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云服務系統(tǒng)中組件服務副本的關鍵問題研究

發(fā)布時間:2018-01-30 22:58

  本文關鍵詞: 云服務系統(tǒng) 組件服務副本 吞吐量約束 拓撲匹配 灰色-馬爾科夫預測 CloudSim 出處:《東北大學》2014年碩士論文 論文類型:學位論文


【摘要】:隨著云計算技術的日益成熟,云服務系統(tǒng)已經成為了一種重要的軟件開發(fā)模式。在云服務系統(tǒng)應用中,組件服務被部署在不同的服務器或者服務器集群中。由于用戶訪問行為的不確定性,當用戶訪問量增加時,云服務系統(tǒng)可以動態(tài)增加組件服務副本,提高系統(tǒng)的吞吐量進而保證云服務系統(tǒng)性能。從而,如何放置及選擇合適的組件服務副本以保證云服務系統(tǒng)的性能已經成為了目前研究的一個熱點。本文首先分析了云服務系統(tǒng)中組件服務副本相關技術,針對于其中的組件服務副本數量估計、組件服務副本放置以及組件服務副本選擇等三個關鍵問題展開了研究工作。針對于組件服務副本數量估計問題,提出了一個基于吞吐量約束的組件服務副本數量估計算法,該算法根據所建立的組件服務吞吐量聚合規(guī)則,面向云服務系統(tǒng)吞吐量約束保證,計算每個組件服務的吞吐量約束,進而得到每個組件服務副本的數量。針對組件服務副本放置問題,提出了一個基于圖拓撲匹配的組件服務副本放置算法,該算法使用聚類技術獲得組件服務和計算節(jié)點的拓撲結構,并通過匹配兩種拓撲結構來進行組件服務副本放置。該算法可以有效的降低云應用的執(zhí)行周期和延遲時間。針對組件服務副本選擇問題,通過結合負載模型和灰色-馬爾可夫預測技術提出了基于灰色-馬爾可夫預測的組件服務副本選擇算法。在進行組件服務副本選擇時,對計算節(jié)點的負載進行預測,并從中選擇負載最小的計算節(jié)點來進行組件服務副本選擇。通過使用該算法,可以有效的提高組件服務副本的利用率;贑loudSim云仿真軟件搭建了一個仿真實驗環(huán)境并開展了一系列實驗,仿真實驗結果表明了所提出的方案和算法的有效性。
[Abstract]:With the development of cloud computing technology, cloud service system has become an important software development model. Component services are deployed in different servers or server clusters. Because of the uncertainty of user access behavior, cloud service systems can dynamically increase replicas of component services when user traffic increases. Improve the throughput of the system and thus ensure the performance of the cloud service system. How to place and select the appropriate component service replica to ensure the performance of cloud service system has become a hot topic. Firstly, this paper analyzes the component service replica related technology in cloud service system. This paper focuses on the estimation of the number of component service replicas, the placement of component service replicas and the selection of component service replicas, and aims at estimating the number of component service replicas. An algorithm for estimating the number of component service replicas based on throughput constraints is proposed. According to the established aggregation rules of component service throughput, the algorithm is oriented to the throughput constraint assurance of cloud service systems. The throughput constraints of each component service are calculated, and then the number of replicas of each component service is obtained. A component service replica placement algorithm based on graph topology matching is proposed to address the problem of component service replica placement. The algorithm uses clustering technology to obtain the topology of component services and compute nodes. The algorithm can effectively reduce the execution period and delay time of the cloud application, aiming at the problem of component service replica selection. By combining the load model and the grey-Markov prediction technology, this paper proposes a component service replica selection algorithm based on the gray Markov prediction, which is used to select the component service replicas. The load of the computing node is predicted and the computing node with the smallest load is selected to select the copy of the component service. It can effectively improve the utilization rate of component service replicas. A simulation environment based on CloudSim cloud simulation software is built and a series of experiments are carried out. Simulation results show the effectiveness of the proposed scheme and algorithm.
【學位授予單位】:東北大學
【學位級別】:碩士
【學位授予年份】:2014
【分類號】:TP393.09
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本文編號:1477465

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