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Cloud computing has generally involved the use of specialist data centres to support computation and data storage at a central site (or a limited number of sites). The motivation for this has come from the need to provide economies of scale (and subsequent reduction in cost) for supporting large scale computation for multiple user applications over (generally) a shared, multi-tenancy infrastructure...
The use of in-silico simulations in experimental science can greatly increase laboratory efficiency and provide additional insights into interactions not easily described by traditional methods. Such simulations require significant amounts of computational resources, accessible only via supercomputers of large-scale high-performance clusters. Due to the complexity of the computational experiments,...
Coordination of multiple concurrent data stream processing, carried out through a distributed Cloud infrastructure, is described. The coordination (control) is carried out through the use of a Reference net (a particular type of Petri net) based interpreter, implemented alongside the Comet Cloud system. One of the benefits of this approach is that the model can also be executed directly to support...
With increasing availability of instrumented infrastructures in built environments, it is necessary to understand how such data will be stored, processed and analysed in a timely manner. Many "smart cities" applications, for instance, identify how data from building sensors can be combined together to support applications such as emergency response, energy management, etc. Enabling sensor...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.