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1、<p><b> 附錄A 譯文</b></p><p> 超越臺式機:一個關(guān)于云計算的介紹 </p><p> 在這個世界上幾乎每一天都能看到新技術(shù)趨勢的崛起和衰退,一種新的趨勢帶來了更長久的生命力。這種趨勢被稱為云計算,它將改變你使用電腦和互聯(lián)網(wǎng)的方式。</p><p> 云計算預(yù)示著我們在如何存儲信息和運行應(yīng)用程序問題上
2、的重大變革。而不是在單獨的計算機上運行程序的散的數(shù)據(jù),一切都托管在“云”中,通過英特網(wǎng)去訪問“云”中的其他計算機和服務(wù)器。云計算讓你能夠在世界上的任何地方訪問你所有的應(yīng)用程序和文檔,擺脫了臺式機的束縛,讓你更容易在不同的地方和同事進行協(xié)作。</p><p> 第一部分 認識云計算</p><p> 云計算的出現(xiàn)就相當于一個世紀前電力革命的發(fā)生。在電力公司出現(xiàn)之前,每一個農(nóng)場和企業(yè)都通過
3、自己獨立的發(fā)電機發(fā)電。在電網(wǎng)產(chǎn)生以后,農(nóng)場和企業(yè)關(guān)閉他們自己的的發(fā)電機,并且從電力公司以一個比他們用自己發(fā)電機發(fā)電低得多的價格(并且更具有可靠性)買電。</p><p> 為了尋找相同類型革命的發(fā)生,使得云計算成為定局。由于我們所期望的教育普及,每時每刻的可靠性和無處不在的云計算協(xié)作承諾使得以臺式機為計算中心的觀念半途而廢。云計算將是未來發(fā)展的方向。</p><p> 云計算:它是什么
4、和它的不同</p><p> 通過傳統(tǒng)的桌面計算,你可以在你的每一臺電腦上運行程序的副本,你所創(chuàng)建的文件都保存在你創(chuàng)建文件的計算機上。雖然它們能夠被這個網(wǎng)絡(luò)上的其他計算機訪問,但是它們不能被外網(wǎng)的計算機訪問。</p><p> 整個的場景都是以個人計算機為中心。</p><p> 通過云計算,你使用的軟件程序不需要運行在你的個人電腦上,但是卻可以通過訪問英特網(wǎng)
5、上的服務(wù)器使用這個軟件程序。假如你的電腦死機了,但是這個軟件程序仍然可以供其他人使用。這種模式仍然適用于你創(chuàng)建的文件,它們被儲存在一個可以通過互聯(lián)網(wǎng)訪問的集合中。經(jīng)過許可的任何人不僅可以訪問文件,還可以實時地編輯和處理這些文件。不同于傳統(tǒng)的計算,云計算模式不以個人計算機為中心,而是以文檔為中心,個人計算機使用簡單的文件訪問并不重要。</p><p> 但是這只是一個簡化。讓我們來看看更詳細的云計算是什么樣子的?
6、它和我們了解云計算的不同同樣重要。</p><p><b> 云計算的不同</b></p><p> 首先,云計算不是網(wǎng)絡(luò)計算。通過網(wǎng)絡(luò)計算,應(yīng)用程序和文檔被托管在一個公司的服務(wù)器中并且通過公司的網(wǎng)絡(luò)可以訪問那些應(yīng)用程序和文檔。云計算要比網(wǎng)絡(luò)計算大很多,它包含了許多個公司,許多個服務(wù)器和許多個網(wǎng)絡(luò)。此外,與網(wǎng)絡(luò)計算不同,云服務(wù)和儲存通過網(wǎng)絡(luò)在世界的任何地方都可以訪
7、問,但是通過網(wǎng)絡(luò)計算,只能在自己公司的網(wǎng)絡(luò)訪問到。</p><p> 云計算也不是傳統(tǒng)的像一個公司將計算服務(wù)外包(分包)給一個外部公司。雖然外包公司可以托管一個公司的數(shù)據(jù)或者應(yīng)用程序,但是這些程序和計劃只有這個公司的員工通過公司的網(wǎng)絡(luò)才能訪問到,而不是通過整個英特網(wǎng)。</p><p> 因此,盡管表面上很相似,但是網(wǎng)絡(luò)計算和外包不是云計算。</p><p>&l
8、t;b> 什么是云計算</b></p><p> 云計算定義的關(guān)鍵是“云”本身。對于我們而言,云是一大群互聯(lián)的計算機。這些計算機可以是個人電腦或者網(wǎng)絡(luò)服務(wù)器,它們可以是公共或者私人的。</p><p> 例如,谷歌的云是由小的個人電腦和更大的服務(wù)器組成的。谷歌云是私人的(即,谷歌擁有它),是公開訪問的(通過谷歌用戶)。</p><p> 這
9、種計算機云繼承并且超越了單一的公司或者企業(yè)??缙髽I(yè)的跨平臺的廣大用戶群可以訪問云服務(wù)所提供的應(yīng)用程序和數(shù)據(jù)。通過互聯(lián)網(wǎng)訪問,任何被授權(quán)的用戶可以訪問連接在英特網(wǎng)上的任何計算機上的這些文檔和應(yīng)用程序。并且,對于用戶而言,云技術(shù)和云背后的基礎(chǔ)設(shè)施是不可見的。</p><p> 云技術(shù)是否基于HTTP,HTML協(xié)議,XML,JavaScript或者其他特定的技術(shù)是不明顯的。(在大多數(shù)情況下是無所謂的)。</p&
10、gt;<p> 云計算是用戶為中心的。一旦你作為一個用戶連接到云,無論儲存在哪里的文件,信息,圖像,應(yīng)用程序,無論什么都將變成你的。此外,你的數(shù)據(jù)也可以和他人分享。事實上,任何訪問你的數(shù)據(jù)的設(shè)備在云中都將變成你的。</p><p> 云計算是以任務(wù)為中心的。而不是以應(yīng)用程序和它能為你做什么為重點,重點是你需要做什么和應(yīng)用程序怎樣為你完成這個需求。傳統(tǒng)的應(yīng)用程序----文字處理,電子表格,電子郵件
11、等,都將變得沒有它們所產(chǎn)生的文件重要。</p><p> 第二部分 認識云計算</p><p> 云計算是強大的。連接在一起的數(shù)百臺或者數(shù)千臺計算機共同創(chuàng)造的計算能力是一臺單獨的臺式計算機無法比擬的。</p><p> 云計算是可訪問的。因為數(shù)據(jù)被存儲在云中,用戶可以迅速地從多個庫中檢索出更多的信息,你不僅限于一個單獨的數(shù)據(jù)源,如同你和你的臺式個人電腦一樣。&
12、lt;/p><p> 云計算是智能的。由于云中電腦儲存著各種數(shù)據(jù),數(shù)據(jù)挖掘和分析對于以智能的方式訪問這些信息是必要的。</p><p> 云計算是可編程的。許多伴隨云計算的必要任務(wù)必須要實現(xiàn)自動化。例如,要保護存儲在云中某臺計算機上的集成數(shù)據(jù)和信息需要在云中的另外一臺計算機上完整的復(fù)制。如果云中的某臺準備被用于復(fù)制這些數(shù)據(jù)和信息的計算機脫機,那么云的編程將自動的將該計算機的數(shù)據(jù)復(fù)制到云中新
13、的計算機上。</p><p> 所有的這些都是在我們背后定義的,那么什么才是現(xiàn)實世界中的云計算?</p><p> 當你學(xué)習(xí)完整本書,網(wǎng)站托管,互聯(lián)網(wǎng)訪問,團體協(xié)作的應(yīng)用程序一般是可用的。伴隨著更多的方式,也許今天最好最流行的云計算應(yīng)用例子就是谷歌大家庭中的應(yīng)用程序---谷歌文檔和電子表格,谷歌日歷,谷歌郵箱,圖片管理等等。這些應(yīng)用都被托管在谷歌的服務(wù)器中,是任何連接在互聯(lián)網(wǎng)上的用戶都
14、可以訪問的,可用于在世界不同地域的團體協(xié)作。</p><p> 總之,云計算使計算機轉(zhuǎn)移到用戶,從應(yīng)用到任務(wù),從孤立的數(shù)據(jù)到任何地方都可以訪問到的數(shù)據(jù),并且與任何人共享。用戶不再承擔(dān)管理數(shù)據(jù)的任務(wù),他甚至不需要記得數(shù)據(jù)在哪里。所有的事實是數(shù)據(jù)在云中,對于用戶和被授權(quán)的用戶是可以迅速訪問的。</p><p> 從協(xié)作到云:云計算的簡史</p><p> 云計算的
15、前身是客戶機/服務(wù)器模式的計算和點對點的分布式計算。問題是如何集中存儲協(xié)作和如何使多臺計算機協(xié)同工作以增加計算能力。</p><p> 客戶機/服務(wù)器模式計算:集中應(yīng)用和存儲</p><p> 很久以前的計算(1980年左右),一切的操作都是客戶機/服務(wù)器模式。所有的應(yīng)用程序,所有的數(shù)據(jù),都被放在大型計算機上,這種大型計算機被稱為服務(wù)器。如果用戶想訪問特定的數(shù)據(jù)或者運行程序,就必要連接
16、到大型計算機,獲得適當?shù)脑L問,然后從大型計算機上得到程序或者數(shù)據(jù)以完成相應(yīng)的操作。</p><p> 用戶通過計算機終端連接到服務(wù)器,有時也被稱為工作站或者客戶端。這臺計算機有時被稱為啞終端,因為它沒有足夠(如果有的話)的內(nèi)存,存儲空間,處理能力。這僅僅是連接到一個用戶,使他能夠使用計算機主機設(shè)備。</p><p> 當用戶獲準訪問大型主機時,信息技術(shù)(IT)的工作人員沒有偶然訪問時不
17、在的習(xí)慣。甚至在一個大型主機上,處理能力也是有限的---IT工作人員有監(jiān)護這種處理能力的權(quán)利。這種訪問不是立竿見影的,也不可能有兩個用戶同時訪問相同的數(shù)據(jù)。</p><p> 除此之外,用戶幾乎不得不采取IT工作人員給他們的一切措施(沒有任何變化)。想要使用自定義報告去顯示正常的信息子集?但是你不能這么做,雖然IT工作人員可以,但是這是他們從現(xiàn)在開始到數(shù)周后的日程安排。</p><p>
18、 事實是,當許多人共用一臺計算機,即使這是一臺大型主機,你也不得不排隊等候。需要返回一個財務(wù)報告?沒問題,如果你不介意一直等到今天下午或者明天早上。在客戶機/服務(wù)器模式環(huán)境中總是沒有直接訪問的,很少滿足直接訪問的情況。</p><p> 因此客戶機/服務(wù)器模式,雖然提供類似的集中存儲,但是不同于以用戶為中心的云計算,在客戶機/服務(wù)器模式計算中,所有的控制權(quán)在大型主機和控制該臺計算機上的人手中。這不是一個有利于
19、用戶的環(huán)境。</p><p> 點對點計算:資源共享</p><p> 你可以想象,當問客戶機/服務(wù)器模式的系統(tǒng)是一種“趕快和等待”的經(jīng)歷。該系統(tǒng)的服務(wù)器部分還創(chuàng)建了龐大的阻礙。計算機之間的所有通信必須先通過服務(wù)器,可是這種方式可能效率太低。</p><p> 最明顯的是由于一臺計算機連接到另一臺計算機需要通過服務(wù)器促使了點對點(P2P)計算的發(fā)展。P2P計算
20、定義了網(wǎng)絡(luò)中每一臺計算機具有同等責(zé)任和能力的網(wǎng)絡(luò)架構(gòu)。這種相對于傳統(tǒng)的客戶機/服務(wù)器模式的網(wǎng)絡(luò)體系架構(gòu),在網(wǎng)絡(luò)中有一臺或者多臺計算機是專門為其他計算提供服務(wù)的。(這種關(guān)系有時有主/從關(guān)系的特點,中央服務(wù)器是主,客戶機是從)。</p><p> P2P是一個均衡的概念。在P2P環(huán)境中,每臺計算機是一個客戶機和服務(wù)器,沒有主和從。通過承認所有計算機在網(wǎng)絡(luò)中的相同地位,P2P使得網(wǎng)絡(luò)中的計算機可以直接交換資源和提供相
21、互服務(wù)。沒有中央處理器的需求,因為每一臺計算機都能在要求這樣做時提供這樣的功能。</p><p> 點對點也是分散的概念??刂剖欠稚⒌模杏嬎銠C的功能是平等的。內(nèi)容在不同計算機之間也是分散的。沒有集中服務(wù)器被分配到主機的可用資源和服務(wù)。</p><p> 也許最引人注目的P2P計算實施是英特網(wǎng)。今天的許多用戶都忘記(也許不知道),英特網(wǎng)最初的設(shè)想是在其最初ARPA網(wǎng)的幌子下,作為一個
22、能夠分享在美國的計算資源的點對點系統(tǒng)。ARPA網(wǎng)的各種網(wǎng)站(其中的許多不屬于他們),連接在一起的計算機不是作為服務(wù)器和客戶機,而是平等的。</p><p> 初期的P2P英特網(wǎng)最好例子是Usenet網(wǎng)絡(luò)。它創(chuàng)建于1979年,是一個計算機網(wǎng)絡(luò)(通過英特網(wǎng)訪問),每一臺計算機提供該網(wǎng)絡(luò)的全部內(nèi)容。消息在平等的計算機之間傳播。用戶連接到Usenet的每一個服務(wù)器獲得所有(或者幾乎所有)的消息以張貼到每個單獨的服務(wù)器。
23、雖然用戶連接到Usenet服務(wù)器是傳統(tǒng)客戶機/服務(wù)器模式的性質(zhì),但是這種Usenet服務(wù)器之間的關(guān)系肯定了P2P,也預(yù)示著今天的云計算。</p><p> 不過,并不是所有的英特網(wǎng)的一部分就是P2P性質(zhì)。隨著萬維網(wǎng)中P2P的發(fā)展,退后了客戶機/服務(wù)器模式。在網(wǎng)絡(luò)上,每一個網(wǎng)站是由一個計算機組提供服務(wù),網(wǎng)站的訪問者使用客戶端軟件(網(wǎng)絡(luò)瀏覽器)來訪問它。幾乎所有的內(nèi)容都被集中,所有的控制都被集中,在這個過程中,客戶
24、端沒有自主權(quán)或者控制權(quán)在。</p><p> 分布式計算:提供更強的計算能力</p><p> P2P模型中最重要的子集之一是分布式計算,通過個人計算機在網(wǎng)絡(luò)或者在英特網(wǎng)上的閑置來提供大型的,處理器密集型項目的計算能力。所有關(guān)于多臺計算機間的周期的共享是一個簡單的概念。</p><p> 個人計算機,每天運行滿24小時,每周7天,是巨大的計算能力。大多數(shù)人不每
25、時每刻使用他們電腦,卻除去這樣一個電腦的閑置資源。分布式計算使用這些資源。</p><p> 當一臺計算機中加入到一個分布式的計算項目,軟件被安裝在這臺計算機上在用戶未使用的這段時間去運行各種處理活動。這個業(yè)余處理的結(jié)果被定期上傳到分布式計算網(wǎng)絡(luò)上,并與項目中其他計算機類似的結(jié)果相結(jié)合。結(jié)果是,如果有足夠的計算機被涉及,就模擬了更大的大型主機和超級計算機的處理能力,這對于某些大型和復(fù)雜的計算項目的必要的。<
26、;/p><p> 例如,基因研究需要大量的計算能力。對于傳統(tǒng)手段,它可能需要數(shù)年的時間來解決基本的數(shù)學(xué)問題。通過連接在一起的數(shù)千(或者百萬)臺個人計算機,更多的能力適用于這個問題,得出結(jié)論就更快。</p><p> 分布式計算的歷史可以追溯到1973年,多臺計算機聯(lián)網(wǎng)的施樂公司帕洛阿爾托研究中心是通過網(wǎng)絡(luò)尋找閑置資源來開發(fā)殺毒軟件的。一個分布式計算更實際的應(yīng)用出現(xiàn)在1988年,當DEC(數(shù)
27、字設(shè)備公司)系統(tǒng)研究中心的研究人員開發(fā)軟件,在實驗室中分布式的工作應(yīng)用在各個工作組之間以實現(xiàn)大數(shù)字。到1990年,大約100個用戶組,利用這個軟件實現(xiàn)100位數(shù)字,到1995年,同樣的效果被擴展到網(wǎng)絡(luò)來實現(xiàn)130位數(shù)字。</p><p> 沒過多久分布式計算進入了互聯(lián)網(wǎng)。第一個主要的基于英特網(wǎng)的的分布式計算項目是distribute.net,在1997年推出,雇傭了成千上萬的個人計算機來破譯加密代碼。即使是較大
28、的SETI@home,1999年5月,推出了使用連接在一起的數(shù)百萬臺的個人計算機搜索外層空間智慧生命。許多分布式計算項目是在大型企業(yè)內(nèi)進行,采用傳統(tǒng)的網(wǎng)絡(luò)連接,形成分布式計算網(wǎng)絡(luò)。另外,更大的項目通常使用互聯(lián)網(wǎng)用戶的計算機,通常發(fā)生脫機,然后每天通過傳統(tǒng)的消費英特網(wǎng)上傳資料。</p><p><b> 了解云架構(gòu)</b></p><p> 云計算的關(guān)鍵是“云”,一
29、些大規(guī)模網(wǎng)絡(luò)服務(wù)器或者個人計算機連接在龐大的網(wǎng)絡(luò)中。這些計算機并行運行,結(jié)合各自的資源,產(chǎn)生超級計算般的能力。</p><p> 究竟什么是“云”?簡而言之,云是計算機和服務(wù)器都通過英特網(wǎng)公開訪問的集合。這種硬件通常是復(fù)合的和由有一個或者多個數(shù)據(jù)中心為穩(wěn)固基礎(chǔ)的第三方運作。這些機器可以運行任何操作系統(tǒng),這些機器的處理能力不是它們作為單獨臺式機所能比擬的。</p><p> 如圖1.1所
30、示,個人用戶使用他們自己的計算機或者便攜設(shè)備通過英特網(wǎng)連接到云。對于這些個人用戶,云被看作是一個單一的應(yīng)用程序,設(shè)備或者文件。云中的硬件(操作系統(tǒng)管理硬件連接)是無形的。</p><p> 這看似簡單的云架構(gòu),它確實需要一些智能化的管理去將這些計算機連接在一起,并分配任務(wù)處理以滿足眾多的用戶。正如你可以看到在圖1.2中,這一切都開始于個別用戶看到前端界面,選擇一個任務(wù)或者服務(wù)(無論是啟動應(yīng)用程序或者打開一個文檔
31、),用戶的這些請求被傳遞到管理系統(tǒng),然后找出正確的資源,然后調(diào)用系統(tǒng)的恰當資源去供應(yīng)服務(wù)。這些服務(wù)在云中開拓中必要的資源,發(fā)布恰當?shù)木W(wǎng)頁應(yīng)用程序,或者創(chuàng)建文件和打開請求的文件,網(wǎng)頁應(yīng)用程序啟動后,系統(tǒng)的檢測和計量功能跟蹤云的使用,使資源分配和使用于正確的用戶。</p><p> 正如你所看到的,云計算概念的觀念是許多管理任務(wù)的自動化。如果一個系統(tǒng)需要人管理資源的分配過程那么這個系統(tǒng)不是云。在這種情況下,該系統(tǒng)是
32、僅僅以老式數(shù)據(jù)中心為基礎(chǔ)的客戶機/服務(wù)器模式計算的21世紀的版本。對于系統(tǒng)實現(xiàn)云的狀態(tài),必須更換人工管理實現(xiàn)自動化程序。</p><p><b> 附錄B 外文原文</b></p><p> Beyond the Desktop: An Introduction to Cloud Computing</p><p> In a worl
33、d that sees new technological trends bloom and fade on almost a daily basis, one new trend promises more longevity. This trend is called cloud computing, and it will change the way you use your computer and the Internet.
34、</p><p> Cloud computing portends a major change in how we store information and run applications. Instead of running program sand data on an individual desktop computer, everything is hosted in the “cloud”
35、—a nebulous assemblage of computers and servers accessed via the Internet. Cloud computing lets you access all your applications and documents from anywhere in the world, freeing you from the confines of the desktop and
36、making it easier for group members in different locations to collaborate.</p><p> PART 1 Understanding Cloud Computing </p><p> The emergence of cloud computing is the computing equivalent of
37、the electricity revolution of a century ago. Before the advent of electrical utilities, every farm and business produced its own electricity from freestanding generators. After the electrical grid was created, farms and
38、businesses shut down their generators and bought electricity from the utilities, at a much lower price (and with much greater reliability) than they could produce on their own.</p><p> Look for the same typ
39、e of revolution to occur as cloud computing takes hold. The desktop-centric notion of computing that we hold today is bound to fall by the wayside as we come to expect the universal access, 24/7 reliability, and ubiquito
40、us collaboration promised by cloud computing. It is the way of the future.</p><p> Cloud Computing: What It Is—and What It Isn’t</p><p> With traditional desktop computing, you run copies of s
41、oftware programs on each computer you own. The documents you create are stored on the computer on which they were created. Although documents can be accessed from other computers on the network, they can’t be accessed by
42、 computers outside the network.</p><p> The whole scene is PC-centric.</p><p> With cloud computing, the software programs you use aren’t run from your personal computer, but are rather stored
43、 on servers accessed via the Internet. If your computer crashes, the software is still available for others to use. Same goes for the documents you create; they’re stored on a collection of servers accessed via the Inter
44、net. Anyone with permission can not only access the documents, but can also edit and collaborate on those documents in real time. Unlike traditional computing, this cl</p><p> isn’t important.</p>&l
45、t;p> But that’s a simplification. Let’s look in more detail at what cloud computing</p><p> is—and, just as important, what it isn’t.</p><p> What Cloud Computing Isn’t</p><p>
46、; First, cloud computing isn’t network computing. With network computing, applications/documents are hosted on a single company’s server and accessed over the company’s network. Cloud computing is a lot bigger than that
47、. It encompasses multiple companies, multiple servers, and multiple networks. Plus, unlike network computing, cloud services and storage are accessible from anywhere in the world over an Internet connection; with network
48、 computing, access is over the company’s network only.</p><p> Cloud computing also isn’t traditional outsourcing, where a company farms out (subcontracts) its computing services to an outside firm. While a
49、n outsourcing firm might host a company’s data or applications, those documents and programs are only accessible to the company’s employees via the company’s network, not to the entire world via the Internet.</p>
50、<p> So, despite superficial similarities, networking computing and outsourcing are not cloud computing.</p><p> What Cloud Computing Is</p><p> Key to the definition of cloud computing
51、is the “cloud” itself. For our purposes, the cloud is a large group of interconnected computers. These computers can be personal computers or network servers; they can be public or private.</p><p> For exam
52、ple, Google hosts a cloud that consists of both smallish PCs and larger servers. Google’s cloud is a private one (that is, Google owns it) that is publicly accessible (by Google’s users).</p><p> This cloud
53、 of computers extends beyond a single company or enterprise. The applications and data served by the cloud are available to broad group of users, cross-enterprise and cross-platform. Access is via the Internet. Any autho
54、rized user can access these docs and apps from any computer over any Internet connection. And, to the user, the technology and infrastructure behind the cloud is invisible.</p><p> It isn’t apparent (and, i
55、n most cases doesn’t matter) whether cloud services are based on HTTP, HTML, XML, JavaScript, or other specific technologies.</p><p> _ Cloud computing is user-centric. Once you as a user are connected to t
56、he cloud, whatever is stored there—documents, messages, images, applications, whatever—becomes yours. In addition, not only is the data yours, but you can also share it with others. In effect, any device that accesses yo
57、ur data in the cloud also becomes yours.</p><p> _ Cloud computing is task-centric. Instead of focusing on the application and what it can do, the focus is on what you need done and how the application can
58、do it for you. Traditional applications—word processing, spreadsheets, email, and so on—are becoming less important than the documents they create.</p><p> PART 2 Understanding Cloud Computing</p>&l
59、t;p> _ Cloud computing is powerful. Connecting hundreds or thousands of computers together in a cloud creates a wealth of computing power impossible with a single desktop PC.</p><p> _ Cloud computing i
60、s accessible. Because data is stored in the cloud, users can instantly retrieve more information from multiple repositories. You’re not limited to a single source of data, as you are with a desktop PC.</p><p&g
61、t; _ Cloud computing is intelligent. With all the various data stored on the computers in a cloud, data mining and analysis are necessary to access that information in an intelligent manner.</p><p> _ Clou
62、d computing is programmable. Many of the tasks necessary with cloud computing must be automated. For example, to protect the integrity of the data, information stored on a single computer in the cloud must be replicated
63、on other computers in the cloud. If that one computer goes offline, the cloud’s programming automatically redistributes</p><p> that computer’s data to a new computer in the cloud.</p><p> All
64、 these definitions behind us, what constitutes cloud computing in the real world?</p><p> As you’ll learn throughout this book, a raft of web-hosted, Internet-accessible,</p><p> Group-collabo
65、rative applications are currently available, with many more on the way. Perhaps the best and most popular examples of cloud computing applications today are the Google family of applications—Google Docs & Spreadsheet
66、s, Google Calendar, Gmail, Picasa, and the like. All of these applications are hosted on Google’s servers, are accessible to any user with an Internet connection, and can be used for group collaboration from anywhere in
67、the world.</p><p> In short, cloud computing enables a shift from the computer to the user, from applications to tasks, and from isolated data to data that can be accessed from anywhere and shared with anyo
68、ne. The user no longer has to take on the task of data management; he doesn’t even have to remember where the data is. All that matters is that the data is in the cloud, and thus immediately available to that user and to
69、 other authorized users.</p><p> From Collaboration to the Cloud: A Short History of Cloud Computing</p><p> Cloud computing has as its antecedents both client/server computing and peer-to-pee
70、r distributed computing. It’s all a matter of how centralized storage facilitates collaboration and how multiple computers work together to increase computing power.</p><p> Client/Server Computing: Central
71、ized Applications and Storage</p><p> In the antediluvian days of computing (pre-1980 or so), everything operated on the client/server model. All the software applications, all the data, and all the control
72、 resided on huge mainframe computers, otherwise known as servers. If a user wanted to access specific data or run a program, he had to connect to the mainframe, gain appropriate access, and then do his business while ess
73、entially “renting” the program or data from the server.</p><p> Users connected to the server via a computer terminal, sometimes called a workstation or client. This computer was sometimes called a dumb ter
74、minal because it didn’t have a lot (if any!) memory, storage space, or processing power. It was merely a device that connected the user to and enabled him to use the mainframe computer.</p><p> Users access
75、ed the mainframe only when granted permission, and the information technology (IT) staff weren’t in the habit of handing out access casually. Even on a mainframe computer, processing power is limited—and the IT staff wer
76、e the guardians of that power. Access was not immediate, nor could two users access the same data at the same time.</p><p> Beyond that, users pretty much had to take whatever the IT staff gave them—with no
77、 variations. Want to customize a report to show only a subset of the normal information? Can’t do it. Want to create a new report to look at some new data? You can’t do it, although the IT staff can—but on their schedule
78、, which might be weeks from now.</p><p> The fact is, when multiple people are sharing a single computer, even if that computer is a huge mainframe, you have to wait your turn. Need to rerun a financial rep
79、ort? No problem—if you don’t mind waiting until this afternoon, or tomorrow morning. There isn’t always immediate access in a client/server environment, and seldom is there immediate gratification.</p><p>
80、So the client/server model, while providing similar centralized storage, differed</p><p> from cloud computing in that it did not have a user-centric focus; with client/server computing, all the control res
81、ted with the mainframe—and with the guardians of that single computer. It was not a user-enabling environment.</p><p> Peer-to-Peer Computing: Sharing Resources</p><p> As you can imagine, acc
82、essing a client/server system was kind of a “hurry up and wait” experience. The server part of the system also created a huge bottleneck. All communications between computers had to go through the server first, however i
83、nefficient that might be.</p><p> The obvious need to connect one computer to another without first hitting the server led to the development of peer-to-peer (P2P) computing. P2P computing defines a network
84、 architecture in which each computer has equivalent capabilities and responsibilities. This is in contrast to the traditional client/server network architecture, in which one or more computers are dedicated to serving th
85、e others. (This relationship is sometimes characterized as a master/slave relationship, with the central ser</p><p> P2P was an equalizing concept. In the P2P environment, every computer is a client and a s
86、erver; there are no masters and slaves. By recognizing all computers on the network as peers, P2P enables direct exchange of resources and services. There is no need for a central server; because any computer can functio
87、n in that capacity when called on to do so.</p><p> P2P was also a decentralizing concept. Control is decentralized, with all computers functioning as equals. Content is also dispersed among the various pee
88、r computers. No centralized server is assigned to host the available resources and services.</p><p> Perhaps the most notable implementation of P2P computing is the Internet. Many of today’s users forget (o
89、r never knew) that the Internet was initially conceived, under its original ARPAnet guise, as a peer-to-peer system that would share computing resources across the United States. The various ARPAnet sites—and there weren
90、’t many of them—were connected together not as clients and servers, but as equals.</p><p> The P2P nature of the early Internet was best exemplified by the Usenet network. Usenet, which was created back in
91、1979, was a network of computers (accessed via the Internet), each of which hosted the entire contents of the network. Messages were propagated between the peer computers; users connecting to any single Usenet server had
92、 access to all (or substantially all) the messages posted to each individual server. Although the users’ connection to the Usenet server was of the traditional clien</p><p> That said, not every part of the
93、 Internet is P2P in nature. With the development of the World Wide Web came a shift away from P2P back to the client/server model. On the web, each website is served up by a group of computers, and sites’ visitors use cl
94、ient software (web browsers) to access it. Almost all content is centralized, all control is centralized, and the clients have no autonomy or control in the process.</p><p> Distributed Computing: Providing
95、 More Computing Power</p><p> One of the most important subsets of the P2P model is that of distributed computing, where idle PCs across a network or across the Internet are tapped to provide computing powe
96、r for large, processor-intensive projects. It’s a simple concept, all about cycle sharing between multiple computers.</p><p> A personal computer, running full-out 24 hours a day, 7 days a week, is capable
97、of tremendous computing power. Most people don’t use their computers 24/7, however, so a good portion of a computer’s resources go unused. Distributed computing uses those resources.</p><p> When a computer
98、 is enlisted for a distributed computing project, software is installed on the machine to run various processing activities during those periods when the PC is typically unused. The results of that spare-time processing
99、are periodically uploaded to the distributed computing network, and combined with similar results from other PCs in the project. The result, if enough computers are involved, simulates the processing power of much larger
100、 mainframes and supercomputers—which is neces</p><p> For example, genetic research requires vast amounts of computing power. Left to traditional means, it might take years to solve essential mathematical p
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