%, and 93%–177% higher than that of LENC, LRU, and RR, respectively. It is unrealistic to want to rely on meager loan interest for long-term development. The most practical way is to increase the income level of the organization itself.

scholarly journals A Review of Machine Learning Algorithms for Cloud Computing Security

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1379
Author(s):  
Umer Ahmed Butt ◽  
Muhammad Mehmood ◽  
Syed Bilal Hussain Shah ◽  
Rashid Amin ◽  
M. Waqas Shaukat ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Data Storage ◽  
Response Times ◽  
Edge Computing ◽  
Machine Learning Algorithms ◽  
Information Storage ◽  
Future Research ◽  
Computer Algorithms ◽  
Advantages And Disadvantages

Cloud computing (CC) is on-demand accessibility of network resources, especially data storage and processing power, without special and direct management by the users. CC recently has emerged as a set of public and private datacenters that offers the client a single platform across the Internet. Edge computing is an evolving computing paradigm that brings computation and information storage nearer to the end-users to improve response times and spare transmission capacity. Mobile CC (MCC) uses distributed computing to convey applications to cell phones. However, CC and edge computing have security challenges, including vulnerability for clients and association acknowledgment, that delay the rapid adoption of computing models. Machine learning (ML) is the investigation of computer algorithms that improve naturally through experience. In this review paper, we present an analysis of CC security threats, issues, and solutions that utilized one or several ML algorithms. We review different ML algorithms that are used to overcome the cloud security issues including supervised, unsupervised, semi-supervised, and reinforcement learning. Then, we compare the performance of each technique based on their features, advantages, and disadvantages. Moreover, we enlist future research directions to secure CC models.

scholarly journals Dynamic service migration in ultra-dense multi-access edge computing network for high-mobility scenarios

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Haowei Lin ◽  
Xiaolong Xu ◽  
Juan Zhao ◽  
Xinheng Wang
Keyword(s):  
Cloud Computing ◽  
Mobile Application ◽  
High Mobility ◽  
Edge Computing ◽  
The Other ◽  
Mobile Users ◽  
Computing Power ◽  
Service Migration ◽  
The Stability ◽  
Multi Access

Abstract The multi-access edge computing (MEC) has higher computing power and lower latency than user equipment and remote cloud computing, enabling the continuing emergence of new types of services and mobile application. However, the movement of users could induce service migration or interruption in the MEC network. Especially for highly mobile users, they accelerate the frequency of services’ migration and handover, impacting on the stability of the total MEC network. In this paper, we propose a hierarchical multi-access edge computing architecture, setting up the infrastructure for dynamic service migration in the ultra-dense MEC networks. Moreover, we propose a new mechanism for users with high mobility in the ultra-dense MEC network, efficiently arranging service migrations for users with high-mobility and ordinary users together. Then, we propose an algorithm for evaluating migrated services to contribute to choose the suitable MEC servers for migrated services. The results show that the proposed mechanism can efficiently arrange service migrations and more quickly restore the services even in the blockage. On the other hand, the proposed algorithm is able to make a supplement to the existing algorithms for selecting MEC servers because it can better reflect the capability of migrated services.

scholarly journals DSNet: an efficient CNN for road scene segmentation

2020 ◽  
Vol 9 ◽  
Author(s):  
Ping-Rong Chen ◽  
Hsueh-Ming Hang ◽  
Sheng-Wei Chan ◽  
Jing-Jhih Lin
Keyword(s):  
Real Time ◽  
Network Architecture ◽  
Autonomous Driving ◽  
High Accuracy ◽  
Neural Net ◽  
Scene Segmentation ◽  
Convolutional Network ◽  
Advantages And Disadvantages ◽  
Segmentation Accuracy ◽  
Very High

Road scene understanding is a critical component in an autonomous driving system. Although the deep learning-based road scene segmentation can achieve very high accuracy, its complexity is also very high for developing real-time applications. It is challenging to design a neural net with high accuracy and low computational complexity. To address this issue, we investigate the advantages and disadvantages of several popular convolutional neural network (CNN) architectures in terms of speed, storage, and segmentation accuracy. We start from the fully convolutional network with VGG, and then we study ResNet and DenseNet. Through detailed experiments, we pick up the favorable components from the existing architectures and at the end, we construct a light-weight network architecture based on the DenseNet. Our proposed network, called DSNet, demonstrates a real-time testing (inferencing) ability (on the popular GPU platform) and it maintains an accuracy comparable with most previous systems. We test our system on several datasets including the challenging Cityscapes dataset (resolution of 1024 × 512) with an Mean Intersection over Union (mIoU) of about 69.1% and runtime of 0.0147 s/image on a single GTX 1080Ti. We also design a more accurate model but at the price of a slower speed, which has an mIoU of about 72.6% on the CamVid dataset.

scholarly journals Distributed Edge Computing with Blockchain Technology to Enable Ultra -Reliable Low-Latency v2x Communications

2021 ◽  
Author(s):  
Andrei Vladyko ◽  
Vasiliy Elagin ◽  
Anastasia Spirkina ◽  
Ammar Muthanna ◽  
Abdelhamied A. Ateya
Keyword(s):  
Energy Efficient ◽  
Information Exchange ◽  
Network Architecture ◽  
Edge Computing ◽  
Low Latency ◽  
Mobile Edge Computing ◽  
Advantages And Disadvantages ◽  
Blockchain Technology ◽  
Road Users ◽  
Secure Information

As V2X technology develops, acute problems related to reliable and secure information exchange between network objects in real time appear. The article aims to solve the scientific problem of building a network architecture for reliable delivery of correct and uncompromised data within the V2X concept to improve the safety of road users, using blockchain technology and mobile edge computing (MEC). The authors present a formalized mathematical model of the system, taking into account the interconnection of objects and V2X information channels, and an energy-efficient algorithm of traffic offloading to the MEC server. The paper presents the results of application of blockchain technologies and mobile edge computing in the developed system, their description, evaluation of advantages and disadvantages of the implementation.

scholarly journals Dynamic Service Migration in Ultra-Dense Multi-Access Edge Computing network for High Mobility Scenarios

2020 ◽  
Author(s):  
Haowei Lin ◽  
Xiaolong Xu ◽  
Juan Zhao ◽  
Xinheng Wang
Keyword(s):  
Cloud Computing ◽  
Mobile Applications ◽  
High Mobility ◽  
Edge Computing ◽  
The Other ◽  
Mobile Users ◽  
Computing Power ◽  
Service Migration ◽  
The Stability ◽  
Multi Access

Abstract The Multi-Access Edge Computing (MEC) has higher computing power than user equipment and lower latency than remote cloud computing, making new types of services and mobile applications keep emerging. However, the movement of users could induce service migration or interruption in the MEC network. Especially for highly mobile users, they accelerate the frequency of services' migration and handover, impacting on the stability of the total MEC network. In this paper, we propose a hierarchical multi-access edge computing architecture, setting up the Infrastructure for dynamic service migration in the ultra-dense MEC networks. Moreover, we propose a new mechanism for users with high mobility in the ultra-dense MEC network, efficiently arranging service migrations for users with high mobility and ordinary users together. Then, we propose an algorithm for evaluating migrated services to contribute to choose the suitable MEC servers for migrated services. The results show that the proposed mechanism can efficiently arrange service migrations and more quickly restore the services even in the blockage. On the other hand, the proposed algorithm is able to make a supplement to the existing algorithms for selecting MEC servers because it can better reflect the capability of migrated services.

Transforming eMaintenance into iMaintenance with Mobile Communications Technologies and Handheld Devices

2013 ◽  
pp. 182-199 ◽  
Author(s):  
Nalin Sharda
Keyword(s):  
Cloud Computing ◽  
Mobile Communication ◽  
Mobile Communications ◽  
Communication Technologies ◽  
Handheld Devices ◽  
Intelligent Computing ◽  
Digital Ecosystem ◽  
Communications Technologies ◽  
Computer Based ◽  
Software Services

iMaintenance stands for integrated, intelligent and immediate maintenance; which can be made possible by integrating various maintenance functions, and connecting these to handheld devices, such as an iPhone, using mobile communication technologies. The main innovation required for developing iMaintenance systems is to integrate the disparate systems and capabilities developed under the current eMaintenance models, and to make these immediately accessible by ubiquitous and intelligent computing technologies –such as Digital Ecosystems and Cloud Computing– connected via wireless networks and handheld devices such as the iPhone. A Digital Ecosystem is a computer-based system that can evolve with the system that it monitors and controls, and can be embedded in the system’s components, thereby providing the ability to integrate new functionality without any downtime. Cloud Computing can provide access to additional software services that are not available in the local Digital Ecosystem. This chapter will show how these computing paradigms can provide mobile computing and communication facilities required to create novel iMaintenance systems.

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