By Eduardo Martins Guerra, Ednelson Oliveira (auth.), Zaigham Mahmood (eds.)
This e-book provides either state of the art examine advancements and useful advice on methods, applied sciences and frameworks for the rising cloud paradigm. issues and contours: provides the cutting-edge in cloud applied sciences, infrastructures, and repair supply and deployment types; discusses correct theoretical frameworks, useful methods and urged methodologies; bargains tips and top practices for the improvement of cloud-based companies and infrastructures, and examines administration elements of cloud computing; reports buyer views on cellular cloud computing and cloud-based firm source making plans; explores software program functionality trying out, open-source cloudware help, and evaluation methodologies for modernization, migration and pre-migration; describes rising new methodologies suitable to the cloud paradigm, and offers feedback for destiny advancements and study directions.
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Additional resources for Cloud Computing: Methods and Practical Approaches
Example text
The concept of metadata piece can vary with the context and with the metadata definition strategy. For instance, if code annotations are being used, the metadata piece can be a single annotation. As another example, if metadata is defined in an XML document, a metadata piece can be an XML element. 5 presents an example of how an annotation can be associated to its delegate metadata reader. M. Guerra and E. Oliveira «interface» ProcessingLayer +executeLayer() * 1 FrameworkController +execute() access MetadataContainer use «singleton» Repository ConcreteProcessingLayer +executeLayer() access +getInstance() +getMetadata() Fig.
Within science, scalability is an important need since the instruments capable of producing massive amounts of data have emerged. These instruments capture a variety of observations generating copious amounts of data, be it remote observations of Mars, in situ ground sensors measuring greenhouse gases, or information related to feedback loops for oil and gas drilling areas. These measurements and the instruments that take them require highly scalable data-intensive systems, which capture, generate, manage, and distribute data to the worldwide scientific community.
If the image is not stored on a local file system, the image data has to be transferred from a remote machine, thus adding a dependency on network bandwidth. To work around these limitations, the image has to be broken up into smaller parts. This process is called image tiling and building a tile pyramid. The goal is to create small image tiles, typically a few hundred pixels high and wide (512×512 in 2 Architecting Scientific Data Systems in the Cloud 37 Fig. 5 Hybrid use of private and cloud infrastructure in LMMP LMMP), and to send those tiles to the client as needed depending on the location and the zoom level that the client is viewing.