مقاله انگلیسی رایگان در مورد تشخیص مجاورت تقویت شده با رایانش لبه ای سیار – IEEE 2019
مشخصات مقاله | |
ترجمه عنوان مقاله | تشخیص مجاورت تقویت شده با رایانش لبه ای سیار در شبکه های جاده ای آگاه از زمان |
عنوان انگلیسی مقاله | Mobile Edge Computing-Enhanced Proximity Detection in Time-Aware Road Networks |
انتشار | مقاله سال ۲۰۱۹ |
تعداد صفحات مقاله انگلیسی | ۱۵ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه IEEE |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
۴٫۶۴۱ در سال ۲۰۱۸ |
شاخص H_index | ۵۶ در سال ۲۰۱۹ |
شاخص SJR | ۰٫۶۰۹ در سال ۲۰۱۸ |
شناسه ISSN | ۲۱۶۹-۳۵۳۶ |
شاخص Quartile (چارک) | Q2 در سال ۲۰۱۸ |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی کامپیوتر |
گرایش های مرتبط | مهندسی الگوریتم و محاسبات، رایانش ابری |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | دسترسی – IEEE Access |
دانشگاه | School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China |
کلمات کلیدی | بهینه سازی هزینه، تاخیر کم، رایانش لبه ای سیار، تشخیص مجاورت، شبکه های جاده ای آگاه از زمان، فاصله زمانی |
کلمات کلیدی انگلیسی | Cost optimization, low latency, mobile edge computing, proximity detection, time-aware road networks, time distance |
شناسه دیجیتال – doi |
https://doi.org/10.1109/ACCESS.2019.2937337 |
کد محصول | E14034 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract I. Introduction II. Related Work III. Problem Statement IV. MEC Enhanced Proximity Detection Architecture V. Algorithms: Time-Aware Mobile Region Based Detection Method Authors Figures References |
بخشی از متن مقاله: |
Abstract
Given a set of moving objects as well as their friend relationships, a time-aware road network, and a time threshold per friend pair, the proximity detection problem in time-aware road networks is to find each pair of moving objects such that the time distance (defined as the shortest time needed for two moving objects to meet each other) between them is within the given threshold. The problem of proximity detection is often encountered in autonomous driving and traffic safety related applications, which require low-latency, real time proximity detection with relatively low communication cost. However, (i) most existing proximity detection solutions focus on the Euclidean space which cannot be used in road network space, (ii) the solutions for road networks focus on static road networks and do not consider time distance and thus cannot be applied in time-aware road networks, and (iii) there are no works aiming to simultaneously reduce the communication cost, the communication latency, and computational cost. Motivated by these, we first design a low-latency proximity detection architecture based on Mobile Edge Computing (MEC) with the purpose of achieving low communication latency, then propose a proximity detection method including a client-side algorithm and a server-side algorithm, aiming at reducing the communication cost, and subsequently propose server-side computational cost optimization techniques to reduce the computational cost. Experimental results show that our MEC enhanced proximity detection architecture, our proximity detection method, and the server-side computational cost optimization techniques can reduce the communication latency, the communication cost, and the computational cost effectively. Introduction In a road network, how to effectively detect whether the moving users are within proximity or not, is referred to as the problem of proximity detection in road networks. In a dynamically changing road network, proximity detection among a large number of moving users plays an important role in ensuring traffic safety, guaranteeing assisted driving, and realizing the future large-scale autonomous driving. With the spreading of modern mobile devices like smart phones, PDAs or car navigation systems and the development of positioning technologies such as GPS, WiFi, cellular base station positioning or A-GPS, users can conveniently obtain their positions and send their location information to control center servers or other users’ mobile devices. Mobile users communicate with servers or other users frequently, leading to a large number of communication messages referred to as communication cost, consuming a lot of network bandwidth. Given a large number of mobile users and time distance T , time-aware proximity detection problem in road networks is to find a solution which not only can continuously detect which pairs of users among all users are within proximity based on time distance, but also can achieve the objectives of reducing communication cost, communication latency, and computational cost, so as to save the network bandwidth and improve the reliability and efficiency of proximity detection. Here, time distance refers to the shortest time needed for two users to meet each other. |