【摘要】：數(shù)據(jù)中心的低效率是一個普遍存在并且日益嚴重的問題。物價上漲和越來越多的環(huán)境危害影響企業(yè)投資前景,威脅企業(yè)的利潤,并且需要監(jiān)管機構的審查。除了運營的成本高外,一個主要的問題是排放二氧化碳(CO2)所帶來的能源消費。越來越多的顧客開始考慮在選擇“綠色”方面的產(chǎn)品和服務。除了環(huán)境問題,企業(yè)已經(jīng)開始面臨被標上“環(huán)境不友好”所帶來的風險。減少二氧化碳的排放是一個十分重要的問題。為了取得進一步進展,必須用計算機系統(tǒng)來解決。 云計算作為一種并行與分布系統(tǒng)的形式組成了動態(tài)配置的相互連接和虛擬的計算機的一個集合。表現(xiàn)為一個或更多個建立在由服務器和客戶端協(xié)商形成的服務協(xié)議上的統(tǒng)一計算資源。一些新興的云計算基礎設施/平臺如谷歌的App Engine,微軟的Azure,亞馬遜EC2和Aneka等。從能源效率的角度來看,一個云計算數(shù)據(jù)中心可以被定義為大量的計算和通信資源,我們可以使用它將接收的功率轉(zhuǎn)換為計算或數(shù)據(jù)傳輸工作,以滿足用戶的需求。云計算的一個含義為動態(tài)調(diào)整(相應增加或者減少)在白天或者在黑夜觀察到的可預測的或者由訪問模式變更而產(chǎn)生的；或者在應用服務上的一個微小的增加引起的滿足需求變化和應用的資源的數(shù)量。云計算的這種性能對彈性應用(自動縮放)特別有效。如虛擬主機,信息傳遞,社交網(wǎng)絡等都易受這種性能的影響。這些應用常常呈現(xiàn)出瞬間行為(使用模式)和根據(jù)臨界時間和用戶的互動模式(在線/離線)所需要的不同質(zhì)量服務(QoS)要求。 計算虛擬化是創(chuàng)造一個虛擬的(而不是實際)的版本。如一個硬件平臺,一個操作系統(tǒng),一個存儲設備或者一個網(wǎng)絡資源。虛擬化是IT企業(yè)總體趨勢的一部分。IT企業(yè)總體趨勢還包括自動計算、在IT環(huán)境將能夠管理自己基于知覺活動的一個場景。隨著虛擬化技術的快速發(fā)展,大多數(shù)數(shù)據(jù)中心都采用了云計算來設計新一代的數(shù)據(jù)中心框架。這項技術所帶來的好處包括,提高資源利用率,降低運營成本和簡化服務器管理。服務器整合和虛擬機實時遷移也可以用來實現(xiàn)負載均衡和節(jié)能。 虛擬化是已廣泛應用于現(xiàn)代數(shù)據(jù)中心云計算來實現(xiàn)服務器節(jié)能行動的創(chuàng)新。虛擬機(VM)遷移帶來多種益處,如資源分布和能源意識到鞏固。服務器整合實現(xiàn)了能源利用效率,使操作系統(tǒng)的多個實例同時運行在一臺機器。隨著虛擬化,它可能通過虛擬機實時遷移來鞏固服務器。然而,虛擬機遷移帶來額外的能源消耗和全面采用這項技術而導致脫軌的嚴重的安全問題。 雖然以前的工作提供了高效節(jié)能的虛擬機分配,但是虛擬機安全性在能耗方面還沒有被廣泛的研究。本文就是要填補這個由其他研究人員所忽視的不足。因次,本文對其它研究人員而言是互補性的,它提供了在現(xiàn)實世界中部署服務器整合和安全方面的一些有益的見解。 針對論文前面提到的問題,它指出了一些有用的研究方向,以更好地提高數(shù)據(jù)中心的能源效率。本文針對如何提高云計算數(shù)據(jù)中心能源效率問題基于時間輪轉(zhuǎn)算法提出了詳細的解決方案,同時針對實時遷移導致的安全缺陷提出了一種安全的遷移策略。首先,采用時間輪轉(zhuǎn)算法作為虛擬機調(diào)度算法,以減少用于運行虛擬機的物理服務器數(shù)量,同時為確保遷移過程中的虛擬機安全,在已有的虛擬機監(jiān)控器中引入了安全模塊；其次,本文通過工作量配置控制器及工作負載遷移控制器管理服務器集群的工作量,工作量配置控制器包括模擬單一服務器上的多個應用程序工作負載分配的組件和基于遺傳算法用于檢索服務器中大量可替換的工作量并記錄發(fā)現(xiàn)的最好解決方案的優(yōu)化搜索組件,工作量負載遷移控制器是一個基于模糊邏輯的反饋控制回路,此控制器初始化時記錄所有相關服務器最近負載情況及工作量,并確定協(xié)調(diào)服務器負載均衡的適當行動,其顧問模塊持續(xù)監(jiān)控服務器的資源利用率,在資源利用率過高或過低時觸發(fā)模糊控制模塊采取適當?shù)男袆邮狗⻊掌髻Y源利用率恢復均衡；最后,本文深入論述了虛擬機實時遷移過程中已知的安全隱患,針對這些安全隱患本文提出了種安全遷移策略,此策略通過確保安全進程的存儲頁在遷移過程中對其他進程或操作系統(tǒng)是不可見的,保證虛擬機實時遷移過程中的完整性和隱私保護,以消除實時遷移導致的安全缺陷。 本文介紹了當前可用的仿真器,通過比較給出了為什么本文會選擇CloudSim作為仿真框架。然后對CloudSim框架的細節(jié)進行了深入的研究,并對其進行修改以使其適應本文的需求。當前可用的云計算仿真器還比較少,CloudSim可能是其中最復雜的一個。相比GreeenCloud仿真器,CloudSim提供了更精確的時間單位。GreenCloud支持帶期限的工作量,但是只有簡單的單核服務器的調(diào)度策略,MDCSim的工作量僅僅被描述為計算需求,而且限定沒有數(shù)據(jù)的遷移。CloudSim可以實現(xiàn)基于資源的虛擬化技術的復雜調(diào)度和任務執(zhí)行策略。另外,CloudSim還支持能源節(jié)省和能源模型。其方便的可擴展性和可用性,使得它成為本文方案中的首選。 CloudSim采用多層次的軟件框架和架構構件設計。主要分為用戶代碼層和核心層。用戶代碼層可以指定仿真的相關設置,包括仿真的場景,用戶的需求,應用的配置以及用戶和數(shù)據(jù)中心的調(diào)度協(xié)議等,核心層包括了供用戶代碼層使用的接口,虛擬機服務,網(wǎng)絡拓撲設置,云服務資源以及調(diào)度策略等。CloudSim框架提供了基本的模型和實體來實現(xiàn)驗證和評價能耗敏感的擴展的技術和算法。本文對CloudSim進行了一系列的擴展使得它能夠在資源和虛擬機層次模擬高效能耗敏感配置策略。通過擴展處理單元(PE)對象使其包括一個額外的能耗模型對象,來管理每個云主機基礎上的能源消耗。為了支持不同的功耗模式和電源管理技術,如動態(tài)電壓和頻率縮放(DVFS)的建模與仿真,本文提供了一個抽象的實施稱為PowerModel。該抽象類已經(jīng)由一個PE的模擬定制能源消費模式來擴展。論文重寫了該類的getPower方法,該方法的的輸入?yún)?shù)是云主機的當前利用率,輸入?yún)?shù)為當前的能源消耗值。該改進使得CloudSim能夠創(chuàng)造需要實時能耗信息的能耗敏感配置協(xié)議,而且還能統(tǒng)計系統(tǒng)仿真器件的能源消耗總和。 本論文還基于CloudSim實現(xiàn)了安全模塊。CloudSim實體實時產(chǎn)生的每一個事件將被存儲在隊列中,這類事件被稱為未來事件。這些事件按時間參數(shù)順序插入到隊列中。接下來,事件模擬的每一步調(diào)度都將使得事件從未來事件隊列中刪除,并轉(zhuǎn)移到延遲事件隊列。在此之后,一個事件處理方法和安全模塊被每個實體調(diào)用,從延遲事件隊列中選擇事件并執(zhí)行相應的動作。這樣的組織,允許仿真器靈活的組織,并提供了虛擬機保護與防止重放攻擊、實體的鈍化和在模擬運行時中止并重新啟動的強有力的功能。 針對本文提出的算法,本文進行了仿真實驗,實驗中使用CloudSim框架進行修改,證明該方法是有效的。在本文中提出兩種實驗來評估該算法,第一組的測試實驗是采用兩層(2T)、三層(3T)及三層高速架構(3Ths)的方法,先是固定計算節(jié)點的數(shù)量為1500,對比原因是三種拓撲結構數(shù)量和互聯(lián)網(wǎng)交換機的不同。第二組實驗是驗證所提出的節(jié)能技術VM配置技術的有效性。在這個實驗中,本文研究比較了兩個節(jié)能資源管理技術相對一個基準瑣碎技術,并沒有考慮在VM優(yōu)化配置期間到主機�；鶞蕼y試技術是處理器在最大頻率下工作,該種情況下進行操作能使處理能力達到最高。在實驗中通過CloudSim提供的工具包來估計該算法,CloudSim工具包提供了一些新特性,另外還有其提供的獨特功能有可用的虛擬化引擎和靈活處理核心共享空間和時間共享之間的切換分配到虛擬化服務。 從實驗結果可以使我們確信采用動態(tài)循環(huán)制算法來進行服務器整合在要求絕對安全的數(shù)據(jù)中心下對降低能耗是一種非�？尚械慕鉀Q方案。在虛擬機遷移中使用動態(tài)循環(huán)算法應用于服務器整合是一個以減少數(shù)據(jù)中心能源消耗,而不會危及安全的非�？尚械慕鉀Q方案。與現(xiàn)有的方案,如動態(tài)電壓頻率縮放相比,我們的策略也有較低的軟件許可侵犯。實驗證明,提出的在遷移過程中緩解安全策略,對著名的虛擬機的攻擊,如恢復訂購和重放攻擊是可行的。
[Abstract]:The low efficiency of the data center is a widespread and increasingly serious problem. Rising prices and increasing environmental hazards affect enterprise investment prospects, threaten business profits, and require regulatory scrutiny. In addition to the high cost of operation, a major problem is the energy consumption caused by the emission of carbon dioxide (CO2). The more customers begin to consider the "green" products and services. In addition to the environmental problems, enterprises have begun to face the risk of being labeled "environmentally unfriendly". Reducing carbon dioxide emissions is a very important problem. In order to make further progress, the computer system must be used to solve it.
Cloud computing forms a set of dynamically configured interconnections and virtual computers as a form of parallel and distributed systems. It represents one or more unified computing resources built on service protocols formed by server and client negotiation. Some emerging cloud computing infrastructure / platforms, such as Google's App Engi NE, Microsoft's Azure, Amazon EC2 and Aneka, and so on. From an energy efficiency point of view, a cloud computing data center can be defined as a large number of computing and communication resources, and we can use it to convert the received power into computing or data transmission to meet the user's needs. One of the meaning of cloud computing is dynamic adjustment (Xiang Yingzeng Additive or reduced) predictability or changes in access patterns observed during the day or in the night; or the number of resources that meet demand changes and applications in a small increase in application services. This performance of cloud computing is particularly effective for elastic applications (automatic scaling), such as virtual hosts. Transmission, social networks, etc. are easily affected by this performance. These applications often present instantaneous behavior (use pattern) and the different quality service (QoS) requirements required by the critical time and user's interactive mode (online / offline).
Computational virtualization is a virtual (rather than practical) version, such as a hardware platform, an operating system, a storage device, or a network resource. Virtualization is part of the overall trend of the IT enterprise, and the overall trend of the.IT enterprise includes automatic computing, and a field that will be able to manage its own perception based activities in the IT environment. With the rapid development of virtualization technology, most data centers have adopted cloud computing to design a new generation of data center frameworks. The benefits of this technology include improving resource utilization, reducing operating costs and simplifying server management. Server integration and virtual machine real-time migration can also be used to achieve load balancing. And energy saving.
Virtualization is an innovation that has been widely used in modern data center cloud computing to achieve server energy saving action. Virtual machine (VM) migration brings many benefits, such as resource distribution and energy awareness to consolidate. Server integration implements energy efficiency and makes multiple instances of the operating system run on a machine at the same time. With virtualization, it can The virtual machine can be migrated to consolidate the server. However, the virtual machine migration brings additional energy consumption and the full use of this technology, which leads to the serious security problem of derailment.
Although previous work provides efficient and energy-efficient virtual machine allocation, virtual machine security has not been widely studied in terms of energy consumption. This article is to fill this inadequacy that is ignored by other researchers. This article is complementary to other researchers, which provides the deployment of servers in the real world. Some useful views on combination and safety.
In view of the problems mentioned above, it points out some useful research directions to better improve the energy efficiency of the data center. This paper presents a detailed solution based on the time rotation algorithm on how to improve the energy efficiency of the cloud computing data center. At the same time, a kind of security defect caused by real-time migration is put forward. First, the time rotation algorithm is used as a virtual machine scheduling algorithm to reduce the number of physical servers used to run the virtual machine. At the same time, in order to ensure the security of the virtual machine in the migration process, the security module is introduced in the existing virtual machine monitor. The load migration controller manages the workload of the server cluster, and the workload configuration controller includes components that simulate multiple application workload allocation on a single server and an optimized search component based on a genetic algorithm for retrieving a large amount of replaceable workload in the server and recording the best solution for the discovery, and the workload load The migration controller is a feedback control loop based on fuzzy logic, which is initialized to record the load and workload of all related servers and to determine the appropriate action to coordinate the load balance of the server. The consultant module continuously monitors the resource utilization of the server and triggers the mode when the resource utilization rate is too high or too low. The paste control module takes appropriate action to restore the balance of server resource utilization. Finally, this paper discusses the hidden security risks known in the process of real time migration of virtual machines. In this paper, a security migration strategy is proposed for these hidden dangers. This strategy ensures that the storage page of the security progress is used in the migration process to other processes. Or the operating system is invisible to ensure the integrity and privacy protection of the virtual machine during real-time migration, so as to eliminate the security defects caused by real-time migration.
This article introduces current available emulators, and gives a comparison of why this article selects CloudSim as a simulation framework. Then, the details of the CloudSim framework are deeply studied and modified to adapt to the requirements of this article. The current available cloud computing simulator is still relatively small, and CloudSim may be the most complex. One. Compared to the GreeenCloud emulator, CloudSim provides a more precise time unit.GreenCloud to support the workload of the time limit, but only a simple single kernel server scheduling strategy, the workload of the MDCSim is only described as the computing requirement, and the limited data free migration.CloudSim can implement resource based virtualization technology. In addition, the CloudSim also supports energy saving and energy models. The convenience of scalability and availability makes it the first choice in this paper.
CloudSim uses a multilevel software framework and architecture component design. It is divided into user code layer and core layer. The user code layer can specify simulation settings, including simulation scenarios, user requirements, application configuration, and scheduling protocols for users and data centers. The core layer includes the interface for user code layer. .CloudSim frameworks such as virtual machine services, network topology settings, cloud service resources, and scheduling policies provide basic models and entities to validate and evaluate energy sensitive extension techniques and algorithms. A series of extensions to CloudSim are made in this paper to enable it to simulate efficient energy consumption sensitive matching at the source and virtual machine levels. In order to support different power consumption patterns and power management technologies, such as dynamic voltage and DVFS modeling and simulation, this paper provides an abstract implementation called PowerMod. This article provides an abstract implementation called PowerMod. El. this abstract class has been extended by a PE simulation custom energy consumption pattern. The paper rewrites the getPower method of this class. The input parameter of this method is the current utilization of the cloud host and the input parameter is the current energy consumption value. This improvement enables the CloudSim to create an energy consumption sensitive configuration protocol that requires real-time energy consumption information. It can also calculate the total energy consumption of the system simulation device.
On the basis of CloudSim, each event generated by the security module.CloudSim entity will be stored in the queue, which is called the future event. These events are inserted into the queue in a time parameter order. Next, each step of the event simulation will make the event delete from the future event queue and turn the event into the queue. Move to the delay event queue. After that, an event processing method and security module are called by each entity, selecting events from the delayed event queue and performing corresponding actions. Such organizations allow the emulator to be organized flexibly, and provide a virtual machine protection and prevention of replay attacks, the inactivation of the entity, and the discontinuation of the simulation run. And reboot the powerful function.
In this paper, a simulation experiment is carried out in this paper. In the experiment, the CloudSim framework is used to modify the method to prove that the method is effective. In this paper, two experiments are proposed to evaluate the algorithm. The first test experiment is the method of using two layers (2T), three layers (3T) and three layer high speed architecture (3Ths). First, the number of fixed computing nodes is fixed. For 1500, the comparison is due to the difference between the number of three topology structures and the Internet switch. The second set of experiments is a validation of the effectiveness of the proposed energy saving technology VM configuration technology. In this experiment, this paper compared two energy saving resource management technologies relative to a benchmark trivial technique, and did not consider the owner to the master during the optimal configuration. The standard test technique is the processor working at the maximum frequency, in which the operation makes the highest processing power. In the experiment, the algorithm is estimated by the tool package provided by the CloudSim, the CloudSim toolkit provides some new features, and the unique features provided by it have the available virtualization engines and flexibility. The switch between core sharing and time sharing is allocated to virtualization services.
From the experimental results we can make sure that the use of dynamic cyclic algorithm for server integration is a very feasible solution to reduce energy consumption in a data center requiring absolute security. In virtual machine migration, the application of dynamic loop algorithm to server integration is one to reduce the energy consumption of data centers, but not A very feasible solution that endangers security. Compared with existing schemes, such as dynamic voltage scaling, our strategy also has a lower software license violation. Experiments show that the proposed mitigation strategy in the migration process, the attack on the famous virtual machine, such as restoring order and replay attacks, is feasible.
【學位授予單位】：中南大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TP308

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相關期刊論文 前1條

1 陳康;鄭緯民;;云計算:系統(tǒng)實例與研究現(xiàn)狀[J];軟件學報;2009年05期

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本文編號：2139193