抑制车载自组织网络广播风暴的SEIR流行病传播模型

Q4 Engineering

International Journal of Vehicle Safety Pub Date : 2017-07-19 DOI:10.1504/IJVS.2017.10006058

M. Chitra, S. Sathya

{"title":"抑制车载自组织网络广播风暴的SEIR流行病传播模型","authors":"M. Chitra, S. Sathya","doi":"10.1504/IJVS.2017.10006058","DOIUrl":null,"url":null,"abstract":"Vehicular Ad Hoc Networks (VANETs) is a form of Intelligent Transportation System (ITS) to improve road safety and transport efficiency. During an emergency like accidents, traffic jams, etc., the vehicles in VANET are alerted with an Emergency Safety Message (ESM) through broadcasting. However, blind broadcasting of ESMs across VANETs leads to Broadcast Storm Problem (BSP) which would affect the QoS requirements of VANET. Hence, it is vital to suppress BSP to broadcast ESMs effectively. This paper proposes a Broadcast Storm Suppression Algorithm (BSSA) based on the concept of epidemic spreading, i.e. SEIR (Susceptible, Exposed, Infected and Removed) model. The broadcast storm is suppressed by finding the 'Farthest Infected Vehicle' (FIV) travelling in the direction of the ESM and recovering the other infected vehicles within the region to prevent from rebroadcasting the ESM. The SEIR model is simulated in NS-2.34 and found to outperform other popular broadcasting techniques.","PeriodicalId":35143,"journal":{"name":"International Journal of Vehicle Safety","volume":"9 1","pages":"228-252"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"SEIR epidemic spreading model to suppress broadcast storm in vehicular ad hoc networks\",\"authors\":\"M. Chitra, S. Sathya\",\"doi\":\"10.1504/IJVS.2017.10006058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicular Ad Hoc Networks (VANETs) is a form of Intelligent Transportation System (ITS) to improve road safety and transport efficiency. During an emergency like accidents, traffic jams, etc., the vehicles in VANET are alerted with an Emergency Safety Message (ESM) through broadcasting. However, blind broadcasting of ESMs across VANETs leads to Broadcast Storm Problem (BSP) which would affect the QoS requirements of VANET. Hence, it is vital to suppress BSP to broadcast ESMs effectively. This paper proposes a Broadcast Storm Suppression Algorithm (BSSA) based on the concept of epidemic spreading, i.e. SEIR (Susceptible, Exposed, Infected and Removed) model. The broadcast storm is suppressed by finding the 'Farthest Infected Vehicle' (FIV) travelling in the direction of the ESM and recovering the other infected vehicles within the region to prevent from rebroadcasting the ESM. The SEIR model is simulated in NS-2.34 and found to outperform other popular broadcasting techniques.\",\"PeriodicalId\":35143,\"journal\":{\"name\":\"International Journal of Vehicle Safety\",\"volume\":\"9 1\",\"pages\":\"228-252\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Vehicle Safety\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJVS.2017.10006058\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Vehicle Safety","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJVS.2017.10006058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}

引用次数: 5

摘要

车载自组织网络（VANET）是智能交通系统（ITS）的一种形式，旨在提高道路安全和运输效率。在事故、交通堵塞等紧急情况下，VANET中的车辆会通过广播收到紧急安全信息（ESM）。然而，ESM在VANET之间的盲广播会导致广播风暴问题（BSP），这将影响VANET的QoS要求。因此，抑制BSP对ESM的有效广播至关重要。本文提出了一种基于流行病传播概念的广播风暴抑制算法（BSSA），即SEIR（易感、暴露、感染和移除）模型。通过发现“最远受感染车辆”（FIV）朝ESM方向行驶，并在该地区内回收其他受感染车辆，以防止转播ESM，来抑制广播风暴。在NS-2.34中模拟了SEIR模型，发现其优于其他流行的广播技术。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

SEIR epidemic spreading model to suppress broadcast storm in vehicular ad hoc networks

Vehicular Ad Hoc Networks (VANETs) is a form of Intelligent Transportation System (ITS) to improve road safety and transport efficiency. During an emergency like accidents, traffic jams, etc., the vehicles in VANET are alerted with an Emergency Safety Message (ESM) through broadcasting. However, blind broadcasting of ESMs across VANETs leads to Broadcast Storm Problem (BSP) which would affect the QoS requirements of VANET. Hence, it is vital to suppress BSP to broadcast ESMs effectively. This paper proposes a Broadcast Storm Suppression Algorithm (BSSA) based on the concept of epidemic spreading, i.e. SEIR (Susceptible, Exposed, Infected and Removed) model. The broadcast storm is suppressed by finding the 'Farthest Infected Vehicle' (FIV) travelling in the direction of the ESM and recovering the other infected vehicles within the region to prevent from rebroadcasting the ESM. The SEIR model is simulated in NS-2.34 and found to outperform other popular broadcasting techniques.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Vehicle Safety Engineering-Automotive Engineering

CiteScore

0.30

自引率

0.00%

发文量

期刊介绍： The IJVS aims to provide a refereed and authoritative source of information in the field of vehicle safety design, research, and development. It serves applied scientists, engineers, policy makers and safety advocates with a platform to develop, promote, and coordinate the science, technology and practice of vehicle safety. IJVS also seeks to establish channels of communication between industry and academy, industry and government in the field of vehicle safety. IJVS is published quarterly. It covers the subjects of passive and active safety in road traffic as well as traffic related public health issues, from impact biomechanics to vehicle crashworthiness, and from crash avoidance to intelligent highway systems.