scholarly journals 5G Cross-Border Operation for Connected and Automated Mobility: Challenges and Solutions

2019 ◽  
Vol 12 (1) ◽  
pp. 5 ◽  
Author(s):  
Apostolos Kousaridas ◽  
Andreas Schimpe ◽  
Sebastian Euler ◽  
Xavier Vilajosana ◽  
Mikael Fallgren ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Autonomous Vehicles ◽  
Communication Technologies ◽  
Mobile Edge Computing ◽  
High Definition ◽  
Qos Prediction ◽  
Cross Border ◽  
Map Generation ◽  
Data Connection

The vision of cooperative, connected and automated mobility (CCAM) across Europe can only be realized when harmonized solutions that support cross-border traffic exist. The possibility of providing CCAM services along different countries when vehicles drive across various national borders has a huge innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of services along borders also poses interesting technical challenges. The situation is particularly innovative given the multi-country, multi-operator, multi-telco-vendor, and multi-car-manufacturer scenario of any cross-border layout. This paper introduces the challenges associated to a cross-border deployment of communication technologies through the analysis of three use cases: tele-operated driving, high-definition map generation and distribution for autonomous vehicles, and anticipated cooperative collision avoidance. Furthermore, a set of 5G solutions have been identified to ensure that CCAM services can be supported efficiently in cross-border scenarios. Faster handover of a data connection from one operator to another, generalized inter-mobile edge computing (MEC) coordination, and quality of service (QoS) prediction are some of the solutions that have been introduced to reduce the uncertainties of a real 5G cross-border deployment.

A Trust Based Secure and Privacy Aware Framework for Efficient Taxi and Car Sharing System

2018 ◽  
Vol 2 (1) ◽  
pp. 34-47 ◽  
Author(s):  
Oladayo Olakanmi ◽  
Sekoni Oluwaseun
Keyword(s):  
Quality Of Service ◽  
Service Delivery ◽  
Private Information ◽  
Autonomous Vehicles ◽  
Trust Model ◽  
Security And Privacy ◽  
Car Sharing ◽  
Perfect Model ◽  
Taxi Service

This article describes how taxi service is an essential means of mobility in many cities. Recent findings show that average automobile owners utilize their vehicles for only 5% of its time in a day. Therefore, the advent of autonomous vehicles and car sharing will make it possible for owners to engage their vehicles as taxis when not in use by utilizing its 95% free time for income generation. Sensitive private information is required to be released during a taxi service delivery, which may bring certain security and privacy issues and challenges. This may hinder the prospect of using autonomous vehicles as a form of taxi. As a result of these, the authors propose a secure and privacy-preserving taxi service framework for car sharing, which ensures protection of car owner and passengers personal details, e.g. identity, location, destination, etc. The authors developed a decay-based trust model for a framework in order to monitor and improve the quality of service rendered to passengers by vehicles. The decay-based trust model was simulated on the framework. The simulation of the decay-based trust model shows that it is a perfect model for rewarding vehicles which render good quality of service and blacklisting vehicles with frequent poor service delivery.

scholarly journals Design and Implementation of Edge-Fog-Cloud System through HD Map Generation from LiDAR Data of Autonomous Vehicles

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2084
Author(s):  
Junwon Lee ◽  
Kieun Lee ◽  
Aelee Yoo ◽  
Changjoo Moon
Keyword(s):  
Real Time ◽  
Autonomous Vehicles ◽  
Fog Computing ◽  
Point Clouds ◽  
Lidar Data ◽  
High Definition ◽  
Localization And Mapping ◽  
Cloud Server ◽  
Map Generation ◽  
Self Driving Cars

Self-driving cars, autonomous vehicles (AVs), and connected cars combine the Internet of Things (IoT) and automobile technologies, thus contributing to the development of society. However, processing the big data generated by AVs is a challenge due to overloading issues. Additionally, near real-time/real-time IoT services play a significant role in vehicle safety. Therefore, the architecture of an IoT system that collects and processes data, and provides services for vehicle driving, is an important consideration. In this study, we propose a fog computing server model that generates a high-definition (HD) map using light detection and ranging (LiDAR) data generated from an AV. The driving vehicle edge node transmits the LiDAR point cloud information to the fog server through a wireless network. The fog server generates an HD map by applying the Normal Distribution Transform-Simultaneous Localization and Mapping(NDT-SLAM) algorithm to the point clouds transmitted from the multiple edge nodes. Subsequently, the coordinate information of the HD map generated in the sensor frame is converted to the coordinate information of the global frame and transmitted to the cloud server. Then, the cloud server creates an HD map by integrating the collected point clouds using coordinate information.

scholarly journals NFVMon: Enabling Multioperator Flow Monitoring in 5G Mobile Edge Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Enrique Chirivella-Perez ◽  
Juan Gutiérrez-Aguado ◽  
Jose M. Alcaraz-Calero ◽  
Qi Wang
Keyword(s):  
Mobile Networks ◽  
Communication Systems ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
High Definition ◽  
Flow Monitoring ◽  
Fifth Generation ◽  
New Generation ◽  
Monitoring Architecture

With the advances of new-generation wireless and mobile communication systems such as the fifth-generation (5G) mobile networks and Internet of Things (IoT) networks, demanding applications such as Ultra-High-Definition video applications is becoming ever popular. These applications require real-time monitoring and processing to meet the mission-critical quality of service requirements and are expected to be supported by the emerging fog or edge computing paradigms. This paper presents NFVMon, a novel monitoring architecture to enable flow monitoring capabilities of network traffic in a 5G multioperator mobile edge computing environment. The proposed NFVMon is integrated with the management plane of the Cloud Computing. NFVMon has been prototyped and a reference implementation is presented. It provides novel capabilities to provide disaggregated metrics related to the different 5G mobile operators sharing infrastructures and also about the different 5G subscribers of each of such mobile operators. Extensive experiments for evaluating the performance of the system have been conducted on a mid-sized infrastructure testbed.

Privacy-Aware Forecasting of Quality of Service in Mobile Edge Computing

2021 ◽  
pp. 1-1
Author(s):  
Huiying Jin ◽  
Pengcheng Zhang ◽  
Hai Dong ◽  
Yuelong Zhu ◽  
Athman Bouguettaya
Keyword(s):  
Quality Of Service ◽  
Edge Computing ◽  
Mobile Edge Computing

The Application and Research of CATV Communication Technology in the Field of Electricity Consumption Information Collection in China

2013 ◽  
Vol 834-836 ◽  
pp. 974-981
Author(s):  
Xiao Hui Song ◽  
Fan Tao Lin ◽  
Jing Fen Bai ◽  
Xiang Jiang Yang
Keyword(s):  
Communication Network ◽  
Quality Of Service ◽  
Communication Technology ◽  
Electricity Consumption ◽  
Communication Technologies ◽  
Information Collection ◽  
Security Architecture ◽  
Collection System ◽  
Bidirectional Communication

This paper presents the application of bidirectional communication technology of CATV in Electricity Consumption Information Collection System (ECICS), analyses the architecture of bidirectional communication technology and the communication technologies to improve the quality of service, describes the physical architecture, security architecture and system functions of ECICS based on CATV communication network .

scholarly journals 5G connected and automated driving: use cases, technologies and trials in cross-border environments

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Dirk Hetzer ◽  
Maciej Muehleisen ◽  
Apostolos Kousaridas ◽  
Sokratis Barmpounakis ◽  
Stefan Wendt ◽  
...  
Keyword(s):  
European Commission ◽  
Collision Avoidance ◽  
Use Cases ◽  
Automated Driving ◽  
High Definition ◽  
Cross Border ◽  
Total Budget ◽  
Map Generation ◽  
5G Technologies ◽  
Initial Results

AbstractCooperative, connected and automated mobility (CCAM) across Europe requires harmonized solutions to support cross-border seamless operation. The possibility of providing CCAM services across European countries has an enormous innovative business potential. However, the seamless provision of connectivity and the uninterrupted delivery of real-time services pose technical challenges which 5G technologies aim to solve. The situation is particularly challenging given the multi-country, multi-operator, multi-telco-vendor, multi-car-manufacturer and cross-network-generation scenario of any cross-border scenario. Motivated by this, the 5GCroCo project, with a total budget of 17 million Euro and partially funded by the European Commission, aims at validating 5G technologies in the Metz-Merzig-Luxembourg cross-border 5G corridor considering the borders between France, Germany and Luxembourg. The activities of 5GCroCo are organized around three use cases: (1) Tele-operated Driving, (2) high-definition map generation and distribution for automated vehicles and (3) Anticipated Cooperative Collision Avoidance (ACCA). The results of the project help contribute to a true European transnational CCAM. This paper describes the overall objectives of the project, motivated by the discussed challenges of cross-border operation, the use cases along with their requirements, the technical 5G features that will be validated and provides a description of the planned trials within 5GCroCo together with some initial results.

scholarly journals Using Programmable Interfaces for Networks as the Key to Provide Quality of Service in the Internet

10.28945/2410 ◽  
2001 ◽  
Author(s):  
Jairo Gutierrez ◽  
Terence Wee
Keyword(s):  
Quality Of Service ◽  
New Technologies ◽  
Communication Technologies ◽  
Integrated Approach ◽  
Poor Quality ◽  
The Internet ◽  
Heterogeneous Nature ◽  
Dynamic Modification ◽  
Ip Routers

The growth of the Internet with its increasing levels of traffic, more ambitious applications and the convergence of communication technologies results in poor quality of service. New technologies such as those discussed in this paper have been developed to aid in introducing quality of service to the Internet. However, those efforts may seem to be in vain due to the heterogeneous nature of IP-based networks. This paper suggests an integrated approach to provide end-to-end quality of service on the Internet based on the use of programmable interfaces. The need for dynamic modification of policies and configurations within IP routers and switches is already beginning to emerge and that functionality will help fulfill customers' demands for differentiated services.

scholarly journals Nonlinear Autoregressive Recurrent Neural Network Model for Quality of Service Prediction

2020 ◽  
Vol 8 (6) ◽  
pp. 4762-4770
Keyword(s):  
Neural Network ◽  
Quality Of Service ◽  
Recurrent Neural Network ◽  
Prediction System ◽  
Qos Prediction ◽  
Proposed Model ◽  
Routing Monitoring ◽  
The Given ◽  
Nonlinear Autoregressive

Due to the advances in computer networks, Internet and multimedia communications, Quality of Service (QoS) monitoring and assessment become an increasingly important. The importance of assessing QoS stems from the fact it may reflect the resources availability of a network that may provide solutions for QoS provision, routing, monitoring, management … etc. In the literature, several monitoring and measurement approached and methods have been developed to quantify and predict the QoS of multimedia applications transmitted over such networks. In this research, a new QoS prediction system will be designed. The proposed system is based on using the Nonlinear Autoregressive with eXogenous input model (NARX) using recurrent neural network. This prediction system uses in addition to the QoS parameters; previous measured QoS values will used as inputs to this model. The expected output of this new model is the forecasted QoS. The proposed model will be trained, tested, validated and then optimized to provide a good estimate of the QoS provided by the given network. Simulation results are expected to show that the proposed model will have high accurate QoS prediction capabilities compared to other QoS assessment systems adopted in the literature.

scholarly journals Predicting Quality of Service via Leveraging Location Information

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Liang Chen ◽  
Fenfang Xie ◽  
Zibin Zheng ◽  
Yaoming Wu
Keyword(s):  
Neural Network ◽  
Quality Of Service ◽  
Inner Product ◽  
Location Information ◽  
Network Distance ◽  
Qos Prediction ◽  
Location Aware ◽  
Factorization Machine ◽  
Prediction Approach

QoS (Quality of Service) (our approach can be applied to a wide variety of services; in this paper, we focus on Web services) performance is intensively relevant to locations due to the network distance and the Internet connection between users and services. Thus, considering the location information of services and users is necessary. However, the location information has been ignored by most previous work. In this paper, we take both services’ and users’ location information into account. Specifically, we propose a location-aware QoS prediction approach, called LANFM, by exploiting neural network techniques and factorization machine to improve user-perceived experience. First of all, the information (e.g., id and location) of services and users is expressed as embedding vectors by leveraging neural network techniques. Then, the inner product of various embedding vectors, along with the weighted sum of feature vectors, is used to predict the QoS values. It should be noted that the inner product operation could capture the interactions between services and users, which is helpful to predict QoS values of services that have not been invoked by users. A collection of extensive experiments have been carried out on a real-world dataset to validate the effectiveness of the LANFM model.

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