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Proceedings ArticleDOI

AVANET Services, Autonomous Vehicles and the Mobile Cloud

TLDR
This talk will revisit VANET applications and will propose a Vehicular Cloud platform along with representative mobile service examples.
Abstract
As vehicles will soon become network connected, new vehicle applications are emerging, from navigation safety to location aware content distribution, urban surveillance and intelligent transport. Autonomous vehicles stand out as important players, with plenty of sensors, memory and processing power. The richness of on-board resources and the diversity of applications set the Vehicular ad Hoc Network(VANET) apart from conventional MANETs and introduce new challenges in the services they provide. First, it becomes apparent that safe navigation in a future with autonomous car platoons, say, will demand efficient, low latency V2V. Moreover, other applications (eg, surveillance, traffic management, etc) will require a degree of coordination not possible with the conventional Internet Cloud. To this end, low latency cooperation can be best supported by a Mobile Computing Cloud (MCC), where vehicles use V2V to propagate computation results, share resources and provide mobile services. This talk will revisit VANET applications and will propose a Vehicular Cloud platform along with representative mobile service examples.

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Journal ArticleDOI

Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems

TL;DR: This survey introduces the corresponding ITS applications and discusses how traffic forecasting can improve the performance of these applications, and introduces the characteristics of these two types of prediction methods through specific examples of state-of-the-art approaches.
Journal ArticleDOI

DACON: A Novel Traffic Prediction and Data-Highway-Assisted Content Delivery Protocol for Intelligent Vehicular Networks

TL;DR: A novel data-highway-assisted content delivery protocol for addressing the content delivery problem in VANETs is provided and the advantages of the predicted vehicular traffic volume driven by a newly designed fast traffic flow prediction scheme are explored.
Proceedings ArticleDOI

Empirical Study and Analysis of the Impact of Traffic Flow Control at Road Intersections on Vehicle Energy Consumption

TL;DR: The advantage of this method is that it can improve the energy efficiency of the vehicle within the system without updating the vehicle, and some state-of-the-art approaches are compared through the form of an empirical study.
Journal ArticleDOI

Novel Sustainable and Heterogeneous Offloading Management Techniques in Proactive Cloudlets

TL;DR: A novel hybrid offloading model to solve the heterogeneous resource-constraint offloading issues in the Cloudlet, concerning the offloading energy and execution efficiency and Experimental results reveal that the proposed framework can effectively reduce the off loading energy cost and execution time, compared to currently existing solutions.
Proceedings ArticleDOI

Security Enhancing Method in Vehicular Networks by Exploiting the Accurate Traffic Flow Prediction

TL;DR: In this article, the authors proposed a data transmission security improvement method based on accurate traffic flow prediction for addressing a specific data theft problem, which can detect the fraud vehicle that spread fake traffic information to increase the possibility that it may be selected as a relay node, thereby increasing its theft of the data of related users who use it as a relaying node.
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