Enterprises increasingly need to develop distributed systems in an agile manner, with minimal perturbation to end users and at lower costs. This paper discusses architectural design options and principles to address integration challenges. It includes a comprehensive table for evaluating relevant technologies.

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In the modern world, two powerful forces are at absolute odds: system complexity is increasing while budgets are tightening. It seems clear that, in order to manage this state of affairs, we must look for new and different ways to do things rather than just making incremental improvements on the old ways. Data-centric middleware provides that opportunity by enabling a fundamental step forward in efficiency for designing, developing, and deploying next generation, distributed mission-critical systems.

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This paper presents a comprehensive overview of the Data Distribution Service standard (DDS) and describes its benefits for developing robust precision assembly applications. DDS is a platform-independent standard released by the Object Management Group (OMG) for data-centric publish-subscribe systems. It allows decoupled applications to transfer information, regardless of what architecture, programming language or operating system they use.

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The growing popularity of cheap and widespread data collection “edge” devices and the easy access to communication networks (both wired and wireless) is weaving in more devices and systems into the fabric of our daily lives. As computation and storage costs continue to drop faster than network costs, the trend is to move data and computation locally, using data distribution technology to move data between the nodes as and when needed. As a result, the quantity of data, the scale of its distribution and the complexity integration is growing at a rapid pace.

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