本文選題：并行計(jì)算 + 云計(jì)算��； 參考：《北京郵電大學(xué)》2012年博士論文

【摘要】：信息和數(shù)據(jù)對于任何一個(gè)行業(yè)都有著巨大的價(jià)值,然而在面對海量數(shù)據(jù)時(shí),及時(shí)的分析和處理卻是難題。在過去的十年里,隨著各行業(yè)信息化程度的提高,數(shù)據(jù)量的快速增長已在很多行業(yè)中出現(xiàn)。為了滿足及時(shí)分析處理大規(guī)模數(shù)據(jù)的需求,越來越多的領(lǐng)域開始嘗試使用并行計(jì)算技術(shù)。在過去的5到8年的時(shí)間里,并行計(jì)算編程模型的研究和應(yīng)用已經(jīng)從專業(yè)領(lǐng)域延伸到IT、電子商務(wù)等信息化程度較高的行業(yè)。 并行計(jì)算并非一項(xiàng)新技術(shù),從概念的提出到今天已經(jīng)歷了數(shù)十年的時(shí)間,在很多專業(yè)領(lǐng)域已有了相當(dāng)長的研究歷史,并取得了很多的研究成果。但是隨著應(yīng)用領(lǐng)域的改變,技術(shù)的使用場景和需求也發(fā)生了巨大的變化,目前對基于集群資源的通用并行計(jì)算編程模型及系統(tǒng)的研究還很缺乏。隨著越來越多行業(yè)的加入,人們對普遍適用的并行計(jì)算技術(shù)的需求會(huì)不斷增長,這為通用并行計(jì)算編程模型及系統(tǒng)的研究帶來機(jī)遇,同時(shí)也帶來了挑戰(zhàn)。近年來,對通用并行計(jì)算的研究已初具規(guī)模,提出了很多通用編程模型和系統(tǒng),例如MapReduce、Dryad等,但是還有很多問題并沒有得到解決。 (1)模型及系統(tǒng)的通用性問題。大部分模型和系統(tǒng)是針對單一問題的需求而提出的,所能夠涵蓋的問題類型有限,在使用時(shí)通常需要對待處理的問題進(jìn)行轉(zhuǎn)換。并且任務(wù)的處理流程已固化在系統(tǒng)設(shè)計(jì)中,使基于模型的程序設(shè)計(jì)缺乏靈活性。 (2)系統(tǒng)的擴(kuò)展性問題。通用并行系統(tǒng)通常架構(gòu)在大規(guī)模集群之上,但是系統(tǒng)的設(shè)計(jì)卻對資源擴(kuò)展問題缺乏足夠的考慮,隨著集群規(guī)模的不斷擴(kuò)大和任務(wù)量的持續(xù)增長,系統(tǒng)的控制核心已出現(xiàn)負(fù)載困難的現(xiàn)象。 (3)通用架構(gòu)的層次定位問題。雖然以架構(gòu)去管理資源、用模型去承載任務(wù)的設(shè)計(jì)可以增加集群的通用性,但是對于具體的計(jì)算模型而言卻沒有任何的益處。如果不能將任務(wù)的管理流程抽象,架構(gòu)的通用只能局限在資源配置層次。 (4)模型應(yīng)用領(lǐng)域的探尋。通用并行計(jì)算在海量數(shù)據(jù)處理方面展現(xiàn)出的優(yōu)越性能,使很多問題的解決思路趨向于并行處理,然而并不是所有問題都適合并行處理,模型的應(yīng)用范圍值得思考。 圍繞上述問題,本文開展了以下工作： (1)對通用并行計(jì)算編程模型及系統(tǒng)展開了研究,對現(xiàn)有模型的優(yōu)勢和不足進(jìn)行了分析總結(jié),提出了功能并行、時(shí)間并行與數(shù)據(jù)并行分層疊加的并行模式設(shè)計(jì),擴(kuò)展了模型的應(yīng)用范圍。同時(shí)在系統(tǒng)設(shè)計(jì)方面,將應(yīng)用的執(zhí)行流程控制作為特殊任務(wù)進(jìn)行設(shè)計(jì),使應(yīng)用的執(zhí)行流程更多樣化,應(yīng)用程序的設(shè)計(jì)更靈活。這兩方面的設(shè)計(jì)創(chuàng)新能夠增強(qiáng)并行計(jì)算編程模型及系統(tǒng)的通用性。 (2)對通用并行系統(tǒng)的擴(kuò)展性問題進(jìn)行了研究,通過分析和總結(jié)了現(xiàn)有系統(tǒng)出現(xiàn)擴(kuò)展性問題的主要原因。提出了分布式多控制點(diǎn)系統(tǒng)架構(gòu),用多控制點(diǎn)分布式管理取代單控制點(diǎn)集中式管理,優(yōu)化了資源信令發(fā)送和處理機(jī)制、將并發(fā)應(yīng)用的管理和調(diào)度拆分到不同控制點(diǎn)上,以此解決由控制點(diǎn)資源有限和任務(wù)負(fù)載不斷增長引起的擴(kuò)展性問題,從而提升系統(tǒng)的擴(kuò)展能力。 (3)對通用系統(tǒng)架構(gòu)進(jìn)行了研究,提出了可持續(xù)擴(kuò)展的集群架構(gòu)。在解決系統(tǒng)擴(kuò)展性問題的同時(shí),使集群架構(gòu)設(shè)計(jì)更適合承載通用并行計(jì)算模型。新架構(gòu)實(shí)現(xiàn)了資源管理與任務(wù)調(diào)度相分離,同時(shí)對管理模塊進(jìn)行了層次化設(shè)計(jì),使控制層也具有擴(kuò)展能力。同時(shí)新架構(gòu)還對任務(wù)管理進(jìn)行了抽象,將通用的任務(wù)管理功能集成在架構(gòu)中,而將流程定義及控制預(yù)留給任務(wù)管理結(jié)點(diǎn)實(shí)現(xiàn)。 (4)研究了通用并行計(jì)算在解決網(wǎng)絡(luò)狀態(tài)分析問題方而的應(yīng)用�；谕ㄓ貌⑿杏�(jì)算系統(tǒng)的特點(diǎn),對其所適用的問題類型進(jìn)行了分析。并以流量擁塞調(diào)整問題為主要研究對象,進(jìn)行了并行算法設(shè)計(jì),使用并行系統(tǒng)對處理過程進(jìn)行加速,從而縮短問題處理時(shí)間。該研究嘗試尋找一條并行處理網(wǎng)絡(luò)狀態(tài)分析問題的途徑。
[Abstract]:Information and data are of great value for any industry. However, in the face of massive data, timely analysis and processing is a difficult problem. In the past ten years, the rapid growth of data has emerged in many industries as the level of information technology increases. In order to meet the need for timely analysis and processing of large data, More and more fields have begun to try to use parallel computing technology. In the past 5 to 8 years, the research and application of parallel computing programming models have been extended from professional to IT, electronic commerce and other industries with high degree of information.
Parallel computing is not a new technology. It has been a few decades since the proposal of the concept. It has a long history of research in many professional fields and has achieved many research results. However, with the change of the application field, the use scene and demand of technology have also changed greatly. The general parallel computing programming model and the research of the system are still very short. As more and more industries are joined, the demand for universal parallel computing technology is increasing. This brings opportunities to the research of general parallel computing programming model and system, and also brings challenges. In recent years, the research on general parallel computing has been studied. Research has begun to take shape, and many common programming models and systems have been put forward, such as MapReduce, Dryad, etc., but there are still many problems that have not been solved.
(1) the generality of the model and system. Most models and systems are proposed for the needs of a single problem. The types of problems that can be covered are limited and often need to be converted to the processing problems in use. And the processing flow of the task has been solidified in the system design to make the model based programming lack flexibility.
(2) the extensibility of the system. The general parallel system is usually built on a large scale cluster, but the design of the system lacks sufficient consideration for the problem of resource expansion. With the continuous expansion of the scale of the cluster and the continuous growth of the task volume, the core of the control system has appeared to have a negative load.
(3) the hierarchical location of general architecture. Although the architecture to manage resources, the design of the model to carry the task can increase the generality of the cluster, but there is no benefit for the specific calculation model. If the task management process can not be abstracted, the general framework of the architecture can only be limited to the level of resource allocation.
(4) the exploration of the application field of the model. The general parallel computing shows the superior performance in the mass data processing, so that many problems can be solved in parallel processing, but not all the problems are suitable for parallel processing. The application scope of the model is worth thinking.
Around the above problems, the following work has been carried out in this paper.
(1) the general parallel computing programming model and system are studied, the advantages and disadvantages of the existing model are analyzed and summarized, the parallel mode design of function parallel, time parallel and data parallel layer superposition is proposed, and the application scope of the model is extended. Meanwhile, the application process control is used as a special design in the system design. The special task is designed to make the application process more diverse and the application design more flexible. These two aspects of design innovation can enhance the parallel computing programming model and the universality of the system.
(2) the extensibility of the universal parallel system is studied, and the main reasons for the extensibility of the existing system are analyzed and summarized. A distributed multi control point system architecture is proposed. The distributed management of multi control points is used to replace the centralized management of single control point, and the mechanism of sending and processing resource signaling is optimized, and the concurrent application will be applied. Management and scheduling are broken down to different control points to solve the extensibility problems caused by limited resources of control points and increasing task load, so as to improve the scalability of the system.
(3) the architecture of general system is studied and a sustainable and extended cluster architecture is put forward. In solving the problem of system extensibility, the design of cluster architecture is more suitable for carrying general parallel computing model. The new architecture realizes the separation of resource management and task scheduling, and the hierarchical design of the management module, so that the control layer is also made The new architecture also abstracts the task management and integrates the general task management functions into the architecture, while the process definition and control are reserved to the task management node.
(4) the application of general parallel computing in solving the problem of network state analysis is studied. Based on the characteristics of the general parallel computing system, the types of the problem are analyzed. The problem of traffic congestion adjustment is taken as the main research object, the parallel algorithm is designed, and the processing process is accelerated by the parallel system. This study tries to find a parallel approach to network state analysis.

【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2012
【分類號】：TP338.6

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