本文選題：信息物理系統(tǒng) + 復(fù)雜事件處理��； 參考：《中國(guó)農(nóng)業(yè)大學(xué)》2017年博士論文

【摘要】：信息物理系統(tǒng)(CPS)是通過(guò)計(jì)算(Computation)、通信(Communication)與控制(Control)技術(shù)的有機(jī)與深度融合,實(shí)現(xiàn)計(jì)算資源與物理資源的緊密結(jié)合與協(xié)調(diào)的下一代智能系統(tǒng)。CPS已被運(yùn)用于醫(yī)療、能源、交通等多個(gè)重要發(fā)展領(lǐng)域,具有廣闊的應(yīng)用前景。CPS技術(shù)和農(nóng)業(yè)的有機(jī)結(jié)合被稱(chēng)為農(nóng)業(yè)CPS,農(nóng)業(yè)CPS可能包含類(lèi)型繁多的、相互連接的設(shè)備,這些設(shè)備不斷產(chǎn)生大量的原始數(shù)據(jù),同時(shí)目前的CPS系統(tǒng)大都是分布式部署,不同層次數(shù)據(jù)源的數(shù)據(jù)具有海量、異構(gòu)和分散等特征,而傳統(tǒng)的數(shù)據(jù)處理技術(shù)難以對(duì)其進(jìn)行有效處理,可以引入基于事件的處理方法。農(nóng)業(yè)CPS采集的事件流中,單個(gè)事件表達(dá)含義有限,用戶(hù)更加關(guān)心的是反映農(nóng)業(yè)智能控制邏輯的符合特定模式的事件序列,如何從事件流中識(shí)別這些有意義的事件序列是農(nóng)業(yè)CPS數(shù)據(jù)處理中的一個(gè)難點(diǎn),復(fù)雜事件處理(CEP)技術(shù)作為CPS的核心技術(shù)可以有效解決這個(gè)問(wèn)題。而噪聲、傳感器誤差、時(shí)鐘不同步、網(wǎng)絡(luò)負(fù)載和延遲以及其它原因,都會(huì)造成農(nóng)業(yè)數(shù)據(jù)的不確定性,因此需要對(duì)不確定性的復(fù)雜事件處理技術(shù)開(kāi)展研究。事件的不確定性可以量化為概率,因此不確定事件流的處理轉(zhuǎn)化為對(duì)概率事件流的處理。概率復(fù)雜事件是由多個(gè)概率原子事件按照特定的模式復(fù)合后生成,在復(fù)合的過(guò)程中復(fù)雜事件的概率如何由原子事件概率計(jì)算生成以及如何按特定模式進(jìn)行事件的匹配檢測(cè)是需要研究的兩個(gè)主要問(wèn)題。本文在對(duì)目前CPS中CEP技術(shù)的研究現(xiàn)狀和面臨的挑戰(zhàn)進(jìn)行深入分析的基礎(chǔ)上,以農(nóng)業(yè)CPS為背景,用溫室大棚作為實(shí)例,針對(duì)這兩個(gè)問(wèn)題,從復(fù)雜事件的概率計(jì)算、基于樹(shù)的屬性不確定時(shí)的復(fù)雜事件檢測(cè)算法、以及基于概率時(shí)間Petri網(wǎng)的時(shí)間不確定的復(fù)雜事件檢測(cè)模型幾個(gè)方面開(kāi)展了深入的研究。本文的工作主要包括以下方面:(1)研究了農(nóng)業(yè)CPS中復(fù)雜事件的概率計(jì)算問(wèn)題,提出了一種基于近似世系的概率計(jì)算方法。不確定復(fù)雜事件處理是要檢測(cè)出滿(mǎn)足概率閾值的事件序列,因此如何計(jì)算不確定原子事件流組成的復(fù)雜事件的概率是進(jìn)行復(fù)雜事件處理時(shí)面對(duì)的主要挑戰(zhàn)之一,本文加入數(shù)據(jù)世系管理理論,為了應(yīng)對(duì)不斷產(chǎn)生的海量的概率原始事件,引入充分近似世系計(jì)算算法,提出離散多項(xiàng)式近似世系計(jì)算算法,對(duì)兩種算法進(jìn)行分析和比較,實(shí)驗(yàn)證明兩種算法均可進(jìn)行數(shù)據(jù)壓縮后再計(jì)算,從而減少計(jì)算量,提高計(jì)算效率,后者相較于前者壓縮比例更高,更有優(yōu)勢(shì)。(2)研究了基于樹(shù)的農(nóng)業(yè)CPS中不確定復(fù)雜事件檢測(cè)算法的問(wèn)題,提出了針對(duì)一般屬性不確定的PUCEP算法和時(shí)間屬性不確定的編碼ESI-tree解決方案。農(nóng)業(yè)CPS系統(tǒng)中因?yàn)閭鞲衅髡`差、采集精度、網(wǎng)絡(luò)通訊技術(shù)等等原因會(huì)造成事件屬性的不確定性,本文提出一種解決一般屬性不確定事件流的復(fù)雜事件查詢(xún)檢測(cè)方法--PUCEP算法,它在二叉樹(shù)基礎(chǔ)上融合了NFA方法,并將概率閾值引入其中進(jìn)行優(yōu)化,通過(guò)實(shí)驗(yàn)對(duì)比證明優(yōu)化后的算法在多項(xiàng)性能上都有所改進(jìn);時(shí)間是事件眾多屬性中比較特殊的屬性,針對(duì)其特殊性本文提出樹(shù)形解決方案ESI-tree,再根據(jù)樹(shù)的特點(diǎn)對(duì)樹(shù)進(jìn)行壓縮,然后采用編碼方法對(duì)其進(jìn)一步優(yōu)化,通過(guò)實(shí)驗(yàn)對(duì)比證明編碼后的匹配算法在執(zhí)行效率和內(nèi)存占用等方面都具有優(yōu)勢(shì)。(3)研究了基于Petri網(wǎng)的農(nóng)業(yè)CPS中不確定復(fù)雜事件檢測(cè)建模的問(wèn)題,提出了一種基于概率時(shí)間Petri網(wǎng)的復(fù)雜事件檢測(cè)模型的方法。農(nóng)業(yè)CPS中復(fù)雜事件由原子事件組合形成,原子事件的產(chǎn)生與CPS各個(gè)部分的采集、傳輸、轉(zhuǎn)換等過(guò)程緊密相關(guān),在這個(gè)過(guò)程中,由于系統(tǒng)誤差或隨機(jī)誤差導(dǎo)致原子事件的時(shí)間不確定,本文針對(duì)時(shí)間的不確定性,以溫室大棚為實(shí)例,利用概率時(shí)間Petri網(wǎng)對(duì)系統(tǒng)的原子事件建模,形成原子事件的模型,再將原子事件概率時(shí)間Petri網(wǎng)模塊組合形成復(fù)雜事件模型,利用這個(gè)模型可以準(zhǔn)確分析復(fù)雜事件語(yǔ)義,檢測(cè)匹配過(guò)程中對(duì)復(fù)雜事件的誤判、漏判,最后通過(guò)實(shí)例分析證明了該方法的正確性,并通過(guò)編程測(cè)試證明延時(shí)偏移概率越高,復(fù)雜事件檢測(cè)的誤判可能性越大,系統(tǒng)開(kāi)銷(xiāo)也越大。
[Abstract]:The information physical system (CPS) is an organic and deep integration of Computation, communication (Communication) and control (Control) technology, and the next generation intelligent system,.CPS, which realizes the close combination and coordination of computing resources and physical resources, has been applied to many important fields of development, such as medical treatment, energy source, traffic and so on, and has a broad application prospect,.C The organic combination of PS technology and agriculture is called agricultural CPS. Agricultural CPS may contain a wide range of interconnected devices. These devices produce a large number of original data. At the same time, most of the current CPS systems are distributed, and the data of different levels of data are characterized by sea, isomerism and dispersion and traditional data processing. It is difficult to deal with it effectively. The event based processing method can be introduced. In the event stream collected by agricultural CPS, the meaning of individual events is limited, and the user is more concerned about the event sequence that reflects the specific pattern of the agricultural intelligent control logic. How to identify these meaningful event sequences from the event flow is the agricultural CPS A difficult point in data processing, complex event processing (CEP) technology as the core technology of CPS can effectively solve this problem. Noise, sensor error, clock synchronization, network load and delay, and other reasons will cause uncertainty in agricultural data, so it is necessary to carry out complex event processing techniques for uncertainty. The uncertainty of the event can be quantified as a probability, so the processing of the uncertain event flow is converted to the processing of the probability event flow. The probability complex event is generated by multiple probability atomic events combined with a specific pattern, and how the probability of a complex event is generated by the probability calculation of the atomic event in a complex process and how The matching detection of events in a particular pattern is the two main problem that needs to be studied. On the basis of the current research status and challenges of CEP technology in CPS, this paper takes agricultural CPS as the background, uses greenhouse as an example, and aims at these two problems, from the probability calculation of complex events, based on the tree attributes. The complex event detection algorithm in uncertain time and the time uncertainty complex event detection model based on the probability time Petri net have been studied in several aspects. The work of this paper mainly includes the following aspects: (1) the probability calculation problem of complex events in agricultural CPS is studied, and a probability meter based on the approximate lineage is proposed. Calculation method. Undetermined complex event processing is to detect the event sequence that satisfies the probability threshold, so how to calculate the probability of the complex event which is not determined by the flow of the atomic event flow is one of the main challenges in the process of complex event processing. Starting events, introducing a full approximate lineage calculation algorithm, a discrete polynomial approximation algorithm is proposed, and the two algorithms are analyzed and compared. The experiment proves that the two algorithms can be compacted after data compression, thus reducing the amount of calculation and improving the computational efficiency. The latter has a higher compression ratio and a better advantage. (2) study Based on the problem of uncertain complex event detection algorithm in tree based agricultural CPS, a ESI-tree solution for PUCEP algorithm and uncertain time attribute is proposed. In agricultural CPS system, the uncertainty of event attributes will be caused by sensor error, acquisition precision, network communication technology and so on. A complex event query detection method --PUCEP algorithm is proposed to solve the general attribute uncertain event flow. It combines the NFA method on the basis of the two fork tree, and introduces the probability threshold into the optimization. The experimental comparison shows that the optimized algorithm is improved in many properties, and the time is more special among the many attributes of the event. According to its particularity, this paper puts forward the tree solution ESI-tree, then compresses the tree according to the characteristics of the tree, and then uses the coding method to further optimize it. Through the experiment comparison, it is proved that the matching algorithm after the coding has advantages in the execution efficiency and memory occupation. (3) the agricultural CPS based on Petri net is studied. The problem of complex event detection modeling is not determined. A method of complex event detection model based on probability time Petri net is proposed. The complex events in agricultural CPS are formed by the combination of atomic events. The generation of atomic events is closely related to the acquisition, transmission and conversion of each part of the CPS. In this process, the system error or the system error or the system error is closely related. The random error leads to the uncertainty of the time of the atomic event. In this paper, aiming at the uncertainty of the time, this paper takes the greenhouse as an example to model the atomic events of the system by using the probability time Petri net to form the model of the atomic event, and then combine the Petri net module of the atomic event probability time to form a complex event model, and use this model to be accurate. The complex event semantics is analyzed, and the misjudgments and misjudgments of complex events are detected in the matching process. Finally, the correctness of the method is proved by the case analysis. The higher the delay offset probability is, the higher the probability of the complex event detection is, the greater the system overhead is.

【學(xué)位授予單位】：中國(guó)農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：S126

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