Edge Computing-Based Security Framework for Big Data Analytics in VANETs

Garg, Sahil; Singh, Amritpal; Kaur, Kuljeet; Aujla, Gagangeet Singh; Batra, Shalini; Kumar, Neeraj; Obaidat, Mohammad S.

doi:10.1109/mnet.2019.1800239

Cited by 158 publications

(53 citation statements)

References 12 publications

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“…3) Data security: Data security refers to preventing data leakage from the perspectives of transmission and storage. The former has been discussed in communication security, where various cryptography approaches are proposed to protect data in different scenarios [182], [183]. The cryptography is also a significant technology of securing data storage, such as an encrypted database [184] and file system [185].…”

Section: Security and Privacymentioning

confidence: 99%

Edge Computing for Autonomous Driving: Opportunities and Challenges

Liu¹,

et al. 2019

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The recent proliferation of computing technologies, e.g., sensors, computer vision, machine learning, hardware acceleration, and the broad deployment of communication mechanisms, e.g., DSRC, C-V2X, 5G, have pushed the horizon of autonomous driving, which automates the decision and control of vehicles by leveraging the perception results based on multiple sensors. The key to the success of these autonomous systems is making a reliable decision in a real-time fashion. However, accidents and fatalities caused by early deployed autonomous vehicles arise from time to time. The real traffic environment is too complicated for the current autonomous driving computing systems to understand and handle. In this paper, we present the state-of-the-art computing systems for autonomous driving, including seven performance metrics and nine key technologies, followed by eleven challenges and opportunities to realize autonomous driving. We hope this paper will gain attention from both the computing and automotive communities and inspire more research in this direction.

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Section: Security and Privacymentioning

confidence: 99%

Edge Computing for Autonomous Driving: Opportunities and Challenges

Liu¹,

et al. 2019

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“…Thus, it is also necessary to ensure secure communication and avoid the spread of viruses or false information. As security and privacy is a priority, there is a need for more studies, research, solutions and mechanisms in this area [26], [231], [232], [233], [234].…”

Section: Security and Privacymentioning

confidence: 99%

Computation Offloading for Vehicular Environments: A Survey

et al. 2020

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With significant advances in communication and computing, modern day vehicles are becoming increasingly intelligent. This gives them the ability to contribute to safer roads and passenger comfort through network devices, cameras, sensors, and computational storage and processing capabilities. However, to run new and popular applications, and to enable vehicles operating autonomously requires massive computational resources. Computational resources available with the current day vehicles are not sufficient to process all these demands. In this situation, other vehicles, edge servers, and servers in remote data centers can help the vehicles by lending their computing resources. However, to take advantage of these computing resources, computation offloading techniques have to be leveraged to transfer tasks or entire applications to run on other devices. Such computation offloading can lead to improved performance and Quality of Service (QoS) for applications and for the network. However, computation offloading in a highly dynamic environment such as vehicular networks is a major challenge. Therefore, this survey aims to review and organize the computation offloading literature in vehicular environments. In addition, we demystify some concepts, propose a taxonomy with the most important aspects and classify most works in the area according to each category. We also present the main tools, scenarios, subjects, strategies, objectives, etc., used in the works. Finally, we present the main challenges and future directions to guide future research in this active research area.

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“…• congestion (Zhao et al, 2019;Zhu & Liang, 2019;Mishra, 2019;Reddy & Mehta, 2019;Garg et al, 2019);…”

Section: Urban Logisticsmentioning

confidence: 99%

Smart city concept in the light of the literature review

Winkowska

Szpilko

Pejić

2019

Engineering Management in Production and Services

130

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A B S T R A C T Nowadays, the transformations of metropolises into smart cities is a crucial factor in improving the living conditions of the inhabitants. The goal of the smart city concept is modern urban management using technical tools that offer state-of-the-art technologies, considering the applicable ecological standards while saving resources and achieving the expected results. The purpose of this article is to identify the areas of research analysed in the international literature in the field of smart cities. The bibliometric analysis was carried out to achieve the purpose. The analysis covered publications on smart cities published in Scopus and Web of Science databases from January 2009 to May 2019. Based on the bibliometric analysis, a bibliometric map was developed using the mapping technique VOS -the visualisation of similarities. Original clusters were created using the VOSviewer software. The bibliometric map visualises the results of the analysis that targeted the word coexistence. K E Y W O R D S smart city, smart city subareas, bibliometric map

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Edge Computing-Based Security Framework for Big Data Analytics in VANETs

Cited by 158 publications

References 12 publications

Edge Computing for Autonomous Driving: Opportunities and Challenges

Edge Computing for Autonomous Driving: Opportunities and Challenges

Computation Offloading for Vehicular Environments: A Survey

Smart city concept in the light of the literature review

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