【摘要】：作為21世紀(jì)十大新興技術(shù)之一，無線傳感器網(wǎng)絡(luò)（Wireless Sensor Network，WSN）通過對(duì)傳感技術(shù)、微電子工藝，以及無線網(wǎng)絡(luò)的融合，實(shí)現(xiàn)了物理世界與信息網(wǎng)絡(luò)世界的連接，極大的擴(kuò)展了人類認(rèn)識(shí)和改造世界的能力。但在當(dāng)前的WSN應(yīng)用中，所部署的傳感器節(jié)點(diǎn)大多無法支持能量捕獲，僅采用能量有限的電池供電且很難得到補(bǔ)充，同時(shí)網(wǎng)絡(luò)中各節(jié)點(diǎn)往往處于能耗不均衡狀態(tài)，這些現(xiàn)狀嚴(yán)重制約了WSN的運(yùn)行壽命以及網(wǎng)絡(luò)的擴(kuò)容。 在低成本電池技術(shù)、新型能源技術(shù)等取得突破之前，能否有效提高WSN的能量效率是保證其廣泛、可靠部署與應(yīng)用的關(guān)鍵，其根本問題是如何減小WSN節(jié)點(diǎn)通信模塊所產(chǎn)生的通信能耗。本文針對(duì)上述問題，主要從如何設(shè)計(jì)高效的數(shù)據(jù)匯集方法的角度分析并解決問題。主要研究思路為：通過數(shù)據(jù)壓縮減少待匯集的數(shù)據(jù)總量，通過優(yōu)化傳輸機(jī)制提高數(shù)據(jù)匯集的效率。與此同時(shí)，壓縮感知和網(wǎng)絡(luò)編碼作為新興的信息技術(shù)，分別從數(shù)據(jù)壓縮和優(yōu)化傳輸?shù)慕嵌葹楦吣苄?shù)據(jù)匯集方法的設(shè)計(jì)提供了新思路。但是，這兩種技術(shù)單獨(dú)應(yīng)用于WSN數(shù)據(jù)匯集仍存在較大的缺陷與不足。 本文通過深入分析網(wǎng)絡(luò)編碼與壓縮感知的內(nèi)在聯(lián)系，利用WSN各節(jié)點(diǎn)感知數(shù)據(jù)的相關(guān)性以及無線傳輸?shù)膹V播特性，創(chuàng)新性的將網(wǎng)絡(luò)編碼與壓縮感知結(jié)合在一起，從聯(lián)合信源網(wǎng)絡(luò)編碼的角度提出了新型的高能效WSN數(shù)據(jù)匯集方案，稱之為壓縮網(wǎng)絡(luò)編碼方案（Compressed Network Coding，CNC）。本文首先對(duì)WSN中應(yīng)用壓縮感知與網(wǎng)絡(luò)編碼的可行性進(jìn)行了論證，建立了CNC數(shù)據(jù)匯集方案的系統(tǒng)框架；基于該系統(tǒng)框架，以分布式數(shù)據(jù)傳輸效率提升和網(wǎng)絡(luò)整體能耗降低為研究目標(biāo)，給出了CNC的一種具體實(shí)現(xiàn)方法——OMP-RL-CNC（Orthogonal Matching Pursuit Random Linear Compressed Network Coding）；進(jìn)而，，本文通過分析各個(gè)節(jié)點(diǎn)能耗情況，以增加一定的集中式調(diào)度操作為代價(jià)，給出了兩種在降低整體能耗的同時(shí)能實(shí)現(xiàn)能耗均衡的CNC實(shí)現(xiàn)方法——E-OMP-RL-CNC（Enhanced OMP-RL-CNC）、E2-OMP-RL-CNC（two-times Enhanced OMP-RL-CNC），這兩種方法綜合解決了能耗不均所致的關(guān)鍵節(jié)點(diǎn)過早失效的問題，有效地延長了網(wǎng)絡(luò)運(yùn)行壽命；最終，本文搭建了實(shí)際硬件平臺(tái)，對(duì)所提出的CNC方案進(jìn)行了實(shí)現(xiàn)與驗(yàn)證。 本文的主要工作可歸納為如下幾個(gè)方面： （1）建立基于CNC的WSN數(shù)據(jù)匯集方案的系統(tǒng)框架。通過分析WSN數(shù)據(jù)匯集的研究現(xiàn)狀，分析了現(xiàn)有數(shù)據(jù)匯集方法的優(yōu)缺點(diǎn)；通過分析廣義蝶形網(wǎng)絡(luò)的編碼增益、傳感器節(jié)點(diǎn)感知數(shù)據(jù)的相關(guān)性，論證了基于CNC進(jìn)行WSN數(shù)據(jù)匯集的可行性。在此基礎(chǔ)上，提出了CNC數(shù)據(jù)匯集方案的系統(tǒng)框架，其中包括網(wǎng)絡(luò)結(jié)構(gòu)、節(jié)點(diǎn)功能、節(jié)點(diǎn)工作模式等。 （2）給出了一種以分布式高效數(shù)據(jù)傳輸和網(wǎng)絡(luò)整體能耗降低為目標(biāo)的CNC數(shù)據(jù)匯集方案的具體實(shí)現(xiàn)方法——OMP-RL-CNC。基于CNC數(shù)據(jù)匯集方案的系統(tǒng)框架，設(shè)計(jì)了隨機(jī)線性實(shí)現(xiàn)的網(wǎng)絡(luò)編碼向量，使得網(wǎng)絡(luò)編碼的全局編碼矩陣滿足RIP（Restricted Isometry Property）特性要求。并且，將面向壓縮感知重構(gòu)的OMP解碼算法結(jié)合進(jìn)來，有效的解決了基于有限域的隨機(jī)線性網(wǎng)絡(luò)編碼（Finite Field based Random Linear Network Coding，F(xiàn)FRL-NC）所存在的“全有全無”問題以及對(duì)有限域依賴所導(dǎo)致的重構(gòu)效率較低的問題。該方法在待匯集數(shù)據(jù)量相同的情況下，相對(duì)已有方法在全網(wǎng)范圍內(nèi)降低了數(shù)據(jù)包傳輸次數(shù)，進(jìn)而降低了整網(wǎng)能耗。 （3）通過改進(jìn)OMP-RL-CNC，進(jìn)一步給出了兩種能實(shí)現(xiàn)能耗均衡的CNC實(shí)現(xiàn)方法——E-OMP-RL-CNC、E2-OMP-RL-CNC。這兩種方法以最大化網(wǎng)絡(luò)壽命為目標(biāo)，以增加一定的集中式調(diào)度操作為代價(jià)。通過與已有數(shù)據(jù)匯集方法中具有代表性的匯聚樹路由協(xié)議（Collection Tree Protocol，CTP）、傳統(tǒng)網(wǎng)絡(luò)編碼（Network Coding，NC）數(shù)據(jù)傳輸方案進(jìn)行仿真對(duì)比分析，驗(yàn)證了E-OMP-RL-CNC、E2-OMP-RL-CNC可綜合解決WSN數(shù)據(jù)匯集的能效問題：不僅能有效節(jié)約整體網(wǎng)絡(luò)能耗、還能實(shí)現(xiàn)能耗均衡。 （4）通過硬件測(cè)試平臺(tái)對(duì)所提方法進(jìn)行了實(shí)現(xiàn)與驗(yàn)證。搭建了室外無線傳感器網(wǎng)絡(luò)環(huán)境，并在該環(huán)境下實(shí)現(xiàn)了本文提出的三種CNC數(shù)據(jù)匯集方法。基于實(shí)測(cè)數(shù)據(jù)分析了網(wǎng)絡(luò)中各節(jié)點(diǎn)的能耗情況，實(shí)驗(yàn)驗(yàn)證了所提方法解決WSN能效問題的有效性。
[Abstract]:As one of the top ten emerging technologies in the 21st century , Wireless Sensor Network ( WSN ) has realized the connection between physical world and information network world through the fusion of sensing technology , microelectronic process and wireless network .

In order to improve the energy efficiency of WSN , it is the key to ensure its extensive , reliable deployment and application before the breakthrough of low cost battery technology and new energy technology . The fundamental problem is how to reduce the communication energy consumption of WSN node communication module .

In this paper , we deeply analyze the relationship between network coding and compression perception , use the relativity of the sensor data of WSN and the broadcast characteristics of wireless transmission , combine the network coding with the compression perception , propose a new high energy efficiency WSN data collection scheme from the angle of joint source network coding , which is called the compressed network coding scheme ( CNC ) . Firstly , the feasibility of applying compression sensing and network coding in WSN is demonstrated , and the system framework of CNC data collection scheme is established .
Based on the framework of the system , the distributed data transmission efficiency and the overall energy consumption of the network are reduced to the research target , and a concrete realization method of CNC _ OMP - RL - CNC ( Orthogonal Matching Random Linear Compressed Network Coding ) is given .
Furthermore , by analyzing the energy consumption of each node , this paper presents two CNC realizing methods _ E - OMP - RL - CNC ( Enhanced OMP - RL - CNC ) , E2 - OMP - RL - CNC ( two - times Enhanced OMP - RL - CNC ) , which can reduce the whole energy consumption while reducing the whole energy consumption .
Finally , the practical hardware platform is set up , and the CNC solution is implemented and verified .

The main work of this paper can be summarized as follows :

( 1 ) establishing a system framework of a CNC - based data collection scheme of the WSN , analyzing the research status of the WSN data collection , and analyzing the advantages and disadvantages of the existing data collection method ;
Based on the analysis of the correlation between coding gain and sensor node perception data of generalized butterfly network , the feasibility of data collection based on CNC is demonstrated . On this basis , a system framework of CNC data collection scheme is proposed , including network structure , node function , node operation mode , etc .

( 2 ) A concrete implementation method _ OMP - RL - CNC based on distributed high - efficiency data transmission and reduction of total energy consumption of network is presented . A random linear implemented network coding vector is designed based on CNC data aggregation scheme .

( 3 ) By improving OMP - RL - CNC , two kinds of CNC realizing methods _ E - OMP - RL - CNC , E2 - OMP - RL - CNC , which can realize energy consumption equalization , are given .

( 4 ) The method is realized and verified by the hardware test platform . The outdoor wireless sensor network environment is built , and the three kinds of CNC data collection methods presented in this paper are realized under the environment . Based on the measured data , the energy consumption of each node in the network is analyzed , and the proposed method is verified to solve the problem of energy efficiency of WSN .
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5;TP212.9

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本文編號(hào)：2123712