本文選題：仿生自主神經(jīng)系統(tǒng)　切入點(diǎn)：監(jiān)控　出處：《電子科技大學(xué)》2017年博士論文　論文類型：學(xué)位論文

【摘要】：隨著云計(jì)算技術(shù)的快速發(fā)展和應(yīng)用普及,使得以往分散的資源再次呈現(xiàn)出集中的趨勢(shì),這使得云計(jì)算環(huán)境的規(guī)模也相應(yīng)的變的越來越大,復(fù)雜性也相應(yīng)提高。如何保障云計(jì)算環(huán)境的可靠運(yùn)行,如何有效的評(píng)價(jià)云計(jì)算環(huán)境的服務(wù)性能,又該如何應(yīng)對(duì)云計(jì)算環(huán)境龐大的能耗問題,以及研究有效處理用戶服務(wù)請(qǐng)求和資源優(yōu)化供給之間的均衡優(yōu)化調(diào)度,都成為迫切的需求。針對(duì)于此,必須對(duì)可靠計(jì)算、高性能計(jì)算和節(jié)能計(jì)算技術(shù)進(jìn)行深入研究,綜合可靠性、性能和能耗等多指標(biāo),建立多維關(guān)聯(lián)的評(píng)估模型,并基于綜合評(píng)估模型研究面向多目標(biāo)的均衡調(diào)度機(jī)制。為了保障可靠性,監(jiān)控是重要的保障手段,但現(xiàn)有監(jiān)控缺乏自主自治能力,系統(tǒng)架構(gòu)也不太適合云計(jì)算環(huán)境;為了進(jìn)行性能評(píng)估,必須充分考慮云服務(wù)的特征才能建立合適的性能模型,并有效考慮可靠性對(duì)性能的影響才能更準(zhǔn)確的評(píng)估云服務(wù)的性能;為了節(jié)能高效計(jì)算,傳統(tǒng)方法僅將能耗和性能作為相互制約的因素,而忽略了可靠性。在已有的研究中,將可靠性、性能和能耗分離割裂的評(píng)估建模,也導(dǎo)致了基于相關(guān)模型的優(yōu)化調(diào)度帶有局限性。針對(duì)以上問題,本文主要研究了面向云計(jì)算環(huán)境的仿生自主監(jiān)控系統(tǒng)和多指標(biāo)關(guān)聯(lián)的均衡調(diào)度機(jī)制,主要研究?jī)?nèi)容及貢獻(xiàn)體現(xiàn)在四個(gè)方面,如下:1)針對(duì)傳統(tǒng)監(jiān)控系統(tǒng)擴(kuò)展性差、缺乏自主性,以及未能充分考慮云計(jì)算虛擬化和動(dòng)態(tài)彈性等問題,設(shè)計(jì)了一種具備仿生自主神經(jīng)系統(tǒng)特征的云監(jiān)控系統(tǒng)。該云監(jiān)控系統(tǒng)具備“人機(jī)交互層——中樞神經(jīng)系統(tǒng)層——周圍神經(jīng)系統(tǒng)層——神經(jīng)元層——神經(jīng)突軸層”五層的分層架構(gòu),融入自組織、自診斷、自修復(fù)和自行為等自主特性。新的架構(gòu)設(shè)計(jì),采用周圍神經(jīng)和神經(jīng)元的結(jié)構(gòu)能充分反映虛擬資源的宿主特性,同時(shí)設(shè)計(jì)周圍神經(jīng)系統(tǒng)內(nèi)部的自治特性,即能完成自治任務(wù),也可有效減輕中樞壓力;逐級(jí)擴(kuò)展的樹型結(jié)構(gòu)賦予系統(tǒng)良好的擴(kuò)展性。將自主特性融入云監(jiān)控系統(tǒng),有效提升了監(jiān)控系統(tǒng)對(duì)規(guī)模復(fù)雜云計(jì)算環(huán)境的適應(yīng)性和健壯性,并利于自動(dòng)擴(kuò)展。通過自組織功能有效解決了規(guī)模虛擬化資源因動(dòng)態(tài)變化(加入、退出等)帶來的監(jiān)控難和部署繁瑣問題;通過自診斷和自修復(fù)提升云監(jiān)控系統(tǒng)自身的穩(wěn)定可靠性;通過自行為模塊的設(shè)計(jì),不僅增強(qiáng)了系統(tǒng)的擴(kuò)展功能,也減少了不必要的數(shù)據(jù)傳輸,降低了對(duì)系統(tǒng)的開銷。2)針對(duì)傳統(tǒng)性能評(píng)估忽略可靠性的問題,提出了一個(gè)面向云服務(wù)特征的關(guān)聯(lián)“可靠性——性能”的性靠度模型。云計(jì)算環(huán)境具有異構(gòu)性、虛擬化和按需服務(wù)特征,其關(guān)聯(lián)性能(性靠度)評(píng)估模型也因此不同�？紤]虛擬資源的失效和修復(fù)行為,運(yùn)用Markov鏈對(duì)其可靠性進(jìn)行評(píng)估,提出采用通用生成函數(shù)(Universal Generating Function,UGF)分析異構(gòu)云資源池可靠性的方法;考慮按需服務(wù)特性,分析1:1和1:D映射模式下云服務(wù)的不同性能,建立反映請(qǐng)求生滅過程的云服務(wù)系統(tǒng)性能模型;考慮資源可靠隨機(jī)性對(duì)服務(wù)性能隨機(jī)性的影響,通過Baysian方法將可靠性、性能模型關(guān)聯(lián),建立新的面向云計(jì)算特征的性靠度模型。實(shí)驗(yàn)結(jié)果表明,該二維關(guān)聯(lián)建模方法,能更準(zhǔn)確的評(píng)價(jià)真實(shí)云計(jì)算環(huán)境的服務(wù)性能。其意義還在于,提供了一種通用的分析不同的性靠度關(guān)聯(lián)的方法。3)針對(duì)傳統(tǒng)評(píng)估方法將可靠性、性能和能耗指標(biāo)割裂開來的不足,以及云計(jì)算環(huán)境所面臨的嚴(yán)重能耗的現(xiàn)實(shí)問題,提出了一種關(guān)聯(lián)“可靠性——性能——能耗”的多維關(guān)聯(lián)的層級(jí)建模方法,建立綜合性評(píng)估指標(biāo)。該層級(jí)建模的思想是:提出和求解一個(gè)復(fù)雜系統(tǒng)的全局模型往往較為復(fù)雜,本文采取將全局模型分解為覆蓋交互因子的多個(gè)子模型的方法,然后通過對(duì)子模型的迭代求解可以獲得全局模型,以順利的完成系統(tǒng)的整體評(píng)估。在云計(jì)算環(huán)境中,多維層次模型的關(guān)聯(lián)交互存在一個(gè)共同的條件參數(shù)——“可用資源隨機(jī)數(shù)量”,基于該條件參數(shù)所建立的各個(gè)子模型,最后可通過Bayesian途徑,移除條件參數(shù),最終整合各個(gè)子模型,并獲得多指標(biāo)關(guān)聯(lián)的綜合性評(píng)價(jià)指標(biāo)——期望性能和期望能耗。采用該方法,本文將基于真實(shí)采樣數(shù)據(jù)進(jìn)行統(tǒng)計(jì)分析所獲得的能耗模型與可靠性和性能關(guān)聯(lián),通過實(shí)驗(yàn)驗(yàn)證了多維關(guān)聯(lián)的能耗評(píng)估的有效性。4)針對(duì)云計(jì)算環(huán)境所面臨的復(fù)雜供需制約調(diào)度需求,及現(xiàn)有層次化調(diào)度缺乏自主性和優(yōu)化調(diào)度目標(biāo)單一等問題,提出了一種分層優(yōu)化調(diào)度模型和多指標(biāo)聯(lián)合優(yōu)化的調(diào)度策略。其具體工作機(jī)制為:全局代理負(fù)責(zé)全局的任務(wù)分發(fā),體現(xiàn)集中管控;局部代理實(shí)現(xiàn)區(qū)域自治,通過本地自主計(jì)算形成反映任務(wù)不同分配情況的局部資源優(yōu)化的“供需地圖”,在多指標(biāo)聯(lián)合的利潤(rùn)目標(biāo)優(yōu)化下實(shí)現(xiàn)資源的合理調(diào)度供給以匹配全局代理動(dòng)態(tài)變化的任務(wù)需求。在局部?jī)?yōu)化的基礎(chǔ)上,利用反映多維關(guān)聯(lián)的優(yōu)化函數(shù),設(shè)計(jì)具體的遺傳算法進(jìn)行問題的求解,實(shí)現(xiàn)多目標(biāo)聯(lián)合優(yōu)化下的全局最優(yōu)。實(shí)驗(yàn)結(jié)果表明該分層優(yōu)化調(diào)度機(jī)制能夠提高搜索最優(yōu)解的效率,可以獲得綜合的優(yōu)化效果。
[Abstract]:With the rapid development and popularization of the application of cloud computing technology, which makes distributed resources once again showing the concentration trend, which makes the scale of cloud computing environment also become more and more big, the complexity is increased accordingly. How to ensure the reliable operation of the cloud computing environment, such as service performance evaluation of any effective cloud computing environment the problem of energy consumption, environmental computation and how to deal with the cloud, and study the effective treatment of equilibrium between user service request scheduling and optimization of resource supply, has become the urgent demand. According to this, must be reliable computing, high performance computing and saving computing technology in-depth research, comprehensive reliability, performance and energy consumption etc. multi index evaluation model, multidimensional association, and the scheduling mechanism for multi-objective comprehensive evaluation model based on. In order to ensure the reliability, monitoring is an important guarantee But the existing monitoring means, lack of autonomy ability, system architecture is not suitable for cloud computing environment; in order to evaluate the performance, must fully consider the characteristics of cloud services to establish suitable performance models, and consider the performance reliability of the performance impact of cloud services to assess more accurately; in order to energy efficient computing, traditional method only the energy consumption and performance as factors restrict each other, while ignoring the reliability. In the previous study, the reliability evaluation model of separation between performance and energy consumption, also led to the optimization of scheduling based on correlation model with limitations. In view of the above problems, this paper mainly studies the Bionics for cloud computing scheduling mechanism independent monitoring system and related indicators, the main research contents and contributions are in four aspects: 1) the traditional monitoring system scalability, lack of self The Lord, and do not consider the virtual and dynamic elastic problems such as cloud computing, design a cloud monitoring system with bionic autonomic nervous system characteristics. The cloud monitoring system with hierarchical architecture of human-computer interaction layer of central nervous system, peripheral nervous system neurons - layer - layer neural axonal layer "the five layer, into self organization, self diagnosis, self repair and self independent characteristics. The new architecture design, the structure and characteristics of host peripheral nerve neurons can fully reflect the virtual resource, and design of autonomous internal characteristics of the peripheral nervous system, which can accomplish autonomous tasks, can effectively alleviate the central pressure; the tree structure gradually extended to the good scalability of the system. The independent characteristics into the cloud monitoring system, improve the monitoring system of computing environment adaptability and robustness of complex cloud scale And, to automatically expand. Through the self-organization function effectively solves the scale of virtualized resources due to dynamic changes (join, exit) caused by monitoring difficult and complicated problems through deployment; self diagnosis and self repair to enhance reliability of cloud monitoring system's stability; by module design, not only enhances the expansion function of the system also, reduce the unnecessary data transmission, reduces the system overhead of.2) to assess the reliability of the traditional ignore performance, proposed a feature oriented Cloud Service Association "reliability performance" of reliability model. Cloud computing environment is heterogeneous, virtualization and on-demand service features. The association performance evaluation model (of reliability) are so different. Considering the virtual resource failure and repair, the use of Markov chain to assess its reliability, the general production function (Universal Ge Nerating Function, UGF) analysis method of heterogeneous cloud resource pool reliability; according to need service characteristics, analysis of different performance of cloud services 1:1 and 1:D mapping mode, the establishment of performance reflect the request of cloud service system model of the birth and death process; considering the influence on the performance of reliable resources random random, through the Baysian method to reliability the performance model, association, build cloud computing features of the new reliability model. The experimental results show that the two-dimensional correlation modeling method can more accurately evaluate the real cloud service performance computing environment. Its significance lies, provides a general analysis of different methods on the degree of the associated.3) for the traditional evaluation method of reliability, low performance and energy consumption index separated, serious problems of energy consumption and cloud computing environment, proposes a reliable performance of association "- - hierarchical modeling method of multidimensional association energy consumption ", the establishment of a comprehensive evaluation index. The hierarchical modeling idea is put forward: the global model and solving a complex system is often complex, this paper adopts the global model is decomposed into several sub models covering the interaction factor, and then through the iterative sub model can be obtained the global model, in order to complete the whole evaluation system smoothly. In the cloud computing environment, related multidimensional hierarchical model interaction there is a common condition -" random number of available resources, each sub model parameters based on the condition, finally through the Bayesian pathway, remove the condition parameters, final integration sub model and multi index comprehensive evaluation index association -- expected performance and expected energy consumption. Using this method, this paper will be based on the real data sampling system The analysis model of energy consumption and reliability and performance, through experimental verification of the.4 effectiveness evaluation of the Energy Association) for cloud computing complex supply and demand facing the environment and the existing scheduling needs, hierarchical scheduling scheduling problems such as lack of autonomy and single objective optimization, this paper proposed a novel scheduling model and multi joint optimization index hierarchical optimization scheduling strategy. The specific mechanism for global agency is responsible for the global task distribution, reflect centralized management; implementation of regional autonomy of local agents, through local autonomic computing form reflect the distribution of the different tasks of local resource optimization "supply and demand map", the supply of resources in a reasonable scheduling optimization combined with profit the parameters to match the dynamic changes of the global agency requirements. Based on local optimization, the optimization of the letter reflects the Multidimensional Association Number, we design specific genetic algorithm to solve the problem, and achieve the global optimization under multi-objective joint optimization. The experimental results show that the hierarchical optimization scheduling mechanism can improve the efficiency of search optimal solution, and achieve comprehensive optimization results.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP393.09

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