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Embedded computing systems have started to carry out the key control functions in diverse domains such as telecommunications, automotive electronics, avionics and even complete industrial manufacturing lines. Traditionally, such embedded control systems have been implemented in a monolithic, centralized manner. However, distributed and parallel solutions have been steadily gaining popularity. In a distributed setup, the control task is carried out by a number of controllers distributed over the entire system and interconnected as a network by communication components such as field buses. More…mehr

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Produktbeschreibung
Embedded computing systems have started to carry out the key control functions in diverse domains such as telecommunications, automotive electronics, avionics and even complete industrial manufacturing lines. Traditionally, such embedded control systems have been implemented in a monolithic, centralized manner. However, distributed and parallel solutions have been steadily gaining popularity. In a distributed setup, the control task is carried out by a number of controllers distributed over the entire system and interconnected as a network by communication components such as field buses. More demanding local control applications require controllers based on parallel architectures or processors with dedicated co-processors. Distribution and parallelism in embedded system design increase the engineering challenges and demand new development methods and tools.

From Model-Driven Design to Resource Management for Distributed Embedded Systems contains 16 original contributions as well as 12 invited papers by distinguished invited speakers. These papers were presented at the Working Conference on Distributed and Parallel Embedded Systems (DIPES 2006), which was held in October 2006 in Braga, Portugal, and sponsored by the International Federation for Information Processing (IFIP).

This volume covers the following very timely topics: model-driven design, test and evolution of embedded systems, timing analysis and predictability, scheduling, allocation, communication and resource management in distributed real-time systems.


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