Evaluation of Docker as Edge computing platform

Author(s):  
Bukhary Ikhwan Ismail ◽  
Ehsan Mostajeran Goortani ◽  
Mohd Bazli Ab Karim ◽  
Wong Ming Tat ◽  
Sharipah Setapa ◽  
...  
Author(s):  
Ashish Joglekar ◽  
Gurunath Gurrala ◽  
Puneet Kumar ◽  
Francis C Joseph ◽  
Kiran T S ◽  
...  

Author(s):  
Jo Yoshimoto ◽  
Ittetsu Taniguchi ◽  
Hiroyuki Tomiyama ◽  
Takao Onoye

2022 ◽  
Vol 54 (9) ◽  
pp. 1-37
Author(s):  
Pasika Ranaweera ◽  
Anca Jurcut ◽  
Madhusanka Liyanage

The future of mobile and internet technologies are manifesting advancements beyond the existing scope of science. The concepts of automated driving, augmented-reality, and machine-type-communication are quite sophisticated and require an elevation of the current mobile infrastructure for launching. The fifth-generation (5G) mobile technology serves as the solution, though it lacks a proximate networking infrastructure to satisfy the service guarantees. Multi-access Edge Computing (MEC) envisages such an edge computing platform. In this survey, we are revealing security vulnerabilities of key 5G-based use cases deployed in the MEC context. Probable security flows of each case are specified, while countermeasures are proposed for mitigating them.


Author(s):  
Luiz Angelo Steffenel ◽  
Manuele Kirsch Pinheiro ◽  
Lucas Vaz Peres ◽  
Damaris Kirsch Pinheiro

The exponential dissemination of proximity computing devices (smartphones, tablets, nanocomputers, etc.) raises important questions on how to transmit, store and analyze data in networks integrating those devices. New approaches like edge computing aim at delegating part of the work to devices in the “edge” of the network. In this article, the focus is on the use of pervasive grids to implement edge computing and leverage such challenges, especially the strategies to ensure data proximity and context awareness, two factors that impact the performance of big data analyses in distributed systems. This article discusses the limitations of traditional big data computing platforms and introduces the principles and challenges to implement edge computing over pervasive grids. Finally, using CloudFIT, a distributed computing platform, the authors illustrate the deployment of a real geophysical application on a pervasive network.


Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4905 ◽  
Author(s):  
Rongxu Xu ◽  
Wenquan Jin ◽  
Dohyeun Kim

Internet of Things (IoT) devices are embedded with software, electronics, and sensors, and feature connectivity with constrained resources. They require the edge computing paradigm, with modular characteristics relying on microservices, to provide an extensible and lightweight computing framework at the edge of the network. Edge computing can relieve the burden of centralized cloud computing by performing certain operations, such as data storage and task computation, at the edge of the network. Despite the benefits of edge computing, it can lead to many challenges in terms of security and privacy issues. Thus, services that protect privacy and secure data are essential functions in edge computing. For example, the end user’s ownership and privacy information and control are separated, which can easily lead to data leakage, unauthorized data manipulation, and other data security concerns. Thus, the confidentiality and integrity of the data cannot be guaranteed and, so, more secure authentication and access mechanisms are required to ensure that the microservices are exposed only to authorized users. In this paper, we propose a microservice security agent to integrate the edge computing platform with the API gateway technology for presenting a secure authentication mechanism. The aim of this platform is to afford edge computing clients a practical application which provides user authentication and allows JSON Web Token (JWT)-based secure access to the services of edge computing. To integrate the edge computing platform with the API gateway, we implement a microservice security agent based on the open-source Kong in the EdgeX Foundry framework. Also to provide an easy-to-use approach with Kong, we implement REST APIs for generating new consumers, registering services, configuring access controls. Finally, the usability of the proposed approach is demonstrated by evaluating the round trip time (RTT). The results demonstrate the efficiency of the system and its suitability for real-world applications.


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