期刊論文

學年 100
學期 2
出版(發表)日期 2012-03-01
作品名稱 Mixing Greedy and Predictive approaches to Improve Geographic Routing for VANET
作品名稱(其他語言)
著者 Wu, Tin-Yu; Wang, Yan-Bo; Lee, Wei-Tsong
單位 淡江大學電機工程學系
出版者 Oxford: John Wiley & Sons Ltd.
著錄名稱、卷期、頁數 Wireless Communications and Mobile Computing 12(4), pp.367–378
摘要 In recent years, thanks to the development and popularization of wireless network technologies, the issue of vehicular ad hoc network (VANET) has received great attention, and more and more VANET-related researches have been brought up. Generally speaking, the biggest difference between VANET and traditional ad hoc network is the velocity of carriers because in VANET, the velocity of vehicles, the carriers, is much higher than those in traditional ad hoc. Therefore, it would be a great challenge to forward data efficiently in VANETs and many researches proposed have focused on the development of routing protocols. The current proposed routing protocols are all assumed to simulate in a distributed and ideal environment. As for the complex geographic environments, such as urban scenarios, extra amendments must be needed to improve the efficiency of the routing protocols. Thus, the main purpose of this paper is to design a suitable routing protocol for urban scenarios with better performance and adaptability. For this reason, greedy on straight roads and predictive at the intersections (GSPI) routing protocol is proposed to use greedy mode on straight roads and to use predictive mode at the intersections. In greedy mode, we choose the next hop according to the weight value that combines the distances and multi-rate. In predictive mode, we predict the directions of the vehicles to determine the next hop. The simulation results reveal that our proposed algorithm indeed proves its feasibility.
關鍵字 VANET; geographic position-based routing protocol; greedy perimeter stateless routing; GSPI
語言 en
ISSN 1530-8677
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度
國別 GBR
公開徵稿
出版型式 電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/54973 )

機構典藏連結