The high level objective of this cluster is to build the fundamental basis of a new real-time software technology that can provide a more efficient and predictable support to the development of future embedded systems, characterized by high complexity dynamic behaviour and distributed organisation. In particular, the new software technology should:

 

• support scalability to facilitate the porting of control applications to different platforms;

• simplify the management of resources to control the growing complexity and distribution of embedded systems;

• take advantage of parallel processing platforms, such as multicores, in order to satify timing and adaptity requirements;

• be light-weight to opimize the usage of scarce resuources in tiny embedded computing devices;

• increase programming flexibility, for specifying functional and performance requirements to simplify test and verification;

• enable run-time reconfigurability and functionality updates to deal with the dynamics and ubiquitous nature of the supporting computing infrastructure;

• increase programming productivity, by raising the level of abstraction of the resource management services;

• increase system adaptivity to react to environmental changes, still providing a sufficient level of performance;

• be robust to tolerate transient and permanent overload conditions due to wrong design assumptions or unpredictable changes.

Such features would have a concrete impact on European industry to reduce time to market, and improve software reliability and testability. To support industry in such a transition phase, new tools, algorithms and kernel mechanisms must be also provided. In this respect, this cluster is playing an active role, acting as a bridge between the academic and the industrial world, especially in the domain of consumer electronics, robotics, industrial automation, telecommunications, and the so called cyber-physical systems.

A means to achieve such a goal is to develop a research platform for real-time systems to share competencies, resources, and tools targeting at the development of applications, such as control systems, with performance and timing requirements. The use of a shared platform is essential for experimenting new real-time software technology, including novel scheduling algorithms, resource management techniques, communication paradigms, energy-aware policies and overload handling approaches to increase robustness and predictability. A shared platform also facilitates the transfer of research results to industry, as it allows teaching practical knowledge of concepts and techniques. In addition, several solutions can be developed and tested in parallel in different partner sites, allowing the evaluation of the most appropriate approach for specific applications.

Specific research topics addressed in this cluster are related to operating systems and networks, with particular emphasis on scheduling and resource management, including energy-aware strategies and exploitation of parallelism in multicores.

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