本文選題：網(wǎng)絡(luò)功能虛擬化 + 故障檢測�。� 參考：《電子科技大學(xué)》2017年碩士論文

【摘要】：為了滿足日益增長的網(wǎng)絡(luò)服務(wù)需求,越來越多的網(wǎng)絡(luò)中間件被部署到網(wǎng)絡(luò)中使得網(wǎng)絡(luò)僵化問題嚴(yán)重。網(wǎng)絡(luò)功能虛擬化從運營商的角度對現(xiàn)有網(wǎng)絡(luò)架構(gòu)進行改造,通過軟硬件資源解耦,將各種網(wǎng)絡(luò)硬件設(shè)備整合到行業(yè)標(biāo)準(zhǔn)的x86服務(wù)器中并使用軟件實現(xiàn)的網(wǎng)絡(luò)功能來替代專有設(shè)備的功能,有效提升了網(wǎng)絡(luò)功能的開發(fā)效率,也使得網(wǎng)絡(luò)功能的部署和管理更加靈活方便。自提出以來,網(wǎng)絡(luò)功能虛擬化已在學(xué)術(shù)界和工業(yè)界引起了廣泛的關(guān)注。然而網(wǎng)絡(luò)功能虛擬化在提升效率的同時,也給網(wǎng)絡(luò)可靠性帶來一些挑戰(zhàn)。虛擬化的過程占用額外的系統(tǒng)資源,而且虛擬節(jié)點相較于傳統(tǒng)物理節(jié)點更加復(fù)雜。這些因素導(dǎo)致網(wǎng)絡(luò)功能虛擬化環(huán)境下具有更高的故障發(fā)生概率。故障發(fā)生后,能否快速準(zhǔn)確地進行故障檢測和定位對于維護系統(tǒng)長期穩(wěn)定可靠地提供服務(wù)至關(guān)重要。故障管理是網(wǎng)絡(luò)管理的一項基本內(nèi)容,其目標(biāo)是盡快消除故障并恢復(fù)服務(wù)的正常運行,以滿足和用戶達成的服務(wù)等級協(xié)議的要求。本文對網(wǎng)絡(luò)功能虛擬化環(huán)境下的故障檢測和故障定位等兩項核心技術(shù)進行了研究。故障檢測負責(zé)捕獲系統(tǒng)發(fā)生的故障,而故障定位負責(zé)對故障的原因和位置進行定位。針對網(wǎng)絡(luò)功能虛擬化的環(huán)境特性以及傳統(tǒng)數(shù)值檢測技術(shù)的缺陷,本文基于無監(jiān)督機器學(xué)習(xí)的方法構(gòu)建故障檢測模型。提出了一種基于模型融合的無監(jiān)督故障檢測機制,該機制可以有效覆蓋傳統(tǒng)檢測算法的檢測盲區(qū)并提高檢測性能。此外,本文還針對突發(fā)特性造成的錯誤告警現(xiàn)象進行處理,提出了基于時間窗的修正機制過濾錯誤告警。在故障定位方面,本文對網(wǎng)絡(luò)功能虛擬化環(huán)境下故障原因定位和故障位置定位的方法進行了研究,提出了一種基于相關(guān)性分析的分層故障定位機制。該機制基于時間和特征變異程度的相關(guān)性分析對故障原因進行定位,基于時間、服務(wù)功能鏈和資源共享等方面的相關(guān)性分析對故障位置進行定位。通過拓展依賴關(guān)系圖增加服務(wù)功能鏈引入的相關(guān)性,可有效提高定位結(jié)果的準(zhǔn)確性。定位機制通過“自頂向下,逐層定位”的實施原則集成各個層次的定位結(jié)果,突破了信息獲取受限的瓶頸。本文以三層云服務(wù)為基礎(chǔ)搭建仿真環(huán)境,并向其中注入幾種不同類型故障進行實驗,仿真結(jié)果顯示本文提出的解決方案可以有效檢測并定位注入的故障。
[Abstract]:In order to meet the increasing demand for network services, more and more network middleware is deployed to the network, which makes the network rigid. Network function virtualization transforms the existing network architecture from the point of view of the operator and decouples it through software and hardware resources. Integrating all kinds of network hardware devices into the industry standard x86 server and using the network function realized by the software to replace the function of the proprietary equipment, the development efficiency of the network function is improved effectively. It also makes the deployment and management of network functions more flexible and convenient. Since it was put forward, network function virtualization has attracted wide attention in academia and industry. However, network function virtualization not only improves efficiency, but also brings some challenges to network reliability. The virtualization process takes up additional system resources, and virtual nodes are more complex than traditional physical nodes. These factors lead to higher probability of failure in virtualization of network function. After the fault occurs, it is very important to quickly and accurately detect and locate the fault for the maintenance system to provide service stably and reliably for a long time. Fault management is one of the basic contents of network management. Its goal is to eliminate the fault as soon as possible and resume the normal operation of the service to meet the requirements of the service level agreement reached with the user. In this paper, two core technologies, such as fault detection and fault location, are studied in network function virtualization environment. Fault detection is responsible for capturing the fault of the system, and fault location is responsible for locating the cause and location of the fault. Aiming at the environmental characteristics of network function virtualization and the shortcomings of traditional numerical detection techniques, this paper constructs a fault detection model based on unsupervised machine learning. An unsupervised fault detection mechanism based on model fusion is proposed, which can effectively cover the blind areas of traditional detection algorithms and improve detection performance. In addition, this paper also deals with the error alarm caused by burst characteristics, and proposes a time window based correction mechanism to filter error alarm. In the aspect of fault location, this paper studies the methods of fault cause location and fault location in network function virtualization environment, and proposes a hierarchical fault location mechanism based on correlation analysis. The mechanism is based on the correlation analysis of time and degree of feature variation to locate the fault cause, and based on the correlation analysis of time, service function chain and resource sharing to locate the fault location. By extending the dependency graph to increase the correlation introduced by the service function chain, the accuracy of the location results can be improved effectively. The localization mechanism integrates the localization results of different levels through the implementation principle of "top-down, location-by-layer", which breaks through the bottleneck of limited access to information. This paper builds a simulation environment based on the three-layer cloud service, and injects several different types of faults into the simulation environment. The simulation results show that the proposed solution can effectively detect and locate the injected faults.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP393.0

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本文編號：1996740