本文選題：云服務(wù) + 中間件��； 參考：《福州大學(xué)》2014年碩士論文

【摘要】：在Web應(yīng)用日益普及的今天,Web服務(wù)器承擔(dān)的任務(wù)越來越繁重,特別是進(jìn)行大數(shù)據(jù)量的計算時,服務(wù)器的硬件資源成了計算效率的瓶頸。而單純地提高服務(wù)器本身的性能效果并不明顯,而且存在資源浪費(fèi)。如果能將計算任務(wù)分解成若干個子任務(wù),分配給閑置的計算服務(wù)器,那么由于并行計算的優(yōu)勢,效率將大大提高。云計算技術(shù)可以解決大任務(wù)計算的效率問題。云計算是一種商業(yè)式的計算模型,它可以將計算任務(wù)分解成小任務(wù),分布到大量由計算機(jī)構(gòu)成的資源池上,使得各種應(yīng)用能夠根據(jù)需要獲取計算能力、存儲空間和信息服務(wù)。由于云計算任務(wù)的計算過程是在各臺計算機(jī)的本地進(jìn)行的,在網(wǎng)絡(luò)上傳輸?shù)膬H有任務(wù)描述和計算結(jié)果,所以網(wǎng)絡(luò)傳輸?shù)拇鷥r小,計算效率取決于計算節(jié)點(diǎn)的平均性能和負(fù)載均衡算法。本文提出了一種基于多Agent的云服務(wù)中間件的框架體系,分為三個層次,用戶接口層、SOA層和資源管理層。用戶接口層負(fù)責(zé)任務(wù)接口的描述,Web請求端通過接口調(diào)用云服務(wù)模式下的任務(wù)計算。SOA層是面向服務(wù)的,它管理了云服務(wù)中間件向用戶接口提供的服務(wù),維護(hù)服務(wù)列表,可以根據(jù)用戶的請求查找相應(yīng)的服務(wù)。資源管理層是整個云服務(wù)中間件的核心部分,它包含了一個負(fù)載均衡器和監(jiān)控器,提供容錯服務(wù)和日志服務(wù),實(shí)現(xiàn)了任務(wù)分解、分發(fā)和結(jié)果匯總的邏輯,維護(hù)計算節(jié)點(diǎn)列表。一個完整的Agent平臺由多個Agent容器組成,每個容器下有若干個Agent和一個消息調(diào)度模塊,Agent之間通過發(fā)送和接收消息進(jìn)行通信。在臺風(fēng)預(yù)報云服務(wù)中間件CSMTF (Cloud Service Middleware Of Typhoon Forecast)中,有一個負(fù)責(zé)任務(wù)分解、分發(fā)和結(jié)果匯總的Agent,稱為主控節(jié)點(diǎn)。主控節(jié)點(diǎn)接收從請求端發(fā)來的計算任務(wù),內(nèi)置的負(fù)載均衡器實(shí)時獲取各臺閑置計算機(jī)的性能信息,將任務(wù)分配給輕載節(jié)點(diǎn)。主控節(jié)點(diǎn)內(nèi)置的日志監(jiān)控器負(fù)責(zé)各Agent日志的收集和記錄,以便管理人員查看了解Agent的工作情況。同時,主控節(jié)點(diǎn)還內(nèi)置了容錯監(jiān)控器,檢測Agent運(yùn)行狀況,恢復(fù)出錯的Agent。云服務(wù)中間件中有若干個負(fù)責(zé)子任務(wù)計算的Agent,稱為計算節(jié)點(diǎn)。計算節(jié)點(diǎn)實(shí)時發(fā)送本機(jī)的負(fù)載信息給主控節(jié)點(diǎn),接收來自主控節(jié)點(diǎn)分發(fā)的子任務(wù),在本地計算,并向主控節(jié)點(diǎn)返回計算的結(jié)果。計算節(jié)點(diǎn)也帶有一個日志監(jiān)控器,用于記錄本地Agent的信息,內(nèi)置的容錯監(jiān)控器用于本地恢復(fù)。臺風(fēng)預(yù)報系統(tǒng)是一個典型的Web應(yīng)用,它是一個會商式的群決策支持系統(tǒng)(GDSS)。其中的專家預(yù)報路徑就涉及了大數(shù)據(jù)量計算,Web服務(wù)器需要對預(yù)測的路徑與數(shù)據(jù)庫中的所有歷史臺風(fēng)路徑進(jìn)行相似度計算,并且要求實(shí)時顯示最相似路徑。而數(shù)據(jù)庫中的路徑點(diǎn)數(shù)有成千上萬,在Web服務(wù)器資源有限的情況下,很難進(jìn)行有效的計算。本文將云服務(wù)中間件的技術(shù)應(yīng)用到臺風(fēng)預(yù)報系統(tǒng)上,以提高相似路徑計算的效率。最后,本文搭建實(shí)驗環(huán)境對CSMTF系統(tǒng)做了性能測試,與Web服務(wù)器單機(jī)計算相比,計算速度有顯著的提高,大大縮短了服務(wù)器的響應(yīng)時間。
[Abstract]:In the Web application is becoming more and more popular, Web server takes more and more arduous task, especially the calculation of large amount of data, the server hardware resources has become a bottleneck of computational efficiency. And simply improve the performance of the server itself is not obvious, and there is a waste of resources. If it can be decomposed into several computational tasks sub tasks, assigned to the computing server idle, then because of the advantage of parallel computing efficiency will be greatly improved. Cloud computing technology can solve the problem of efficiency calculation tasks. Cloud computing is a business model type, it can compute tasks into small tasks, distributed to a large number of resources by computer then, according to the needs of various applications that access computing power, storage space and information services. The calculation process of cloud computing task is performed in the local computer, The only task in the transmission network description and calculation results, so the network transmission cost is small, the computational efficiency depends on the average performance of computing nodes and load balancing algorithm. This paper proposes a framework of cloud service middleware based on multi Agent, divided into three levels, the user interface layer, SOA layer and resource management the user interface layer. The interface layer is responsible for the task description, the Web request by calling the interface end cloud service model under the task of calculating the.SOA layer is service oriented, it manages the cloud service middleware provides to user interface services, maintenance services list, according to the user's request to find the corresponding service resource management layer is the core part. The cloud service middleware, which includes a load balancer and monitor, provide fault tolerance service and log service, realize the task decomposition, distribution and results summary logic, maintenance plan A list of nodes. A complete Agent platform is composed of a plurality of Agent container, and a plurality of Agent and a message scheduling module of each container, Agent communicate by sending and receiving messages. In the forecast of typhoon cloud service middleware CSMTF (Cloud Service Middleware Of Typhoon Forecast), a responsible for task decomposition a summary of the results of the distribution, and Agent, known as the master node. The master node receives a request sent from the terminal computing tasks, load equalizer performance information real-time access to each idle computer built-in, assign tasks to light load nodes. The master node built-in monitor log log Agent is responsible for the collection and recording. In order to understand the management view Agent work. At the same time, the master node has built-in fault-tolerant monitor, testing the running condition of Agent, middle Agent. cloud service part error recovery in if A responsible for sub task computation Agent, called compute node. Calculation of real-time transmitting node of the machine load information to the master node, the master node receives from the distribution of sub tasks in the local computation, and return to the main control node calculation results. The compute nodes with a log is used to record the monitor. The local Agent information monitor built for local fault tolerant recovery. Typhoon forecast system is a typical application of Web, it is a type of consultation group decision support system (GDSS). The expert forecast path involves the calculation of a large amount of data, the Web server needs all the historical path and database on the prediction of typhoon in the similarity calculation, and real-time display the most similar path. The path points in the database there are tens of thousands of, in the Web server under the condition of limited resources, it is difficult to effectively calculate the. The cloud service middleware technology is applied to the typhoon forecasting system, to improve the efficiency of similar path calculation. Finally, this paper set up the experimental environment of the CSMTF system performance test, compared with the Web single server computing, the computing speed is significantly improved, greatly shorten the response time of the server.

【學(xué)位授予單位】：福州大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.09

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