The principal difference between CW and conventional systems of computation is that CW allows inclusion in the information set, I, of propositions expressed in a natural language, that is, linguistic valuations. Legalization of linguistic valuations has important implications. First, it greatly enhances the capability of computational methodologies to deal with imperfect information, that is, information which in one or more respects is imprecise, uncertain, incomplete, unreliable, vague or

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... ially true. In realistic settings, such information is the norm rather than exception. Second, in cases in which there is a tolerance for imprecision, linguistic valuations serve to exploit the tolerance for imprecision through the use of words in place of numbers. And third, linguistic valuations are close to human reasoning and thus facilitate the design of systems which have a high level of machine intelligence, that is, high level of MIQ (machine IQ). What does Computing with Words have to offer? The answer rests on two important tools which are provided by the machinery of fuzzy logic. The first tool is a formalism for mmprecisiation of propositions expressed in a natural language through representation of the meaning of a proposition as a generalized constraint of the form X isr R, where as noted earlier X is the constrained variable, R is the constraining relation and r is the modality of the constraint (Zadeh 1986). The second tool is a formalism for computing with mm-precisiated propositions through propagation and counterpropagation of generalized constraints. The principal rule governing constraint propagation is the Extension Principle (Zadeh 1965(Zadeh , 1975. In combination, these two tools provide an effective formalism for computation with information described in a natural language. And it is these tools that serve as a basis for legalization of linguistic valuations. What is important to note is that the machinery of fuzzy if-then rules-a machinery which is employed in almost all applications of fuzzy logic-is a part of the conceptual structure of CW. and the Center for the Study of Language and Information, Stanford University. His earlier work was concerned in the main with systems analysis, decision analysis and information systems. His current research is focused on fuzzy logic, computing with words and soft computing, which is a coalition of fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing and parts of machine learning. Int'l Conf. Grid Computing and Applications | GCA'10 | Lotfi doctorates. He has published extensively on a wide variety of subjects relating to the conception, design and analysis of information/intelligent systems, and is serving on the editorial boards of over sixty journals. Professor in the Abstract: Computing is being transformed to a model consisting of services that are commoditised and delivered in a manner similar to utilities such as water, electricity, gas, and telephony. In such a model, users access services based on their requirements without regard to where the services are hosted. Several computing paradigms have promised to deliver this utility computing vision and they include Grid computing, P2P computing, and more recently Cloud computing. The latter term denotes the infrastructure as a "Cloud" in which businesses and users are able to access applications from anywhere in the world on demand. Cloud computing delivers infrastructure, platform, and software (application) as services, which are made available as subscription-based services in a pay-as-you-go model to consumers. These services in industry are respectively referred to as Infrastructure as a Service (Iaas), Platform as a Service (PaaS), and Software as a Service (SaaS). To realize Cloud computing potential, vendors such as Amazon, Google, Microsoft, and IBM are starting to create and deploy Clouds in various locations around the world. In addition, companies with global operations require faster response time, and thus save time by distributing workload requests to multiple Clouds in various locations at the same time. This creates the need for establishing a computing atmosphere for dynamically interconnecting and provisioning Clouds from multiple domains within and across enterprises. There are many challenges involved in creating such Clouds and Cloud interconnections. This keynote (1) presents the 21st century vision of computing and identifies various IT paradigms promising to deliver the vision of computing utilities; (2) defines the architecture for creating market-oriented Clouds and computing atmosphere by leveraging technologies such as VMs; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new Cloud Computing initiative, called Cloudbus: (i) Aneka, a software system for providing PaaS within private or public Clouds and supporting market-oriented resource management, (ii) internetworking of Clouds for dynamic creation of federated computing environments for scaling of elastic applications, (iii) creation of 3rd party Cloud brokering services for content delivery network and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon and Nirvanix along with Grid mashups, and (iv) CloudSim supporting modelling and simulation of Clouds for performance studies; and (5) concludes with the need for convergence of competing IT paradigms for delivering our 21st century vision along with pathways for future research.