發(fā)布時間：2018-07-03 20:00

  本文選題：資源分配 + 價格比例��； 參考：《北京郵電大學(xué)》2015年博士論文

【摘要】：互聯(lián)網(wǎng)、尤其是移動互聯(lián)網(wǎng)的普及,使得用戶規(guī)模和應(yīng)用種類急劇增加。在這種用戶規(guī)模巨大以及衍生的高度動態(tài)情況下,傳統(tǒng)服務(wù)平臺無法滿足用戶的服務(wù)質(zhì)量需求。這促使了云計算的出現(xiàn)和發(fā)展。云計算的高可靠性、高可用性以及彈性特點不僅保證了大規(guī)模用戶的高質(zhì)量服務(wù),還降低了提供商的成本。另外,通過采用按需付費的方式,云計算降低了用戶的成本。鑒于云計算的優(yōu)勢,科研機構(gòu)和企業(yè)采用云計算技術(shù)改造現(xiàn)有的平臺或應(yīng)用。然而,云平臺的資源分配問題是當前亟待解決的一個難題。不合理的資源分配方式不僅使得資源利用率低下,有時甚至難以滿足應(yīng)用的動態(tài)資源需求。已有的資源分配算法從系統(tǒng)或整體的角度最優(yōu)化分配云計算資源。然而,云計算是一種基于效用的商業(yè)計算模式,提供商和用戶之間及內(nèi)部存在著復(fù)雜的競爭,提供商和用戶根據(jù)競爭情況擁有各自的供給和需求策略。因此,基于博弈論的資源分配算法能夠深入研究提供商和用戶的策略,更加適合分析云計算資源的分配問題。雖然已有研究人員基于博弈論研究云計算資源分配問題,仍然存在著諸多挑戰(zhàn)。需要一個不受用戶數(shù)量限制的快速高效、可擴展的云計算資源分配算法；大規(guī)模的用戶具有迥異的特征,使用多約束條件等方式無法準確描述用戶的不同需求；大規(guī)模用戶的隨機加入和退出導(dǎo)致云環(huán)境高度動態(tài)變化,通過反復(fù)協(xié)商機制研究提供商和用戶的均衡狀態(tài)不可行；針對相互關(guān)聯(lián)的復(fù)雜云服務(wù),需要一個有效的服務(wù)部署策略。針對上述的局限性,本文基于博弈論研究了云計算資源的分配和服務(wù)的部署問題。主要包括：1.基于荷蘭式拍賣的虛擬機分配算法。為了快速高效的分配虛擬機資源,提出了多實例荷蘭式拍賣算法。該算法的拍賣時間與用戶數(shù)量和虛擬機類型數(shù)目無關(guān),更加適用于大規(guī)模的云計算虛擬機分配。另外,該算法中各個類型的虛擬機降價策略互不相干,使得該機制有著很好的可擴展性,易于分布式實現(xiàn)。提供商能夠根據(jù)保留價格等因素決定拍賣的終止時間,實現(xiàn)社會總收益或自己收入的最大化。2.基于價格比例的計算型資源分配算法。為了實現(xiàn)CPU、內(nèi)存等可分割資源的有效分配,我們采用基于SLA的效用函數(shù)描述不同經(jīng)濟能力用戶申請的不同等級服務(wù),并利用價格比例方法分配資源。這樣,不僅實現(xiàn)了價值高的服務(wù)獲得更多資源的價高者得方式的有效性,還保證了每個競價者為單位資源支付相同的價格,保障了公平性。進一步的,考慮不同的使用場景,基于此算法提供了2種云資源分配機制。3.基于貪婪拍賣的帶寬資源分配算法。分析傳統(tǒng)的中心式和分布式網(wǎng)絡(luò)資源分配機制的不足,基于貪婪拍賣提出了適用于任何需求類型(彈性、實時、階梯式等)場景的多競價貪婪拍賣機制,彌補了中心式和分布式機制的缺陷,適用于云計算網(wǎng)絡(luò)資源分配。進一步的,考慮實際情況中用戶需求類型基本為彈性需求的特點,提出了具有更少競價通信消耗的多維度競價貪婪拍賣機制。4.基于擁塞博弈的服務(wù)部署算法�？紤]基于云的服務(wù)復(fù)雜且相互關(guān)聯(lián)的特性,將云計算的服務(wù)部署問題轉(zhuǎn)化為擁塞博弈問題。綜合考慮服務(wù)的效率和成本,基于擁塞博弈模型實現(xiàn)云計算服務(wù)的優(yōu)化部署。為了驗證上述資源分配以及服務(wù)部署算法的有效性,本論文從分別從理論和實驗的角度進行了分析。結(jié)果表明本文提出的資源分配以及服務(wù)部署算法具有很好的性能,能夠快速高效的分配云計算資源,適用于大規(guī)模、高度動態(tài)、復(fù)雜的云環(huán)境中。
[Abstract]:The popularity of the Internet, especially the mobile Internet, has led to a sharp increase in the size and application of the user. In the large and highly dynamic conditions of the user, the traditional service platform is unable to meet the user's quality of service. This has prompted the emergence and development of cloud computing. The high reliability, high availability and bomb of the cloud computing. The characteristics not only guarantee high quality services for large users, but also reduce the cost of providers. In addition, cloud computing reduces the cost of users by paying on demand. In view of the advantages of cloud computing, research institutions and enterprises transform the existing platforms or applications by using cloud computing technology. However, the problem of resource allocation in cloud platforms. It is a difficult problem to be solved at present. The irrational allocation of resources not only makes the utilization of resources low, but sometimes even hard to meet the dynamic resource requirements of the application. The existing resource allocation algorithm optimally distributies cloud computing resources from the perspective of the system or the whole. However, the cloud computing is a utility based business computing model. There is a complex competition between providers and users. Providers and users have their own supply and demand strategies based on competition. Therefore, the game theory based resource allocation algorithm is able to study the strategy of providers and users, and is more suitable for the analysis of the distribution of cloud computing resources. There are still many challenges in the study of the distribution of cloud computing resources by game theory. It needs a fast, efficient and scalable algorithm of cloud computing resource allocation without the limit of the number of users; large users have different characteristics and can not accurately describe the different needs of the users by using multi constraint conditions. It is infeasible to study the equilibrium state of the providers and users through repeated negotiation mechanism, and it is not feasible to study the equilibrium state of the providers and users through repeated negotiation mechanism. For the interrelated complex cloud services, an effective service deployment strategy is needed. Based on the above limitations, this paper studies the Division of cloud computing resources allocation and service based on game theory. The main issues include: 1. virtual machine allocation algorithm based on Holland auction. In order to quickly and efficiently allocate virtual machine resources, a multi instance Holland auction algorithm is proposed. The auction time is independent of the number of users and the number of virtual machines, and it is more suitable for the large-scale cloud computing virtual machine allocation. In addition, the algorithm is used in the algorithm. Each type of virtual machine reduction strategy is not coherent, making the mechanism well extensible and easy to distribute. The provider can determine the termination time of the auction according to the factors such as the reservation price and realize the total social income or the maximum.2. based on the price ratio based computing resource allocation algorithm. In order to realize the CPU We use the utility function based on SLA to describe different levels of service with different economic capabilities and use the price ratio method to allocate resources. Unit resources pay the same price, ensuring fairness. Further, considering different usage scenarios, based on this algorithm, 2 kinds of cloud resource allocation mechanism.3. based on the greedy auction based bandwidth allocation algorithm are provided. The shortcomings of the traditional central and distributed network resource allocation system are analyzed, based on the greedy auction, the application of the algorithm is proposed. The multi bidding greedy auction mechanism of any demand type (elastic, real-time, staircase, etc.) makes up for the defects of the central and distributed mechanism, and is suitable for the allocation of cloud computing network resources. Further, considering the characteristics of the user demand type in the actual situation is basically elastic demand, the multidimensional consumption of less competitive communication is proposed. .4. based on congestion game based service deployment algorithm. Considering the complex and interrelated characteristics of cloud based services, the service deployment problem of cloud computing is transformed into a congestion game problem. The efficiency and cost of services are considered, and the optimal deployment of cloud computing service based on congestion game model is presented. The effectiveness of resource allocation and service deployment algorithm is discussed. This paper is analyzed from the theoretical and experimental points of view. The results show that the resource allocation and service deployment algorithm proposed in this paper have good performance, and can quickly and efficiently allocate cloud computing resources. It is suitable for large-scale, highly dynamic and complex cloud environments.
【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】：2015
【分類號】：TP393.09

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