本文選題：云銀行運(yùn)行周期　切入點(diǎn)：粒子群算法　出處：《云南大學(xué)》2012年碩士論文

【摘要】：隨著社會經(jīng)濟(jì)的發(fā)展,現(xiàn)實(shí)生活中各個領(lǐng)域都要求計(jì)算機(jī)能夠擁有更加強(qiáng)大的計(jì)算能力,并且能夠更加有效快速的整合資源。因此,云計(jì)算孕育而生,帶來了計(jì)算科學(xué)的一場革命。云計(jì)算能夠幫助提高科學(xué)計(jì)算和商業(yè)計(jì)算的能力,對于提升國家的綜合競爭力有著極其關(guān)鍵的作用。云計(jì)算的最終目的是共享資源和服務(wù),因此如何有效的對云計(jì)算問題中的資源進(jìn)行定價以及分配成為云計(jì)算的重要問題。 本文的重點(diǎn)是討論云計(jì)算中的資源定價問題。為了討論資源交易的過程,定義了三個參與交易的主要角色：資源提供者,云銀行,資源消費(fèi)者。資源提供者為云銀行提供資源,云銀行制定具體的資源分配規(guī)則和價格,資源消費(fèi)者提出應(yīng)用請求。本文引入了經(jīng)濟(jì)學(xué)理論來為資源價格的制定提供理論依據(jù),云銀行模型的背景下提出了以粒子群算法為基礎(chǔ)的計(jì)算資源定價策略。該策略主要用于完成云銀行運(yùn)行周期中定階段的資源定價,從而實(shí)現(xiàn)計(jì)算資源的價格實(shí)時自動更新,避免了人為干擾的因素,最終達(dá)到資源交易參與各方利益最大化。最后,本文運(yùn)用CloudSim模擬實(shí)驗(yàn)平臺對所提出的定價策略做了簡單的實(shí)驗(yàn),驗(yàn)證了該策略能夠在一般市場價格規(guī)律條件下,幫助模擬實(shí)現(xiàn)計(jì)算資源價格的自動調(diào)整。
[Abstract]:With the development of social economy, all fields in real life require that computers can have more powerful computing power and integrate resources more effectively and quickly.Therefore, cloud computing was conceived and brought about a revolution in computing science.Cloud computing can help improve the ability of scientific and commercial computing, and it is crucial to improve the overall competitiveness of a country.The ultimate goal of cloud computing is to share resources and services, so how to effectively price and allocate the resources in cloud computing has become an important issue for cloud computing.This paper focuses on resource pricing in cloud computing.In order to discuss the process of resource transaction, three main players are defined: resource provider, cloud bank, and resource consumer.The resource provider provides the resources for the cloud bank, the cloud bank formulates the concrete resource allocation rule and the price, the resources consumer puts forward the application request.In this paper, the economic theory is introduced to provide the theoretical basis for the formulation of resource prices. In the background of cloud bank model, a computational resource pricing strategy based on particle swarm optimization is proposed.This strategy is mainly used to complete the resource pricing in the fixed stage of the cloud bank operation cycle, thereby realizing the real-time and automatic updating of the calculated resource price, avoiding the factors of human interference, and finally maximizing the benefit of the participants in the resource transaction.Finally, this paper makes a simple experiment on the proposed pricing strategy by using CloudSim simulation experiment platform, and verifies that the strategy can help the simulation to realize the automatic adjustment of the calculated resource price under the general market price rule.
【學(xué)位授予單位】：云南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：TP3;F830.3

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本文編號：1705399