發(fā)布時間：2018-02-21 12:23

  本文關(guān)鍵詞： 移動云計算 單幀數(shù)據(jù)流計 動態(tài)環(huán)境 計算切分 數(shù)據(jù)流應(yīng)用 性能解析　出處：《湖北工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：在中國這個高速發(fā)展的社會中,互聯(lián)網(wǎng)發(fā)展的也是相當(dāng)?shù)难杆?云服務(wù)就是互聯(lián)網(wǎng)發(fā)展的產(chǎn)物,其中移動云計算是云服務(wù)系統(tǒng)中的移動應(yīng)用產(chǎn)生的一種新的云計算方式。電池容量、網(wǎng)絡(luò)通信能力和計算存儲資源等是移動終端設(shè)備本身具有局限性,移動云計算有其局限性,但也有其有點(diǎn):在無線網(wǎng)絡(luò)下,可以使移動終端設(shè)備拓展移動應(yīng)用,而且還可以使用云計算的資源,按照需求獲取存儲資源及所需的計算。移動云計算為了能夠提高移動應(yīng)用的服務(wù)質(zhì)量(Quality of Service,Qos)會把全部或部分需要計算的工作移動到云端。在當(dāng)前的移動云計算方式還較少,要探究適合移動客戶端隨處境變化和能用資源網(wǎng)絡(luò)寬帶的狀況下去提升功能。對于上面所講的問題,在本篇文章中會講述關(guān)于移動云服務(wù)應(yīng)用的計算切分方法在動態(tài)環(huán)境下的移動云計算的基礎(chǔ)上的研究,在動態(tài)環(huán)境的影響下去探究計算工作單元在本地計算或者移動到云端計算情況下的動態(tài)決策移動應(yīng)用中的計算。主要展開下面所講任務(wù):在與移動云計算系統(tǒng)框架相結(jié)合的情況下,最先建立一種有狀態(tài)的移動數(shù)據(jù)流應(yīng)用的模型。對于多幀數(shù)據(jù)流計算切分決策、任務(wù)調(diào)度和執(zhí)行效率、動態(tài)優(yōu)化及單幀數(shù)據(jù)流計算切分方案等問題的定義解析是探究移動云計算的問題和方向定義所包括的幾個方面的內(nèi)容。單幀數(shù)據(jù)流計算切分方法是在以上基礎(chǔ)探究的并在知道計算切分方案的情況下提出工作排序及工作任務(wù)數(shù)據(jù)流模型,而且解析了它的工作調(diào)度辦法,計算數(shù)據(jù)幀經(jīng)過計算切分后的執(zhí)行時間是依據(jù)調(diào)度辦法計算的,并且經(jīng)過遺傳的計算方法來執(zhí)行最短的時間下作為適應(yīng)度函數(shù),進(jìn)而計算出最佳的計算切分決策辦法。本篇文章進(jìn)行多幀數(shù)據(jù)的操縱是在單幀數(shù)據(jù)流計算切分辦法的基礎(chǔ)上進(jìn)行的,去探究多幀數(shù)據(jù)優(yōu)化調(diào)整及計算切分決策,考慮到網(wǎng)絡(luò)帶寬在未來短時間內(nèi)的變化情況,要實(shí)現(xiàn)多幀數(shù)據(jù)計算切分方案優(yōu)化決策是經(jīng)過計算節(jié)點(diǎn)的計算切分方案的優(yōu)化調(diào)整辦法來實(shí)現(xiàn)的。對于上面探究的工作內(nèi)容,本篇文章考證闡述了有狀態(tài)的數(shù)據(jù)流應(yīng)用中單幀數(shù)據(jù)計算切分的有效性并分析了多幀數(shù)據(jù)在優(yōu)化調(diào)整后的方法的性能。在本篇論文的最后,考證論文辦法的有效性是經(jīng)過一個移動云計算平臺原型系統(tǒng)“移動云服務(wù)人臉識別”來驗(yàn)證的。在伴隨著移動設(shè)備終端性能的提高級4G時代的的到來,本篇文章探究的移動云計算的計算切分方法能夠更廣泛地應(yīng)用到像語音識別處理系統(tǒng)及條碼二維碼識別等圖像識別處理系統(tǒng)等有狀態(tài)的數(shù)據(jù)流處理程序中。
[Abstract]:In this rapidly developing society in China, the Internet is also developing quite rapidly. Cloud services are the product of the development of the Internet. Mobile cloud computing is a new way of cloud computing generated by mobile applications in cloud service systems. Battery capacity, network communication capacity and computing storage resources are the limitations of mobile terminal devices, and mobile cloud computing has its limitations. But it's also a little bit: in wireless networks, mobile devices can expand their mobile applications, and they can use cloud computing resources. Mobile cloud computing moves all or part of the work needed to compute to the cloud in order to improve the quality of service of mobile applications. To explore the mobile client to adapt to the changing situation and the ability to use resource network broadband to upgrade the function. In this article, we will talk about the research of computing segmentation of mobile cloud service application based on mobile cloud computing in dynamic environment. Under the influence of the dynamic environment to explore the computing work unit in local computing or moving to cloud computing dynamic decision-making mobile application computing. The main tasks described below: with the mobile cloud computing system box. When the frame is combined, A model of stateful mobile data stream application is first established. For multi-frame data stream computing segmentation decision, task scheduling and execution efficiency, The definition analysis of dynamic optimization and single-frame data stream computing segmentation scheme is to explore the problems of mobile cloud computing and several aspects of the definition of direction. The single-frame data stream computing segmentation method is based on the above. The work order and work task data flow model are proposed under the condition of knowing the calculation of the segmentation scheme. Moreover, its scheduling method is analyzed. The execution time of the calculated data frame is calculated according to the scheduling method, and the genetic calculation method is used to perform the fitness function in the shortest time. In this paper, the manipulation of multi-frame data is carried out on the basis of single-frame data stream calculation and segmentation, to explore the optimization adjustment of multi-frame data and the calculation of segmentation decision. Considering the change of network bandwidth in a short time in the future, the optimization decision of multi-frame data computing segmentation scheme is realized through the optimization adjustment method of computing node's computing segmentation scheme. This paper discusses the validity of single-frame data segmentation in the application of stateful data flow and analyzes the performance of the method after optimization and adjustment of multi-frame data. The validity of this method is verified by a prototype system of mobile cloud computing platform "mobile cloud service face recognition". The computational segmentation method of mobile cloud computing explored in this paper can be more widely used in stateful data stream processing programs such as speech recognition processing systems and image recognition processing systems such as barcode two-dimensional code recognition.
【學(xué)位授予單位】：湖北工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP393.09

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1 羅林;基于動態(tài)環(huán)境的移動云計算切分方法的研究[D];湖北工業(yè)大學(xué);2017年

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本文編號：1521963