Cloud computing is a technology that uses the internet and central remote servers to maintain data and applications. Cloud computing allows consumers and businesses to use applications without installation and access their personal files at any computer with internet access. This technology allows for much more efficient computing by centralizing storage, memory, processing and bandwidth.
A simple example of cloud computing is Yahoo email, Gmail, or Hotmail etc. You dont need a software or a server to use them. All a consumer would need is just an internet connection and you can start sending emails. The server and email management software is all on the cloud ( internet) and is totally managed by the cloud service provider Yahoo , Google etc. The consumer gets to use the software alone and enjoy the benefits. The analogy is , ‘If you need milk , would you buy a cow ?’ All the users or consumers need is to get the benefits of using the software or hardware of the computer like sending emails etc. Just to get this benefit (milk) why should a consumer buy a (cow) software /hardware ?
Cloud computing is broken down into three segments: “application” “storage” and “connectivity.” Each segment serves a different purpose and offers different products for businesses and individuals around the world. In June 2011, a study conducted by VersionOne found that 91% of senior IT professionals actually don’t know what cloud computing is and two-thirds of senior finance professionals are clear by the concept,^[1] highlighting the young nature of the technology. In Sept 2011, an Aberdeen Group study found that disciplined companies achieved on average an 68% increase in their IT expense because cloud computing and only a 10% reduction in data center power costs.^[2]


Soft Computing became a formal Computer Science area of study in early 1990s.^[1] Earlier computational approaches could model and precisely analyze only relatively simple systems. More complex systems arising in biology, medicine, the humanities, management sciences, and similar fields often remained intractable to conventional mathematical and analytical methods. That said, it should be pointed out that simplicity and complexity of systems are relative, and many conventional mathematical models have been both challenging and very productive. Soft computing deals with imprecision, uncertainty, partial truth, and approximation to achieve practicability, robustness and low solution cost. Components of soft computing include:

• Neural networks (NN)
• Fuzzy logics (FL)
• Evolutionary computation(EC), including:
  • Evolutionary algorithms
    • Genetic algorithms
    • Differential evolution
  • Metaheuristic and Swarm Intelligence
    • Ant colony optimization
    • Bees algorithms
    • Bat algorithm
    • Cuckoo search
    • Harmony search
    • Firefly algorithm
    • Artificial immune systems
    • Particle swarm optimization
• Ideas about probabilityincluding:
  • Bayesian network
• Chaos theory
• Perceptron

Generally speaking, soft computing techniques resemble biological processes more closely than traditional techniques, which are largely based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis (as in finite element analysis). Soft computing techniques are intended to complement each other.
Unlike hard computing schemes, which strive for exactness and full truth, soft computing techniques exploit the given tolerance of imprecision, partial truth, and uncertainty for a particular problem. Another common contrast comes from the observation that inductive reasoning plays a larger role in soft computing than in hard computing.


References
http://www.wikinvest.com/concept/Cloud_Computing
http://en.wikipedia.org/wiki/Soft_computing

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