車聯(lián)網(wǎng)中繼選擇算法研究
本文選題:車聯(lián)網(wǎng) 切入點(diǎn):中繼選擇 出處:《重慶郵電大學(xué)》2014年碩士論文
【摘要】:信息領(lǐng)域正發(fā)生著由互聯(lián)網(wǎng)到物聯(lián)網(wǎng)的新一輪技術(shù)革命。車聯(lián)網(wǎng)作為戰(zhàn)略性新興產(chǎn)業(yè)中物聯(lián)網(wǎng)和智能交通兩大領(lǐng)域的重要交集已引起學(xué)術(shù)界和工業(yè)界的極大關(guān)注。車聯(lián)網(wǎng)中,車輛的快速移動以及接入點(diǎn)(Access Point, AP)覆蓋范圍有限等因素導(dǎo)致部分車輛無法與AP直接進(jìn)行通信,可通過采用中繼車輛(Relay Vehicle, RV)支持源車輛(Source Vehicle, SV)與AP之間的數(shù)據(jù)轉(zhuǎn)發(fā)。在存在多個候選RV的情況下,,如何綜合考慮物理信道特性、鏈路消息碰撞接入時延、RV的負(fù)載狀況等多因素,選擇最佳RV以保障用戶通信需求,并實(shí)現(xiàn)系統(tǒng)性能優(yōu)化已成為車聯(lián)網(wǎng)的重要研究課題。 本課題針對存在多個SV和多個可用RV,且存在自私車輛的車聯(lián)網(wǎng)場景,提出一種基于多目標(biāo)優(yōu)化的RV選擇算法,通過綜合考慮SV的業(yè)務(wù)需求、信道特性、RV的可用帶寬及由于信道競爭導(dǎo)致消息碰撞等因素,分別建模SV和RV的效用函數(shù),并基于各SV及RV性能最優(yōu)建模多目標(biāo)優(yōu)化模型,最后采用理想點(diǎn)法進(jìn)行SV及RV的最優(yōu)匹配,以確定最佳RV選擇方案。 針對多個SV和多個RV合作實(shí)現(xiàn)RV優(yōu)化選擇的應(yīng)用場景,提出一種基于博弈論的RV選擇算法,通過綜合考慮多種因素對算法性能的影響,建立SV及RV的合作博弈建模,使用二分圖最優(yōu)匹配方法(Kuhn-Munkras算法)對博弈模型進(jìn)行求解,從而得出對應(yīng)系統(tǒng)綜合性能最優(yōu)的最佳RV選擇方案。 針對車聯(lián)網(wǎng)中兩類典型業(yè)務(wù),即時延敏感型業(yè)務(wù)和吞吐量敏感型業(yè)務(wù),本文提出了一種基于簇的RV選擇算法,分別就簇頭選擇和簇間切換機(jī)制開展研究,提出基于效用函數(shù)優(yōu)化的簇頭選擇策略以及基于擬切換簇成員及目標(biāo)簇的效用增益最優(yōu)的簇切換策略。 本文針對車聯(lián)網(wǎng)具體網(wǎng)絡(luò)場景及用戶業(yè)務(wù)需求提出RV優(yōu)化選擇策略,可以作為深入研究車聯(lián)網(wǎng)RV選擇技術(shù)的參考,具有一定的創(chuàng)新性、理論價值和現(xiàn)實(shí)意義。
[Abstract]:The field of information is undergoing a new round of technological revolution from Internet of things to Internet of things. As an important intersection of Internet of things and intelligent transportation in the strategic emerging industries, car networking has attracted great attention from academia and industry. The rapid movement of vehicles and the limited coverage of access points (APs) make some vehicles unable to communicate directly with AP. The relaying vehicle Relay vehicle (RV) can be used to support data forwarding between the source vehicle Source vehicle (SVV) and AP. In the case of multiple candidate RVs, how to consider the physical channel characteristics, link message collision access delay, RV load and other factors, etc. Choosing the best RV to protect the user's communication requirements and realize the system performance optimization has become an important research topic of vehicle networking. In this paper, a multi-objective optimization based RV selection algorithm is proposed for vehicle networking scenarios with multiple SV and available RVs and selfish vehicles. By considering the business requirements of SV comprehensively, this paper proposes a new RV selection algorithm based on multi-objective optimization. Based on the available bandwidth of RV and channel competition, the utility function of SV and RV is modeled, and the multi-objective optimization model is built based on each SV and RV. Finally, the optimal matching of SV and RV is carried out by using the ideal point method to determine the optimal RV selection scheme. In this paper, a game theory based RV selection algorithm is proposed for the application of multiple SV and multiple RV cooperation to realize RV optimal selection. The cooperative game modeling of SV and RV is established by considering the influence of many factors on the performance of the algorithm. Kuhn-Munkras algorithm is used to solve the game model, and the optimal RV selection scheme with optimal comprehensive performance of the corresponding system is obtained. In this paper, a clust-based RV selection algorithm is proposed for two types of typical services, instant delay sensitive services and throughput sensitive services in vehicle networking. Cluster head selection and inter-cluster switching mechanism are studied respectively. A cluster head selection strategy based on utility function optimization and a cluster handover strategy based on optimal utility gain of quasi-switched cluster members and target clusters are proposed. This paper proposes a RV optimal selection strategy for the specific network scenarios and user business requirements of vehicle networking, which can be used as a reference for the in-depth study of RV selection technology in vehicle networking. It has certain innovation, theoretical value and practical significance.
【學(xué)位授予單位】:重慶郵電大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:TN929.5;TP391.44
【參考文獻(xiàn)】
相關(guān)期刊論文 前9條
1 劉爽;朱凱;董宸;;基于PLC一維極軸自動控制的對日跟蹤系統(tǒng)[J];工業(yè)控制計(jì)算機(jī);2010年01期
2 王群;錢煥延;;車聯(lián)網(wǎng)體系結(jié)構(gòu)及感知層關(guān)鍵技術(shù)研究[J];電信科學(xué);2012年12期
3 畢然;湯立波;羅松;;車聯(lián)網(wǎng)應(yīng)用發(fā)展及產(chǎn)業(yè)格局分析[J];電信網(wǎng)技術(shù);2011年09期
4 陳超;呂植勇;付姍姍;彭琪;;國內(nèi)外車路協(xié)同系統(tǒng)發(fā)展現(xiàn)狀綜述[J];交通信息與安全;2011年01期
5 王金炳;;博弈論的發(fā)展歷史和基本內(nèi)容[J];時代經(jīng)貿(mào)(下旬刊);2007年06期
6 胡向東;;物聯(lián)網(wǎng)研究與發(fā)展綜述[J];數(shù)字通信;2010年02期
7 常促宇;向勇;史美林;;車載自組網(wǎng)的現(xiàn)狀與發(fā)展[J];通信學(xué)報(bào);2007年11期
8 張國鵬;丁恩杰;涂相華;;基于博弈論的協(xié)作中繼策略[J];中國礦業(yè)大學(xué)學(xué)報(bào);2012年03期
9 程學(xué)虎;陳亞峰;;車聯(lián)網(wǎng)發(fā)展?fàn)顩r研究[J];中國無線電;2013年02期
本文編號:1674679
本文鏈接:http://sikaile.net/kejilunwen/wltx/1674679.html