دانلود رایگان مقاله یک روش تخلیه محاسبات لبه با حفظ حریم خصوصی برای اینترنت وسایل نقلیه متصل – سال 2019
مشخصات مقاله:
عنوان فارسی مقاله:
یک روش تخلیه محاسبات لبه با حفظ حریم خصوصی برای اینترنت وسایل نقلیه متصل
عنوان انگلیسی مقاله:
An edge computing-enabled computation offloading method with privacy preservation for internet of connected vehicles
کلمات کلیدی مقاله:
IoV، حفظ حریم خصوصی، محاسبه لبه، تخلیه محاسباتی، مصرف انرژی
مناسب برای رشته های دانشگاهی زیر:
مهندسی فناوری اطلاعات – مهندسی کامپیوتر
مناسب برای گرایش های دانشگاهی زیر:
اینترنت و شبکه های گسترده – رایانش ابری – الگوریتم و محاسبات
وضعیت مقاله انگلیسی و ترجمه:
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فهرست مطالب:
Outline
Highlights
Abstract
MSC
Keywords
۱٫ Introduction
۲٫ System model and problem formulation
۳٫ A computation offloading method with privacy preservation for IoV in edge computing
۴٫ Experimental evaluation
۵٫ Related work
۶٫ Conclusion and future work
Acknowledgments
References
قسمتی از مقاله انگلیسی:
Abstract
The Internet of connected vehicles (IoV) is employed to collect real-time traffic conditions for transportation control systems, and the computing tasks are available to be offloaded from the vehicles to the edge computing devices (ECDs) for implementation. Despite numerous benefits of IoV and ECDs, the wireless communication for computation offloading increases the risk of privacy leakage, which may consequently lead to tracking, identity tampering and virtual vehicle hijacking. Therefore, it remains a challenge to avoid privacy conflicts for computation offloading to the ECDs in IoV. To address this challenge, an edge computing-enabled computation offloading method, named ECO, with privacy preservation for IoV is proposed in this paper. Technically, the privacy conflicts of the computing tasks in IoV are analyzed in a formalized way. Then, vehicle-to-vehicle (V2V) communication-based routing for a vehicle is designed to acquire the routing vehicles from the origin vehicle where the computing task is located at the destination vehicle. NSGA-II (non-dominated sorting genetic algorithm II) is adopted to realize multi-objective optimization to reduce the execution time and energy consumption of ECDs and prevent privacy conflicts of the computing tasks. Finally, experimental evaluations are conducted to validate the efficiency and effectiveness of ECO.
1. Introduction
1.1. Background
In recent years, the number of vehicles has increased rapidly to expand residents’ travel range, thus stretching transportation systems to their capacity limits [1]. With the explosive growth of vehicles, traffic congestion and car accidents occur frequently in urban areas. To improve traffic conditions in urban cities, the Internet of connected vehicles (IoV) has emerged as a new paradigm that emphasizes information interaction among vehicles and humans. In the IoV environment, vehicles are connected to devices such as intelligent cameras, sensors and actuators. These devices have transmitters and receivers that connect the vehicles to the remote infrastructure and other vehicles [2][3]. The real-time traffic information collected from the vehicles includes vehicle position, vehicle safety, vehicle driving status and vehicle identification information. IoV services can increase the dissemination of real-time traffic information and the ability of the vehicle drivers to track traffic conditions in real time.
