本文關(guān)鍵詞：面向復(fù)雜網(wǎng)絡(luò)的節(jié)點(diǎn)重要性排序和級(jí)聯(lián)失效研究　出處：《重慶大學(xué)》2016年博士論文　論文類型：學(xué)位論文

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【摘要】：20世紀(jì)90年代末期,隨著小世界網(wǎng)絡(luò)和無標(biāo)度網(wǎng)絡(luò)模型的提出,復(fù)雜網(wǎng)絡(luò)的研究進(jìn)入了一個(gè)嶄新的階段,越來越多的人開始關(guān)注復(fù)雜網(wǎng)絡(luò)。作為復(fù)雜性科學(xué)的一個(gè)重要分支,復(fù)雜網(wǎng)絡(luò)的理論研究得到飛速發(fā)展,并且已經(jīng)滲透到數(shù)理學(xué)科、生命科學(xué)以及工程學(xué)科等各種領(lǐng)域。當(dāng)今隨著物聯(lián)網(wǎng)的興起和發(fā)展,智慧城市進(jìn)程的加快,各種網(wǎng)絡(luò)系統(tǒng)紛紛涌現(xiàn)并得到快速發(fā)展,人類社會(huì)生活已經(jīng)越來越依賴這些基礎(chǔ)設(shè)施網(wǎng)絡(luò)系統(tǒng),如電力網(wǎng)絡(luò)、通信網(wǎng)絡(luò)、Internet、航空網(wǎng)絡(luò)以及物流網(wǎng)絡(luò)等等。這些基礎(chǔ)設(shè)施網(wǎng)絡(luò)在為人類生活帶來便利的同時(shí)也埋下了安全隱患,如交通網(wǎng)絡(luò)的擁堵、大面積的停電事故等等�，F(xiàn)實(shí)世界中的這些網(wǎng)絡(luò)大都可以抽象成復(fù)雜網(wǎng)絡(luò),復(fù)雜網(wǎng)絡(luò)為研究現(xiàn)實(shí)網(wǎng)絡(luò)系統(tǒng)提供了一種新的途徑。通過對(duì)基礎(chǔ)設(shè)施系統(tǒng)災(zāi)難性事件的分析發(fā)現(xiàn),重要節(jié)點(diǎn)以及級(jí)聯(lián)失效現(xiàn)象對(duì)基礎(chǔ)設(shè)施系統(tǒng)功能的影響非常大,因此,本文從網(wǎng)絡(luò)節(jié)點(diǎn)重要性識(shí)別和級(jí)聯(lián)失效兩個(gè)方面對(duì)復(fù)雜網(wǎng)絡(luò)進(jìn)行研究,旨在減少基礎(chǔ)設(shè)施系統(tǒng)中災(zāi)難性事件的發(fā)生避免不必要的經(jīng)濟(jì)損失。雖然現(xiàn)有的相關(guān)研究已經(jīng)取得了一些理論成果,但仍存在很多問題有待進(jìn)一步研究。復(fù)雜網(wǎng)絡(luò)中節(jié)點(diǎn)的重要性排序一直是很多學(xué)者所關(guān)注的研究熱點(diǎn),現(xiàn)有的基于全局信息的方法,如介數(shù)中心性,能夠較為有效地判斷節(jié)點(diǎn)的重要性,但計(jì)算復(fù)雜度高;基于局域信息的方法,雖然降低了計(jì)算復(fù)雜度,但排序精度有待進(jìn)一步提高。另外,目前關(guān)于復(fù)雜網(wǎng)絡(luò)級(jí)聯(lián)失效模型的研究也很多,但很多模型沒有考慮網(wǎng)絡(luò)負(fù)載的時(shí)變特性,負(fù)載重分配的不合理性很可能擴(kuò)大網(wǎng)絡(luò)級(jí)聯(lián)失效的規(guī)模。鑒于此,本文從網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)入手,基于網(wǎng)絡(luò)的局域信息,考慮節(jié)點(diǎn)和邊的相互影響提出了一種新的節(jié)點(diǎn)重要性排序方法,同時(shí)研究了時(shí)變負(fù)載對(duì)網(wǎng)絡(luò)級(jí)聯(lián)失效的影響,并提出了一種新的級(jí)聯(lián)失效模型,減小負(fù)載時(shí)變網(wǎng)絡(luò)級(jí)聯(lián)失效的規(guī)模。另外,考慮人為干預(yù)對(duì)網(wǎng)絡(luò)級(jí)聯(lián)失效的影響,研究了過載節(jié)點(diǎn)崩潰概率對(duì)網(wǎng)絡(luò)級(jí)聯(lián)失效的影響,并提出了相應(yīng)的保護(hù)資源分配策略,又考慮現(xiàn)實(shí)網(wǎng)絡(luò)間的相互依賴關(guān)系,研究了耦合作用下網(wǎng)絡(luò)級(jí)聯(lián)失效的影響因素。具體工作如下:(1)考慮網(wǎng)絡(luò)中節(jié)點(diǎn)和邊的相互依存相互影響,提出了一種基于邊重要性的節(jié)點(diǎn)重要性排序方法。該方法首先根據(jù)邊的端節(jié)點(diǎn)的屬性提出邊的重要性計(jì)算方法,然后根據(jù)端節(jié)點(diǎn)對(duì)該邊重要性的貢獻(xiàn)率確定該邊的重要性對(duì)端節(jié)點(diǎn)重要性的影響力,最后根據(jù)節(jié)點(diǎn)的連邊數(shù)量和各連邊對(duì)節(jié)點(diǎn)重要性的貢獻(xiàn)值來判斷節(jié)點(diǎn)的重要性。以節(jié)點(diǎn)移除后網(wǎng)絡(luò)效率的下降率為評(píng)價(jià)指標(biāo)兼顧方法的計(jì)算復(fù)雜度來綜合評(píng)價(jià)節(jié)點(diǎn)重要性排序方法的優(yōu)劣。(2)考慮網(wǎng)絡(luò)負(fù)載的時(shí)變特性,基于節(jié)點(diǎn)的實(shí)時(shí)剩余容量,提出一種時(shí)變負(fù)載重分策略,并以此策略構(gòu)建新的級(jí)聯(lián)失效模型。以節(jié)點(diǎn)移除后導(dǎo)致的失效節(jié)點(diǎn)的比例的歸一化指標(biāo)作為網(wǎng)絡(luò)抵御級(jí)聯(lián)失效能力的評(píng)價(jià)指標(biāo),并通過算例分析、數(shù)值模擬和實(shí)例仿真研究了負(fù)載重分策略對(duì)網(wǎng)絡(luò)抵御級(jí)聯(lián)失效能力的影響。相比已有的基于固定負(fù)載重分策略的級(jí)聯(lián)失效模型,新模型能夠根據(jù)失效節(jié)點(diǎn)的鄰節(jié)點(diǎn)的實(shí)時(shí)負(fù)載處理能力來對(duì)失效節(jié)點(diǎn)的負(fù)載進(jìn)行重新分配,具有極強(qiáng)的抗干擾能力。在網(wǎng)絡(luò)負(fù)載時(shí)變的情況下,新模型能夠有效提高網(wǎng)絡(luò)抵御級(jí)聯(lián)失效的能力。(3)不同于現(xiàn)有的大多數(shù)研究,本文考慮過載節(jié)點(diǎn)由于保護(hù)機(jī)制的存在可能不會(huì)立刻失效的情況,基于現(xiàn)有研究提出了一種改進(jìn)的帶有崩潰概率的級(jí)聯(lián)失效模型。同樣地,以節(jié)點(diǎn)移除后導(dǎo)致的失效節(jié)點(diǎn)的比例的歸一化指標(biāo)作為網(wǎng)絡(luò)抵御級(jí)聯(lián)失效的能力的評(píng)價(jià)指標(biāo),通過算例分析、數(shù)值模擬和實(shí)例仿真研究了模型中的參數(shù)對(duì)網(wǎng)絡(luò)級(jí)聯(lián)失效規(guī)模的影響,并提出了相應(yīng)的保護(hù)資源分配策略,為網(wǎng)絡(luò)中保護(hù)機(jī)制的建立和保護(hù)資源的分配提供了依據(jù)。(4)考慮網(wǎng)絡(luò)的負(fù)載特性,基于兩種失效模式對(duì)不同條件下網(wǎng)絡(luò)間耦合作用對(duì)網(wǎng)絡(luò)抵御級(jí)聯(lián)失效能力的影響進(jìn)行研究,旨在找到能有效降低相依網(wǎng)絡(luò)級(jí)聯(lián)失效規(guī)模的途徑和策略。數(shù)值模擬和實(shí)例分析結(jié)果顯示,相似耦合比隨機(jī)耦合更有利于降低耦合作用對(duì)網(wǎng)絡(luò)抵御級(jí)聯(lián)失效能力的影響,網(wǎng)絡(luò)的容量閾值是影響相依網(wǎng)絡(luò)級(jí)聯(lián)失效規(guī)模的關(guān)鍵因素,直接決定其他因素對(duì)網(wǎng)絡(luò)抵御級(jí)聯(lián)失效能力的影響程度。另外,相比降序解耦,按照耦合節(jié)點(diǎn)度從小到大的升序解耦更有利于降低耦合作用對(duì)網(wǎng)絡(luò)抵御級(jí)聯(lián)失效能力的影響從而減少網(wǎng)絡(luò)失效節(jié)點(diǎn)的規(guī)模。
[Abstract]:At the end of 1990s, with the small world network and scale-free network model was proposed, the study of complex networks has entered a new stage, more and more people begin to pay attention to complex networks. As an important branch of complexity science, complex network theory have developed rapidly, and has penetrated into the Mathematical Sciences, life science and engineering and other fields. With the rise and development of the Internet of things, the wisdom of the city to speed up the process, various network systems have emerged and got rapid development, human social life has been increasingly dependent on the network infrastructure system, such as power network, communication network, Internet network, aviation and logistics network and so on. These the infrastructure network brings to human life convenience also buried a security risk, such as traffic congestion, large area blackout etc. In the real world. Most of these networks can be abstracted into a complex network, complex network provides a new way for the study of the real network system. Through the analysis of the disaster infrastructure system events, important nodes and cascading failure phenomena influence the infrastructure system function is very large, therefore, this article from the network node the importance of identifying and cascading failures in two aspects of research on complex networks, to reduce the catastrophic events in the infrastructure system to avoid unnecessary economic losses. Although the existing research has made some achievements, but there are still many problems need to be further studied. The importance of nodes in complex networks has been a hot research topic ranking many scholars have paid close attention to the existing method based on global information, such as betweenness centrality, can effectively determine the node weight To, but high computational complexity; method based on local information, while reducing the computational complexity, but the sorting accuracy needs to be improved. In addition, the current research on complex network model of cascading failure are many, but many models do not consider the network load time-varying, unreasonable load redistribution is likely to expand the scale of cascading failure. In view of this, this article from the network topology of network based on local information, consider the interaction of nodes and edges presents a new node importance ranking method, and research the influence of time-varying load on the failure of cascade network, and proposes a new cascading failure model of cascading failure load decreases in size. In addition, consider the impact of human intervention on the failure of network cascade, studied the effect of overload node breakdown probability for cascading failure, and The protection of resource allocation strategies, and consider the relationship between the network reality, studies the factors that influence the coupling effects of cascading failure. The specific work is as follows: (1) considering the nodes and edges in the network depend on each other, this paper presents a ranking method based on the importance of edge node importance are calculated. First this method according to the attribute importance end node edge of the edge, and then according to the end node contribution to the edge of the importance of determining the importance of the edge rate of end node importance influence, according to the contribution to the importance of nodes and the number of edges with node boundary value to determine the importance of nodes to decrease node. After removing the network efficiency is one of the indicators for the evaluation of both the calculation method of quality comprehensive evaluation of node importance ranking method complexity. (2) considering the time-varying characteristics of the load of the network Real time, the residual capacity of nodes based on a time-varying load redistribution strategy, and the strategy of constructing the new model of cascading failure. The evaluation index to remove nodes leads to the normalized index as the proportion of the failure node network against cascading failure ability, and through the example analysis, numerical simulation and Simulation Study on the effect of load redistribution strategy on network against cascading failure ability. Compared with the existing fixed load redistribution cascade strategy based on failure model, the new model can according to the failure node node real-time load processing capacity to redistribute the load failure node, has strong anti-interference ability in the network. When the load change, the new model can effectively improve the ability to resist the network cascading failure. (3) different from most of the existing research, this paper considers the overload protection mechanism for node The problems may not immediately failure, the existing research puts forward a kind of improved with the breakdown probability of cascading failure model based on. Similarly, the evaluation to remove nodes leads to the normalized index proportion of failure nodes as the network ability to resist cascading failure, through the example analysis, numerical simulation and simulation research the parameters of the model scale effect on cascading failure, and puts forward some corresponding resource allocation strategy, provide the basis for the allocation of protection mechanism of the establishment and protection of resources in the network. (4) considering the load characteristics of the network, to study the effects of two kinds of failure modes under different conditions, the coupling between network resist cascade to network failure based on ability, in order to find can effectively reduce the dependence of cascading failure path and strategy scale. Numerical simulation and example analysis results show A similar effect, reduce the coupling effect on the network against cascading failures than random coupling coupling ability is more conducive to the threshold of the network capacity is a key factor affecting the scale dependence of cascading failure, directly determines the influence of other factors on the network against cascading failure ability. In addition, compared with the descending decoupling effect in ascending decoupling more coupling degree from small to large to reduce the coupling effect of the network against cascading failure ability so as to reduce the network node size.

【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：O157.5

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