scholarly journals Edge Network Routing Protocol Base on Target Tracking Scenario

2021 ◽  
Author(s):  
Zhongyi Zhang ◽  
Weihua Zhao ◽  
Ouhan Huang ◽  
Gangyong Jia ◽  
Youhuizi Li ◽  
...  
Keyword(s):  
Target Tracking ◽  
Network Architecture ◽  
Sampling Period ◽  
Network Routing ◽  
Edge Computing ◽  
Communication Overhead ◽  
Edge Network ◽  
Computing Centers ◽  
End Node ◽  
Individual Node

AbstractEdge computing perfectly integrates cloud computing centers and edge-end devices together, but there are not many related researches on how the edge-end node devices work to form an edge network and what the protocols used to implement the communication among nodes in the edge network. Aiming at the problem of coordinated communication among edge nodes in the current edge computing network architecture, this paper proposes an edge network routing and forwarding protocol based on target tracking scenarios. This protocol can meet the dynamic changes of node locations, and the elastic expansion of node scale. Individual node failures will not affect the overall network, and the network ensures efficient real-time with less communication overhead. The experimental results display that the protocol can effectively reduce the communications volume of the edge network, improve the overall efficiency of the network, and set the optimal sampling period, so as to ensure that the network delay is minimized.

scholarly journals Mobile English Teaching Information Service Platform Based on Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Tingyu Jiao
Keyword(s):  
Learning Theory ◽  
Network Architecture ◽  
Information Service ◽  
Edge Computing ◽  
Service Platform ◽  
English Teaching ◽  
Edge Network ◽  
Teachers And Students ◽  
Cognition And Learning ◽  
Teaching Information

Mobile edge computing was born in 2013 and is still in the process of technology R&D and industrialization. Although it is still in the early stages of development, as one of the core technologies of 5G, it has broad development prospects; this article aims to study the design and implementation of a mobile English teaching information service platform under edge computing, so as to improve the efficiency and level of English teaching. The implication of mobile English teaching is that English teachers and students use mobile devices for English teaching and communication at the same time. This article mainly focuses on the research of mobile English teaching information service platform based on edge computing. It discusses edge computing model and edge network architecture and is based on cognitive flexibility theory, informal learning theory, and situational cognition and learning theory. A mobile English teaching model based on “listening, reading, and listening” is constructed, and a mobile English teaching information service platform is designed and implemented. After investigation and research, it is concluded that this platform can improve the efficiency of teacher scheduling by 5%–6% and the student’s 2-3% course selection efficiency.

Implementation of MQTT protocol based network architecture for smart factory

2021 ◽  
pp. 095440542110144
Author(s):  
Chia-Shin Yeh ◽  
Shang-Liang Chen ◽  
I-Ching Li
Keyword(s):  
Machine Tool ◽  
Gesture Recognition ◽  
Manufacturing Process ◽  
Network Architecture ◽  
Information Management System ◽  
Edge Computing ◽  
Smart Factory ◽  
Smart Manufacturing ◽  
Industrial Iot ◽  
Computing Module

The core concept of smart manufacturing is based on digitization to construct intelligent production and management in the manufacturing process. By digitizing the production process and connecting all levels from product design to service, the purpose of improving manufacturing efficiency, reducing production cost, enhancing product quality, and optimizing user experience can be achieved. To digitize the manufacturing process, IoT technology will have to be introduced into the manufacturing process to collect and analyze process information. However, one of the most important problems in building the industrial IoT (IIoT) environment is that different industrial network protocols are used for different equipment in factories. Therefore, the information in the manufacturing process may not be easily exchanged and obtained. To solve the above problem, a smart factory network architecture based on MQTT (MQ Telemetry Transport), IoT communication protocol, is proposed in this study, to construct a heterogeneous interface communication bridge between the machine tool, embedded device Raspberry Pi, and website. Finally, the system architecture is implemented and imported into the factory, and a smart manufacturing information management system is developed. The edge computing module is set up beside a three-axis machine tool, and a human-machine interface is built for the user controlling and monitoring. Users can also monitor the system through the dynamically updating website at any time and any place. The function of real-time gesture recognition based on image technology is developed and built on the edge computing module. The gesture recognition results can be transmitted to the machine controller through MQTT, and the machine will execute the corresponding action according to different gestures to achieve human-robot collaboration. The MQTT transmission architecture developed here is validated by the given edge computing application. It can serve as the basis for the construction of the IIoT environment, assist the traditional manufacturing industry to prepare for digitization, and accelerate the practice of smart manufacturing.

scholarly journals An edge based hybrid intrusion detection framework for mobile edge computing

2021 ◽  
Author(s):  
Ashish Singh ◽  
Kakali Chatterjee ◽  
Suresh Chandra Satapathy
Keyword(s):  
Intrusion Detection ◽  
Real Time ◽  
Network Architecture ◽  
Denial Of Service ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Hybrid Detection ◽  
Game Theoretical Approach ◽  
Improved Performance ◽  
Edge Based

AbstractThe Mobile Edge Computing (MEC) model attracts more users to its services due to its characteristics and rapid delivery approach. This network architecture capability enables users to access the information from the edge of the network. But, the security of this edge network architecture is a big challenge. All the MEC services are available in a shared manner and accessed by users via the Internet. Attacks like the user to root, remote login, Denial of Service (DoS), snooping, port scanning, etc., can be possible in this computing environment due to Internet-based remote service. Intrusion detection is an approach to protect the network by detecting attacks. Existing detection models can detect only the known attacks and the efficiency for monitoring the real-time network traffic is low. The existing intrusion detection solutions cannot identify new unknown attacks. Hence, there is a need of an Edge-based Hybrid Intrusion Detection Framework (EHIDF) that not only detects known attacks but also capable of detecting unknown attacks in real time with low False Alarm Rate (FAR). This paper aims to propose an EHIDF which is mainly considered the Machine Learning (ML) approach for detecting intrusive traffics in the MEC environment. The proposed framework consists of three intrusion detection modules with three different classifiers. The Signature Detection Module (SDM) uses a C4.5 classifier, Anomaly Detection Module (ADM) uses Naive-based classifier, and Hybrid Detection Module (HDM) uses the Meta-AdaboostM1 algorithm. The developed EHIDF can solve the present detection problems by detecting new unknown attacks with low FAR. The implementation results illustrate that EHIDF accuracy is 90.25% and FAR is 1.1%. These results are compared with previous works and found improved performance. The accuracy is improved up to 10.78% and FAR is reduced up to 93%. A game-theoretical approach is also discussed to analyze the security strength of the proposed framework.

Importance of Cloud Computing in 5G Radio Access Networks

2020 ◽  
pp. 255-268
Author(s):  
Wael S. Afifi ◽  
Ali A. El-Moursy ◽  
Mohamed Saad ◽  
Salwa M. Nassar ◽  
Hadia M. El-Hennawy
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Network Architecture ◽  
Access Networks ◽  
Multimedia Services ◽  
Fifth Generation ◽  
Radio Access ◽  
Data Rates ◽  
Computing Centers

The fifth generation of wireless networks (5G) will kick off with evolved mobile broadband services as promised by several mobile-related associations, researchers, and operators. Compared to 4G, 5G aims to provide greater data rates with lower latency and higher coverage to numerous users who stream ubiquitous multimedia services. 5G benefits the innovation of internet of things (IoT) as well. To this end, several modifications in the network architecture are required. This chapter is discussing the role of cloud computing centers in 5G networks, and how such integration could be implemented as found in the literature. The benefits of cloud/5G integration will be explained as well. In addition, some challenges related to the integration will be demonstrated.

Importance of Cloud Computing in 5G Radio Access Networks

2021 ◽  
pp. 226-239
Author(s):  
Wael S. Afifi ◽  
Ali A. El-Moursy ◽  
Mohamed Saad ◽  
Salwa M. Nassar ◽  
Hadia M. El-Hennawy
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Network Architecture ◽  
Access Networks ◽  
Multimedia Services ◽  
Fifth Generation ◽  
Radio Access ◽  
Data Rates ◽  
Computing Centers

The fifth generation of wireless networks (5G) will kick off with evolved mobile broadband services as promised by several mobile-related associations, researchers, and operators. Compared to 4G, 5G aims to provide greater data rates with lower latency and higher coverage to numerous users who stream ubiquitous multimedia services. 5G benefits the innovation of internet of things (IoT) as well. To this end, several modifications in the network architecture are required. This chapter is discussing the role of cloud computing centers in 5G networks, and how such integration could be implemented as found in the literature. The benefits of cloud/5G integration will be explained as well. In addition, some challenges related to the integration will be demonstrated.

scholarly journals ARS: Adaptive Robust Synchronization for Underground Coal Wireless Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4981
Author(s):  
Kuiyuan Zhang ◽  
Mingzhi Pang ◽  
Yuqing Yin ◽  
Shouwan Gao ◽  
Pengpeng Chen
Keyword(s):  
Internet Of Things ◽  
Clock Synchronization ◽  
Sampling Period ◽  
Upper And Lower Bounds ◽  
Communication Overhead ◽  
Wireless Internet ◽  
Robust Synchronization ◽  
Time Stamps ◽  
Communication Links ◽  
Incomplete Measurement

Clock synchronization is still a vital and challenging task for underground coal wireless internet of things (IoT) due to the uncertainty of underground environment and unreliability of communication links. Instead of considering on-demand driven clock synchronization, this paper proposes a novel Adaptive Robust Synchronization (ARS) scheme with packets loss for mine wireless environment. A clock synchronization framework that is based on Kalman filtering is first proposed, which can adaptively adjust the sampling period of each clock and reduce the communication overhead in single-hop networks. The proposed scheme also solves the problem of outliers in data packets with time-stamps. In addition, this paper extends the ARS algorithm to multi-hop networks. Additionally, the upper and lower bounds of error covariance expectation are analyzed in the case of incomplete measurement. Extensive simulations are conducted in order to evaluate the performance. In the simulation environment, the clock accuracy of ARS algorithm is improved by 7.85% when compared with previous studies for single-hop networks. For multi-hop networks, the proposed scheme improves the accuracy by 12.56%. The results show that the proposed algorithm has high scalability, robustness, and accuracy, and can quickly adapt to different clock accuracy requirements.

scholarly journals A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation

2021 ◽  
Vol 20 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Yuris Mulya Saputra ◽  
Dinh Thai Hoang ◽  
Diep N. Nguyen ◽  
Eryk Dutkiewicz
Keyword(s):  
Network Architecture ◽  
Horizontal Cooperation ◽  
Edge Network

scholarly journals Review of the D2D Trusted Cooperative Mechanism in Mobile Edge Computing

Information ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 259 ◽  
Author(s):  
Jie Yuan ◽  
Erxia Li ◽  
Chaoqun Kang ◽  
Fangyuan Chang ◽  
Xiaoyong Li
Keyword(s):  
Cellular Networks ◽  
Mobile Networks ◽  
Network Architecture ◽  
Social Trust ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Internet Technologies ◽  
Architecture Model ◽  
Security Issues ◽  
Cooperative Relationship

Mobile edge computing (MEC) effectively integrates wireless network and Internet technologies and adds computing, storage, and processing functions to the edge of cellular networks. This new network architecture model can deliver services directly from the cloud to the very edge of the network while providing the best efficiency in mobile networks. However, due to the dynamic, open, and collaborative nature of MEC network environments, network security issues have become increasingly complex. Devices cannot easily ensure obtaining satisfactory and safe services because of the numerous, dynamic, and collaborative character of MEC devices and the lack of trust between devices. The trusted cooperative mechanism can help solve this problem. In this paper, we analyze the MEC network structure and device-to-device (D2D) trusted cooperative mechanism and their challenging issues and then discuss and compare different ways to establish the D2D trusted cooperative relationship in MEC, such as social trust, reputation, authentication techniques, and intrusion detection. All these ways focus on enhancing the efficiency, stability, and security of MEC services in presenting trustworthy services.

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