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The success of cloud computing can lead to large, centralized collections of virtual machine (VM) images. The ability to interactively search these VM images at a high semantic level emerges as an important capability. This paper examines the opportunities and challenges in creating such a search capability, and presents early evidence of its feasibility.
In this paper the motivation, design and application of a distributed blackboard architecture for interactive data visualization is discussed. The main advantages of the architecture are twofold. First, it allows visualization tools to be tightly integrated with simulations. Second, it allows qualitative and quantitative analysis to be combined during the visualization process.
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.