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\textsf{\itshape{GuiGen}} is a comprehensive set of tools for creating customized graphical user interfaces (GUIs). It draws from the concept of computing portals, which are here seen as interfaces to application-specific computing services for user communities. While \textsf{\itshape{GuiGen}} was originally designed for the use in computational grids, it can be used in client/server environments as well. Compared to other GUI generators, \textsf{\itshape{GuiGen}} is more versatile and more portable. It can be employed in many different application domains and on different target platforms. With \textsf{\itshape{GuiGen}}, application experts (rather than computer scientists) are able to create their own individually tailored GUIs.
Global grid environments do not only provide massive aggregated computing power but also an unprecedented amount of distributed storage space. Unfortunately, dynamic changes caused by component failures, local decisions, and irregular data updates make it difficult to efficiently use this capacity. In this paper, we address the problem of improving data availability in the presence of unreliable components. We present an analytical model for determining an optimal combination of distributed replica catalogs, catalog sizes, and replica servers. Empirical simulation results confirm the accuracy of our theoretical analysis. Our model captures the characteristics of highly dynamic environments like peer-to-peer networks, but it can also be applied to more centralized, less dynamic grid environments like the European {\em DataGrid}.
Achieving efficient many-to-many communication on a given network topology is a challenging task when many data streams from different sources have to be scattered concurrently to many destinations with low variance in arrival times. In such scenarios, it is critical to saturate but not to congest the bisectional bandwidth of the network topology in order to achieve a good aggregate throughput. When there are many concurrent point-to-point connections, the communication pattern needs to be dynamically scheduled in a fine-grained manner to avoid network congestion (links, switches), overload in the node’s incoming links, and receive buffer overflow. Motivated by the use case of the Compressed Baryonic Matter experiment (CBM), we study the performance and variance of such communication patterns on a Cray XC40 with different routing schemes and scheduling approaches. We present a distributed Data Flow Scheduler (DFS) that reduces the variance of arrival times from all sources at least 30 times and increases the achieved aggregate bandwidth by up to 50%.