文献类型：期刊文献

英文题名：Data sharing in VANETs based on evolutionary fuzzy game

作者：Liu, Jianhua[1,3];Wang, Xin[2];Yue, Guangxue[3];Shen, Shigen[4]

机构：[1]Shanghai Normal Univ, Coll Informat Mech & Elect Engn, Shanghai 200234, Peoples R China;[2]SUNY Stony Brook, Dept Elect & Comp Engn, Stony Brook, NY 11790 USA;[3]Jiaxing Univ, Coll Math Phys & Informat Engn, Jiaxing 314001, Peoples R China;[4]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing 312000, Peoples R China

年份：2018

卷号：81

起止页码：141

外文期刊名：FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE

收录：SCI-EXPANDED(收录号：WOS:000423652200012)、、EI(收录号：20174804455453)、Scopus(收录号：2-s2.0-85034828588)、WOS

基金：This work was partly supported by National Natural Science Foundation of China under Grant Nos. 61572014, 61772018 and by Zhejiang Provincial Natural Science Foundation of China under Grant No. LY16F020028.

语种：英文

外文关键词：Cooperative communications; Data delivery; Game theory; Vehicular networks

外文摘要：There is a growing interest in enabling sharing data transmissions in Vehicular Ad hoc Networks (VANETs). However, due to the constant link disconnections and limited effective bandwidth, it is important and challenging to design a reliable delivery strategy that can reduce the transmission delay to meet the need of delay-sensitive applications. In this work, we propose a real-time scheme for neighboring nodes on the road to cooperatively make their decisions on their data distribution strategies based on evolutionary fuzzy game. The encountering nodes form a contact graph during their contact time. Depending on the link conditions and neighbors' caching spaces, a node will determine between two strategies, distributing data to a neighbor or caching the data. Our algorithm will minimize the cost of caching and data distribution over a wireless link. We have performed extensive simulations to evaluate the performance of our design. We compare the performance of our algorithm with that of non-cooperative data delivery and three peer schemes. Our results demonstrate that the data delivery delay and rate of our algorithm outperform those of non-cooperative data delivery, and the probability of data distribution of our scheme is 4%, 12%, and 19% higher than that of LGC, LCA, and LRU. (C) 2017 Published by Elsevier B.V.