Distributed computing as a utility



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With the increasing maturity of distributed systems infrastructure, a number of companies are promoting the view of distributed resources as a commodity or utility, drawing the analogy between distributed resources and other utilities such as water or electricity. With this model, resources are provided by appropriate service suppliers and effectively rented rather than owned by the end user. This model applies to both physical resources and more logical services:
Physical resources such as storage and processing can be made available to networked computers, removing the need to own such resources on their own. At one end of the spectrum, a user may opt for a remote storage facility for file storage requirements (for example, for multimedia data such as photographs, music or video) and/or for backups. Similarly, this approach would enable a user to rent one or more computational nodes, either to meet their basic computing needs or indeed to perform
distributed computation. At the other end of the
spectrum, users can access sophisticated data centers (networked facilities offering access to repositories of often large volumes of data to users or organizations) or indeed computational infrastructure using the sort of services now provided by companies such as Amazon and Google. Operating system virtualization is a key enabling technology for this approach, implying that users may actually be provided with services by a virtual rather than a physical node.This offers greater flexibility to the service supplier in terms of resource management.
Software services can also be made available across the global Internet using this approach. Indeed, many companies now offer a comprehensive range of services for effective rental, including services such as email and distributed calendars. Google, for example, bundles a range of business services under the banner Google Apps [www.google.com I]. This development is enabled by agreed standards for software services, for example as provided by web services. 

The term cloud computing is used to capture this vision of computing as a utility. A cloud is defined as a set of Internet-based application, storage and computing services sufficient to support most users’ needs, thus enabling them to largely or totally dispense with local data storage and application software (see Figure ). The term also promotes a view of everything as a service, from physical or virtual infrastructure through to software, often paid for on a per-usage basis rather than purchased. Note that cloud computing reduces requirements on users’ devices, allowing very simple desktop or portable devices to access a potentially wide range of resources and services.
Clouds are generally implemented on cluster computers to provide the necessary scale and performance required by such services. A cluster computer is a set of interconnected computers that cooperate closely to provide a single, integrated high-performance computing capability. Building on projects such as the NOW (Network of Workstations) Project at Berkeley [Anderson et al. 1995, now.cs.berkeley.edu] and
Beowulf at NASA [www.beowulf.org], the trend is towards utilizing commodity hardware both for the computers and for the interconnecting networks.

Most clusters consist of commodity PCs running a standard (sometimes cut-down) version of an operating system such as Linux, interconnected by a local area network. Companies such as HP, Sun and IBM offer blade solutions. Blade servers are minimal computational elements containing for example processing and (main memory) storage capabilities. A blade system consists of a potentially large number of blade servers contained within a blade enclosure. Other elements such as power, cooling, persistent storage (disks), networking and displays, are provided either by the enclosure or through virtualized solutions (discussed in Chapter 7). Through this solution, individual blade servers can be much smaller and also cheaper to produce than commodity PCs.
The overall goal of cluster computers is to provide a range of cloud services, including high-performance computing capabilities, mass storage (for example through data centers
), and richer application services such as web search (Google, for example, relies on a massive cluster computer architecture to implement its search engine and other services).
Grid computing can also be viewed as a form of cloud computing. The terms are largely synonymous and at times ill-defined, but Grid computing can generally be viewed as a precursor to the more general paradigm of cloud computing with a bias towards support for scientific applications.

 

 

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1 Quality of service link
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3 Summary link
4 SYSTEM MODELS link
5 Introduction link

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