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Distributed pervasive systems have been employed in a wide spectrum of applications, from environmental monitoring, to emergency response. These systems have very strong coordination requirements and are hard to design. Their development becomes even more complex if we consider that they need to be able to adapt to the frequent changes that can occur in the execution environment, or in the resources available to the system. We present A-3, a model and a self-organizing distributed middleware for designing and implementing high-volume and highly volatile distributed systems. It focuses on the coordination needs of such systems, yet it also provides designers with a clear view of where they can include control loops, and how they can coordinate them for global management. We have evaluated A-3 on an example in which we want to increase the efficiency and safety of staff and patients in a health-care environment using an RFID-based distributed surveillance system. The experiments we present evaluate the scalability, performance, and robustness of our middleware, and compare it with two plausible alternatives: a completely centralized solution, and a decentralized one based on Lime, a well-known distributed tuple space framework. We ascertain that, with A-3, a system can avoid overloading its elements by distributing the communication load, and that this can be achieved autonomously, regardless of the size of the system itself.