本文選題：云計算　切入點：任務調度算法　出處：《山東師范大學》2014年碩士論文

【摘要】：云計算是一種新的計算模式，它通過服務的形式為用戶提供各種資源。云計算的正常運行離不開虛擬化技術。云計算中，利用虛擬化技術，將物理服務器的資源映射到虛擬機層，在一個服務器上部署多個虛擬機，利用虛擬機來執(zhí)行用戶任務，這樣不但提高了服務器的資源利用率，同時保證了不同用戶的應用程序的獨立性。 近年來，越來越多的企業(yè)架構了自己的云服務器，云計算系統需要有滿足自身用戶需要的資源分配和任務調度策略，目前還沒有相關的任務調度標準。因此，對云計算環(huán)境下的任務調度算法研究具有重要的理論和現實意義。本文分析了云計算環(huán)境下的任務調度法算的研究現狀，總結了云計算這一新興商業(yè)模式的獨有的特點，對現有調度算法存在的問題進行了深入分析，然后分別針對獨立型和依賴型兩類任務，提出了兩種任務調度算法。此外，考慮了用戶對云計算中心虛擬機資源的不同偏好性，針對多用戶類，設計了多準則的任務調度算法�？傮w來說，本文主要完成了以下工作： ⑴針對云計算環(huán)境下的獨立型任務，現有的調度方法一般包括遺傳算法、蟻群算法、模擬退火算法等智能算法，，這些算法收斂的速度較快，但是容易陷入局部最優(yōu)，并且算法過度依靠適應度函數的設計，算法復雜度較高。考慮到這類隨機算法的劣勢，我們從博弈論的角度分析云計算環(huán)境下的任務調度問題，設計了一個任務調度博弈模型，將所有用戶任務作為博弈的參與者，所選擇的虛擬機作為博弈策略，以任務處理時延作為博弈參與者的效用函數。找到了博弈的勢函數，證明了博弈是一個勢博弈，并且博弈存在Nash均衡，利用數學分析，證明了該博弈的穩(wěn)定點就是勢函數的最小值點。此外，提出了一種基于勢博弈的任務調度算法，算法能夠求解博弈到達穩(wěn)定點時各個虛擬機上的任務量分布狀態(tài)。仿真實驗表明，該調度算法能降低任務的整體處理時延，并且能使系統的負載均衡程度自適應于用戶任務量的變化，當任務量較少時，開啟較少的虛擬機資源，減少系統的開銷，當任務量較多時，開啟較多的虛擬機資源，保證任務的QoS。此外，考慮了虛擬機的閾值限制，對所提算法進行了擴展，將虛擬機閾值限制這一參數加入到算法中，使得算法更具有一般性。 ⑵針對依賴型任務，分析了任務的DAG圖，主要研究了Fork-Join型任務圖，針對該類任務，基于網絡博弈論中的Wardrop均衡原理，給出了以全體用戶任務處理時延作為代價函數的博弈分析，考慮網絡中全體用戶任務，將求解全體用戶的系統最優(yōu)問題轉化為求解單個用戶的用戶最優(yōu)問題，設計了一個針對該任務的調度算法，該算法能夠求解Wardrop均衡理論中的系統最優(yōu)狀態(tài)。最后，對此算法進行了仿真實驗，實驗表明，相比于單個用戶最優(yōu)的求解算法，該算法能夠較快的完成用戶任務，并且使整個云計算用戶任務達到系統最優(yōu)。 ⑶針對云計算用戶任務對虛擬機資源具有不同的偏向性，對多用戶類多準則的任務調度進行了研究。在云計算環(huán)境下，有些用戶偏向于選擇處理時延小的虛擬機資源，有些用戶偏向于選擇費用低的虛擬機資源，有些用戶偏向于選擇更加安全的虛擬機資源。根據用戶的偏好性不同，將網絡中的用戶分為多類用戶，只考慮費用和時間這兩種指標，為這多類用戶同時競爭虛擬機資源時設計了博弈模型，找到了博弈的勢函數，證明了該博弈為一個勢博弈，同時證明了博弈存在Nash均衡，并且Nash均衡與勢函數的最大值等價。最后，提出了一種基于多用戶類多準則的任務調度算法，求解博弈達到均衡時的各個虛擬機上任務量的狀態(tài)分布。算法的仿真實驗表明，所提算法具有收斂性，算法的求解結果與所有自私用戶經過自由博弈后所得到的穩(wěn)定狀態(tài)是相同的，進一步說明了該算法的有效性及可行性。
[Abstract]:Cloud computing is a new computing mode, it is in the form of services to provide users with a variety of resources. The normal operation of cloud computing cannot do without virtualization. Cloud computing, the use of virtualization technology, the resource mapping of physical servers to virtual machine layer on a server to deploy multiple virtual machines. To perform user tasks using the virtual machine, it will not only improve the utilization of server resources, while ensuring the independence of the application of different users.
In recent years, more and more enterprise architecture its own cloud server, cloud computing system has to meet the need of resource allocation and task scheduling strategy to meet the needs of users, there is no task scheduling standards. Therefore, it has important theoretical and practical significance to the research of cloud computing task scheduling algorithm under the environment. This paper analyzes the research the status of task scheduling method in cloud computing environment is summarized, which is an emerging business model of the unique characteristics of cloud computing, on the existing scheduling problems in-depth analysis, and then according to the independent type and the dependent two kinds of task, put forward two kinds of task scheduling algorithms. In addition, taking into account the different the user preference of virtual machine resources on Cloud Computing Center, for many users, the task scheduling algorithm design standards. In general, this paper mainly completed the following work:
The independent task for cloud computing environment, the existing scheduling method generally includes genetic algorithm, ant colony algorithm, simulated annealing algorithm and other intelligent algorithms, the algorithm converges faster, but easy to fall into local optimum, and the algorithm is too dependent on the design of fitness function, the complexity of the algorithm is higher. Considering the stochastic algorithm the disadvantage, we analyze the problem of cloud computing task scheduling environment, designed a task scheduling game model, all user tasks as the player of the game, the selected virtual machine as the game strategy, the task of processing delay as a utility function of game participants. Find the potential function of the game that proves that the game is a potential game, and the game of the Nash equilibrium, using mathematical analysis, proved that the stable point of the game is the potential function of the minimum point in addition, Presents a task scheduling algorithm based on potential game, each virtual machine algorithm can solve the game task distribution reaches the stable point. Simulation results show that the overall processing delay of the scheduling algorithm can reduce task, and make changes in the load balance of the system is adaptive to the degree of user task amount, when the quantity of task less, less open virtual machine resources, reduce the cost of the system, when the task quantity is more and more open virtual machine resources, ensure the task of QoS. in addition, considering the threshold limit of the virtual machine, the proposed algorithm is extended to the virtual machine threshold limits the parameter added to the algorithm. The algorithm is more general.
For dependent tasks, task analysis DAG, mainly studies the Fork-Join task graph for this kind of task, Wardrop equilibrium principle of network game theory based on the given by the user task processing time delay as the game analysis of the cost function, considering all the users in the network, the optimal solution of all the user into a single user user optimal problem solving, a task scheduling algorithm for the system design, the algorithm can solve the Wardrop equilibrium theory in optimal state. Finally, this algorithm in the simulation experiment, experimental results show that the algorithm compared to the single user optimum, this algorithm can quickly complete the task of the user, and the users of cloud computing task to achieve optimal system.
According to the users of cloud computing tasks with different bias of virtual machine resources, task scheduling for multi user multi criterion is studied. In the cloud computing environment, some users tend to choose the processing resources of virtual machine small delay, some users tend to choose low cost virtual machine resources, some users tend to virtual machine resources to choose more safe. According to different user preferences, the network users are divided into many types of users, only consider the two indicators of cost and time, for the multi class user and virtual machine resources design competition game model, find the potential function of the game, the game is proved a potential game, and prove the existence of Nash equilibrium game, and the maximum value of the equivalent Nash equilibrium and potential function. Finally, put forward a task scheduling algorithm for multi user multi criterion based on solving the game reached The amount of task distribution on each virtual machine scale. Simulation results show that the algorithm, the proposed algorithm has convergence algorithm for solving steady state results and are all selfish users through free after the game is the same, and further illustrates the effectiveness and feasibility of the algorithm.

【學位授予單位】：山東師范大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.01

【引證文獻】

相關碩士學位論文 前1條

1 任新新;基于結構優(yōu)化的虛擬網映射算法研究[D];山東師范大學;2015年

本文編號：1712399