Abstract
Take a second to consider all the essential services and utilities we consume and pay for on a usage basis: water, gas, electricity. In the distant past, some people have suggested that computing be treated under the same model as most other utility providers. The case could certainly be made. For instance, a company that supports its own computing infrastructure may suffer from the costs of equipment, labor, maintenance, and mounting energy bills. It would be more cost-effective if the company paid some third-party provider for its storage and processing requirements based on time and usage. While it made perfect sense from the client’s perspective, the overhead of becoming a computingas-a-utility provider was prohibitive until recently. Through advancements in virtualization and the ability to leverage existing supercomputing capacities, utility computing is finally becoming realized. Known to most as cloud computing, leaders, such as Amazon Elastic Compute Cloud (EC2), Azure, Cloudera, and Google’s App Engine, have already begun offering utility computing to the mainstream. A simple, but interesting property in utility models is elasticity, that is, the ability to stretch and contract services directly according to the consumer’s needs. Elasticity has become an essential expectation of all utility providers. When’s the last time you plugged in a toaster oven and worried about it not working because the power company might have run out of power? Sure, it’s one more device that sucks up power, but you’re willing to eat the cost. Likewise, if you switch to using a more efficient refrigerator, you would expect the provider to charge you less on your next billing cycle. What elasticity means to cloud users is that they should design their applications to scale their resource requirements up and down whenever possible. However, this is not as easy as plugging or unplugging a toaster oven.
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