Du bist jetzt in der Rolle eines wissenschaftlichen Buchautors, der Berichte über Wirtschaftswissenschaftliche Themen schreibt. Deine Aufgabe ist es, den nachfolgenden Text unter Beibehaltung von Zahlen, Daten und Fakten zusammenzufassen. Dabei sollen wichtige Informationen erhalten bleiben. Es dürfen auch Zitate verwendet werden. Diese dann bitte entsprechend kenntlich machen. Bitte am Ende des Textes die Quelle bzw. Literatur, das heißt Autor und Erscheinungsjahr mit angeben.
Dabei beachte folgende Aspekte zum Sprachstil:
Verwende folgenden Sprachstil:

1. Sprache und Stil
- Nutzen Sie formelle und fachsprachliche Begriffe: Verwenden Sie präzise, technische und spezifische Fachterminologie, die im jeweiligen Themenbereich relevant ist.
- Vermeiden Sie umgangssprachliche Ausdrücke: Halten Sie die Sprache professionell und formal.
- Integrieren Sie anspruchsvolle und komplexe Wörter: Setzen Sie eine reichhaltige und komplexe Wortwahl ein, die zur Tiefe des Themas passt.

2. Satzstruktur
- Verwenden Sie lange und verschachtelte Sätze: Bauen Sie Sätze mit mehreren Nebensätzen, Einschüben und Verknüpfungen auf.
- Stellen Sie Kombinationen von Aussagen und Begründungen her: Sätze sollten oft eine klare Aussage und eine darauffolgende Erklärung oder Begründung enthalten.
- Achten Sie auf die Varianz in den Satzlängen: Abwechselnd lange, komplexe Sätze mit kürzeren und prägnanten Sätzen, um den Textfluss zu bewahren.

3. Ton
- Behalten Sie einen sachlichen und neutralen Ton bei: Schreiben Sie in einer Weise, die informationsorientiert und objektiv ist, und vermeiden Sie persönliche oder emotionale Formulierungen.
- Seien Sie analytisch und ideenorientiert: Vermitteln Sie klare Analysen, Informationen und Ideen auf eine methodische Weise.
- Nutzen Sie einen berichtenden Stil: Beschreiben Sie Fakten, Daten und Zusammenhänge in einer deskriptiven und faktischen Art.

4. Rhetorik und Stilmittel
- Setzen Sie Zitate und Referenzen ein: Verwenden Sie Zitate aus relevanten Quellen und Fußnoten, um Ihre Aussagen zu untermauern.
- Nutzen Sie komparative Strukturen: Vergleichen Sie verschiedene Technologien, Märkte oder Länder, um Unterschiede und Gemeinsamkeiten herauszuarbeiten.
- Strukturieren Sie mit logischen Entwicklungen: Entwickeln Sie Ihre Argumente und Ideen logisch hin zu starken, gut begründeten Schlussfolgerungen.

Hier der Text:                                                                                                                                                                                                                                                                                                       
                                                                                                                                                                                                                                                                                                                                   
 Quelle: Above the Clouds: A Berkeley View of Cloud Computing- Michael Armbrust, Armando Fox

Cloud Computing: An Old Idea Whose Time Has (Finally) Come Cloud Computing is a new term for a long-held dream of computing as a utility [35], which has recently emerged as a commercial reality. Cloud Computing is likely to have the same impact on software that foundries have had on the hardware industry. At one time, leading hardware companies required a captive semiconductor fabrication facility, and companies had to be large enough to afford to build and operate it economically. However, processing equipment doubled in price every technology generation. A semiconductor fabrication line costs over $3B today, so only a handful of major “merchant” companies with very high chip volumes, such as Intel and Samsung, can still justify owning and operating their own fabrication lines. This motivated the rise of semiconductor foundries that build chips for others, such as Taiwan Semiconductor Manufacturing Company (TSMC). Foundries enable “fab-less” semiconductor chip companies whose value is in innovative chip design: A company such as nVidia can now be successful in the chip business without the capital, operational expenses, and risks associated with owning a state-of-the-art fabrication line. Conversely, companies with fabrication lines can time-multiplex their use among the products of many fab-less companies, to lower the risk of not having enough successful products to amortize operational costs. Similarly, the advantages of the economy of scale and statistical multiplexing may ultimately lead to a handful of Cloud Computing providers who can amortize the cost of their large datacenters over the products of many “datacenter-less” companies. Cloud Computing has been talked about [10], blogged about [13, 25], written about [15, 37, 38] and been featured in the title of workshops, conferences, and even magazines. Nevertheless, confusion remains about exactly what it is and when it’s useful, causing Oracle’s CEO to vent his frustration: The interesting thing about Cloud Computing is that we’ve redefined Cloud Computing to include ev erything that we already do. . . . I don’t understand what we would do differently in the light of Cloud Computing other than change the wording of some of our ads. Larry Ellison, quoted in the Wall Street Journal, September 26, 2008 These remarks are echoed more mildly by Hewlett-Packard’s Vice President of European Software Sales: A lot of people are jumping on the [cloud] bandwagon, but I have not heard two people say the same thing about it. There are multiple definitions out there of “the cloud.” Andy Isherwood, quoted in ZDnet News, December 11, 2008 Richard Stallman, known for his advocacy of “free software”, thinks Cloud Computing is a trap for users—if applications and data are managed “in the cloud”, users might become dependent on proprietary systems whose costs will escalate or whose terms of service might be changed unilaterally and adversely: It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign. Somebody is saying this is inevitable — and whenever you hear somebody saying that, it’s very likely to be a set of businesses campaigning to make it true. Richard Stallman, quoted in The Guardian, September 29, 2008 Our goal in this paper to clarify terms, provide simple formulas to quantify comparisons between of cloud and conventional Computing, and identify the top technical and non-technical obstacles and opportunities of Cloud Com puting. Our view is shaped in part by working since 2005 in the UC Berkeley RAD Lab and in part as users of Amazon Web Services since January 2008 in conducting our research and our teaching. The RAD Lab’s research agenda is to invent technology that leverages machine learning to help automate the operation of datacenters for scalable Internet services. We spent six months brainstorming about Cloud Computing, leading to this paper that tries to answer the following questions:
What is Cloud Computing, and how is it different from previous paradigm shifts such as Software as a Service (SaaS)? • Why is Cloud Computing poised to take off now, whereas previous attempts have foundered? • What does it take to become a Cloud Computing provider, and why would a company consider becoming one? • What new opportunities are either enabled by or potential drivers of Cloud Computing? • How might we classify current Cloud Computing offerings across a spectrum, and how do the technical and business challenges differ depending on where in the spectrum a particular offering lies? • What, if any, are the new economic models enabled by Cloud Computing, and how can a service operator decide whether to move to the cloud or stay in a private datacenter? • What are the top 10 obstacles to the success of Cloud Computing—and the corresponding top 10 opportunities available for overcoming the obstacles? • What changes should be made to the design of future applications software, infrastructure software, and hard ware to match the needs and opportunities of Cloud Computing?
What is Cloud Computing?
Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the datacenters that provide those services. The services themselves have long been referred to as Software as a Service (SaaS), so we use that term. The datacenter hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the public, we call it a Public Cloud; the service being sold is Utility Computing. Current examples of public Utility Computing include Amazon Web Services, Google AppEngine, and Microsoft Azure. We use the term Private Cloud to refer to internal datacenters of a business or other organization that are not made available to the public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but does not normally include Private Clouds. We’ll generally use Cloud Computing, replacing it with one of the other terms only when clarity demands it. Figure 1 shows the roles of the people as users or providers of these layers of Cloud Computing, and we’ll use those terms to help make our arguments clear. The advantages of SaaS to both end users and service providers are well understood. Service providers enjoy greatly simplified software installation and maintenance and centralized control over versioning; end users can access the service “anytime, anywhere”, share data and collaborate more easily, and keep their data stored safely in the infrastructure. Cloud Computing does not change these arguments, but it does give more application providers the choice of deploying their product as SaaS without provisioning a datacenter: just as the emergence of semiconductor foundries gave chip companies the opportunity to design and sell chips without owning a fab, Cloud Computing allows deploying SaaS—and scaling on demand—without building or provisioning a datacenter. Analogously to how SaaS allows the user to offload some problems to the SaaS provider, the SaaS provider can now offload some of his problems to the Cloud Computing provider. From now on, we will focus on issues related to the potential SaaS Provider (Cloud User) and to the Cloud Providers, which have received less attention. We will eschew terminology such as “X as a service (XaaS)”; values of X we have seen in print include Infrastruc ture, Hardware, and Platform, but we were unable to agree even among ourselves what the precise differences among them might be.1 (We are using Endnotes instead of footnotes. Go to page 20 at the end of paper to read the notes, which have more details.) Instead, we present a simple classification of Utility Computing services in Section 5 that focuses on the tradeoffs among programmer convenience, flexibility, and portability, from both the cloud provider’s and the cloud user’s point of view. From a hardware point of view, three aspects are new in Cloud Computing [42]: 1. The illusion of infinite computing resources available on demand, thereby eliminating the need for Cloud Com puting users to plan far ahead for provisioning; 2. The elimination of an up-front commitment by Cloud users, thereby allowing companies to start small and increase hardware resources only when there is an increase in their needs; and 3. The ability to pay for use of computing resources on a short-term basis as needed (e.g., processors by the hour and storage by the day) and release them as needed, thereby rewarding conservation by letting machines and storage go when they are no longer useful.
Figure 1: Users and Providers of Cloud Computing. The benefits of SaaS to both SaaS users and SaaS providers are well documented, so we focus on Cloud Computing’s effects on Cloud Providers and SaaS Providers/Cloud users. The top level can be recursive, in that SaaS providers can also be a SaaS users. For example, a mashup provider of rental maps might be a user of the Craigslist and Google maps services. We will argue that all three are important to the technical and economic changes made possible by Cloud Com puting. Indeed, past efforts at utility computing failed, and we note that in each case one or two of these three critical characteristics were missing. For example, Intel Computing Services in 2000-2001 required negotiating a contract and longer-term use than per hour. As a successful example, Elastic Compute Cloud (EC2) from Amazon Web Services (AWS) sells 1.0-GHz x86 ISA “slices” for 10 cents per hour, and a new “slice”, or instance, can be added in 2 to 5 minutes. Amazon’s Scalable Storage Service (S3) charges $0.12 to $0.15 per gigabyte-month, with additional bandwidth charges of $0.10 to $0.15 per gigabyte to move data in to and out of AWS over the Internet. Amazon’s bet is that by statistically multiplexing multiple instances onto a single physical box, that box can be simultaneously rented to many customers who will not in general interfere with each others’ usage (see Section 7). While the attraction to Cloud Computing users (SaaS providers) is clear, who would become a Cloud Computing provider, and why? To begin with, realizing the economies of scale afforded by statistical multiplexing and bulk purchasing requires the construction of extremely large datacenters. Building, provisioning, and launching such a facility is a hundred-million-dollar undertaking. However, because of the phenomenal growth of Web services through the early 2000’s, many large Internet companies, including Amazon, eBay, Google, Microsoft and others, were already doing so. Equally important, these companies also had to develop scalable software infrastructure (such as MapReduce, the Google File System, BigTable, and Dynamo [16, 20, 14, 17]) and the operational expertise to armor their datacenters against potential physical and electronic attacks. Therefore, a necessary but not sufficient condition for a company to become a Cloud Computing provider is that it must have existing investments not only in very large datacenters, but also in large-scale software infrastructure and operational expertise required to run them. Given these conditions, a variety of factors might influence these companies to become Cloud Computing providers: 1. Make a lot of money. Although 10 cents per server-hour seems low, Table 2 summarizes James Hamilton’s estimates [23] that very large datacenters (tens of thousands of computers) can purchase hardware, network bandwidth, and power for 1/5 to 1/7 the prices offered to a medium-sized (hundreds or thousands of computers) datacenter. Further, the fixed costs of software development and deployment can be amortized over many more machines. Others estimate the price advantage as a factor of 3 to 5 [37, 10]. Thus, a sufficiently large company could leverage these economies of scale to offer a service well below the costs of a medium-sized company and still make a tidy profit. 2. Leverage existing investment. Adding Cloud Computing services on top of existing infrastructure provides a new revenue stream at (ideally) low incremental cost, helping to amortize the large investments of datacenters. Indeed, according to Werner Vogels, Amazon’s CTO, many Amazon Web Services technologies were initially developed for Amazon’s internal operations [42]. 3. Defend a franchise. As conventional server and enterprise applications embrace Cloud Computing, vendors with an established franchise in those applications would be motivated to provide a cloud option of their own. For example, Microsoft Azure provides an immediate path for migrating existing customers of Microsoft enter prise applications to a cloud environment.
4. Attack an incumbent. A company with the requisite datacenter and software resources might want to establish a beachhead in this space before a single “800 pound gorilla” emerges. Google AppEngine provides an alternative path to cloud deployment whose appeal lies in its automation of many of the scalability and load balancing features that developers might otherwise have to build for themselves. 5. Leverage customer relationships. IT service organizations such as IBM Global Services have extensive cus tomer relationships through their service offerings. Providing a branded Cloud Computing offering gives those customers an anxiety-free migration path that preserves both parties’ investments in the customer relationship. 6. Become a platform. Facebook’s initiative to enable plug-in applications is a great fit for cloud computing, as we will see, and indeed one infrastructure provider for Facebook plug-in applications is Joyent, a cloud provider. Yet Facebook’s motivation was to make their social-networking application a new development platform. Several Cloud Computing (and conventional computing) datacenters are being built in seemingly surprising loca tions, such as Quincy, Washington (Google, Microsoft, Yahoo!, and others) and San Antonio, Texas (Microsoft, US National Security Agency, others). The motivation behind choosing these locales is that the costs for electricity, cool ing, labor, property purchase costs, and taxes are geographically variable, and of these costs, electricity and cooling alone can account for a third of the costs of the datacenter. Table 3 shows the cost of electricity in different locales [10]. Physics tells us it’s easier to ship photons than electrons; that is, it’s cheaper to ship data over fiber optic cables than to ship electricity over high-voltage transmission lines. 4 Clouds in a Perfect Storm: Why Now, Not Then? Although we argue that the construction and operation of extremely large scale commodity-computer datacenters was the key necessary enabler of Cloud Computing, additional technology trends and new business models also played a key role in making it a reality this time around. Once Cloud Computing was “off the ground,” new application opportunities and usage models were discovered that would not have made sense previously. 4.1 New Technology Trends and Business Models Accompanying the emergence of Web 2.0 was a shift from “high-touch, high-margin, high-commitment” provisioning of service “low-touch, low-margin, low-commitment” self-service. For example, in Web 1.0, accepting credit card payments from strangers required a contractual arrangement with a payment processing service such as VeriSign or Authorize.net; the arrangement was part of a larger business relationship, making it onerous for an individual or a very small business to accept credit cards online. With the emergence of PayPal, however, any individual can accept credit card payments with no contract, no long-term commitment, and only modest pay-as-you-go transaction fees.
Ende Quelle: Above the Clouds: A Berkeley View of Cloud Computing- Michael Armbrust, Armando Fox