• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

EDDA:一种高效的车载自组网分布式数据复制算法。

EDDA: An Efficient Distributed Data Replication Algorithm in VANETs.

作者信息

Zhu Junyu, Huang Chuanhe, Fan Xiying, Guo Sipei, Fu Bin

机构信息

School of computer, Wuhan University, Wuhan 430072, China.

Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430072, China.

出版信息

Sensors (Basel). 2018 Feb 10;18(2):547. doi: 10.3390/s18020547.

DOI:10.3390/s18020547
PMID:29439443
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5855516/
Abstract

Efficient data dissemination in vehicular ad hoc networks (VANETs) is a challenging issue due to the dynamic nature of the network. To improve the performance of data dissemination, we study distributed data replication algorithms in VANETs for exchanging information and computing in an arbitrarily-connected network of vehicle nodes. To achieve low dissemination delay and improve the network performance, we control the number of message copies that can be disseminated in the network and then propose an efficient distributed data replication algorithm (EDDA). The key idea is to let the data carrier distribute the data dissemination tasks to multiple nodes to speed up the dissemination process. We calculate the number of communication stages for the network to enter into a balanced status and show that the proposed distributed algorithm can converge to a consensus in a small number of communication stages. Most of the theoretical results described in this paper are to study the complexity of network convergence. The lower bound and upper bound are also provided in the analysis of the algorithm. Simulation results show that the proposed EDDA can efficiently disseminate messages to vehicles in a specific area with low dissemination delay and system overhead.

摘要

由于车载自组织网络(VANETs)的动态特性,在其中进行高效的数据传播是一个具有挑战性的问题。为了提高数据传播性能,我们研究了VANETs中的分布式数据复制算法,用于在车辆节点的任意连通网络中交换信息和进行计算。为了实现低传播延迟并提高网络性能,我们控制网络中可传播的消息副本数量,然后提出了一种高效的分布式数据复制算法(EDDA)。关键思想是让数据载体将数据传播任务分配给多个节点,以加速传播过程。我们计算网络进入平衡状态所需的通信阶段数,并表明所提出的分布式算法能够在少量通信阶段内收敛到共识。本文描述的大多数理论结果是研究网络收敛的复杂性。在算法分析中还提供了下限和上限。仿真结果表明,所提出的EDDA能够以低传播延迟和系统开销,将消息高效地传播到特定区域内的车辆。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/350b1ae3018c/sensors-18-00547-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/0b88a890414e/sensors-18-00547-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/04a76fae022e/sensors-18-00547-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/f91cf741f976/sensors-18-00547-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/90491b6a48a0/sensors-18-00547-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/8326fefb4419/sensors-18-00547-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/db71c6693fea/sensors-18-00547-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/c8a108c64b9b/sensors-18-00547-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/ac99cab50a4b/sensors-18-00547-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/c6d649fc7080/sensors-18-00547-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/7b366d501de4/sensors-18-00547-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/0352a51251b1/sensors-18-00547-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/bec1237f20e5/sensors-18-00547-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/eb449a05531c/sensors-18-00547-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/2fa37d11c11c/sensors-18-00547-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/43befa36e00f/sensors-18-00547-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/f1d8e9710d89/sensors-18-00547-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/21c038065d0e/sensors-18-00547-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/6c470c618c07/sensors-18-00547-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/350b1ae3018c/sensors-18-00547-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/0b88a890414e/sensors-18-00547-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/04a76fae022e/sensors-18-00547-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/f91cf741f976/sensors-18-00547-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/90491b6a48a0/sensors-18-00547-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/8326fefb4419/sensors-18-00547-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/db71c6693fea/sensors-18-00547-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/c8a108c64b9b/sensors-18-00547-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/ac99cab50a4b/sensors-18-00547-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/c6d649fc7080/sensors-18-00547-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/7b366d501de4/sensors-18-00547-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/0352a51251b1/sensors-18-00547-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/bec1237f20e5/sensors-18-00547-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/eb449a05531c/sensors-18-00547-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/2fa37d11c11c/sensors-18-00547-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/43befa36e00f/sensors-18-00547-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/f1d8e9710d89/sensors-18-00547-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/21c038065d0e/sensors-18-00547-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/6c470c618c07/sensors-18-00547-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a514/5855516/350b1ae3018c/sensors-18-00547-g019.jpg

相似文献

1
EDDA: An Efficient Distributed Data Replication Algorithm in VANETs.EDDA:一种高效的车载自组网分布式数据复制算法。
Sensors (Basel). 2018 Feb 10;18(2):547. doi: 10.3390/s18020547.
2
Game-Theoretical Design of an Adaptive Distributed Dissemination Protocol for VANETs.用于车载自组网的自适应分布式传播协议的博弈论设计
Sensors (Basel). 2018 Jan 19;18(1):294. doi: 10.3390/s18010294.
3
Plummeting Broadcast Storm Problem in Highways by Clustering Vehicles Using Dominating Set and Set Cover.通过使用支配集和集合覆盖对车辆进行聚类来解决高速公路上急剧下降的广播风暴问题。
Sensors (Basel). 2019 May 12;19(9):2191. doi: 10.3390/s19092191.
4
EEMDS: An Effective Emergency Message Dissemination Scheme for Urban VANETs.EEMDS:一种适用于城市车载自组网的有效紧急消息传播方案。
Sensors (Basel). 2021 Feb 25;21(5):1588. doi: 10.3390/s21051588.
5
Smartphone-Based Platform for Secure Multi-Hop Message Dissemination in VANETs.基于智能手机的 VANETs 中安全多跳消息分发平台。
Sensors (Basel). 2020 Jan 7;20(2):330. doi: 10.3390/s20020330.
6
A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network.一种用于车载自组织网络中簇内数据聚合的博弈论算法。
Sensors (Basel). 2016 Feb 19;16(2):245. doi: 10.3390/s16020245.
7
Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network.基于城市车辆网络中用户移动性和节点密度的高效稳定路由算法
PLoS One. 2016 Nov 17;11(11):e0165966. doi: 10.1371/journal.pone.0165966. eCollection 2016.
8
Enhancing network stability in VANETs using nature inspired algorithm for intelligent transportation system.利用受自然启发的算法增强 VANET 中的网络稳定性,以实现智能交通系统。
PLoS One. 2024 Jan 11;19(1):e0296331. doi: 10.1371/journal.pone.0296331. eCollection 2024.
9
Design and Analysis of A Beacon-Less Routing Protocol for Large Volume Content Dissemination in Vehicular Ad Hoc Networks.车载自组织网络中用于大容量内容分发的无信标路由协议的设计与分析
Sensors (Basel). 2016 Nov 1;16(11):1834. doi: 10.3390/s16111834.
10
BCDP: Budget constrained and delay-bounded placement for hybrid roadside units in vehicular ad hoc networks.BCDP:车载自组织网络中混合路边单元的预算受限和延迟受限放置
Sensors (Basel). 2014 Nov 27;14(12):22564-94. doi: 10.3390/s141222564.

引用本文的文献

1
Modeling and Performance of the IEEE 802.11p Broadcasting for Intra-Platoon Communication.IEEE 802.11p 广播在车间通信中的建模与性能研究。
Sensors (Basel). 2018 Sep 6;18(9):2971. doi: 10.3390/s18092971.
2
How to Stop Disagreeing and Start Cooperatingin the Presence of Asymmetric Packet Loss.在存在非对称丢包的情况下如何停止分歧并开始合作
Sensors (Basel). 2018 Apr 22;18(4):1287. doi: 10.3390/s18041287.

本文引用的文献

1
BCDP: Budget constrained and delay-bounded placement for hybrid roadside units in vehicular ad hoc networks.BCDP:车载自组织网络中混合路边单元的预算受限和延迟受限放置
Sensors (Basel). 2014 Nov 27;14(12):22564-94. doi: 10.3390/s141222564.