Time-Predictable Embedded Software on Multi-Core Platforms

Discusses the challenges imposed by multi-core architectures in designing time-predictable embedded systems. The book then goes on to describe, in detail, a comprehensive solution to guarantee time-predictable execution on multi-core platforms. It also discusses various techniques and surveys the state-of-the-art in terms of available solutions.

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Multi-core architectures have recently gained in popularity due to their high-performance and low-power characteristics. Most modern desktop systems are now equipped with multi-core processors. Despite the wide-spread adaptation of multi-core processors in desktop systems, using such processors in embedded systems still poses several challenges. Real-time, embedded systems often need to satisfy several extra-functional constraints, such as timing. In particular, for hard real-time systems, such timing constraints are strictly enforced. Violation of these timing constraints may have serious consequences, potentially costing human lives. Therefore, static timing-analysis of hard real-time systems has emerged as a critical problem to solve.

This monograph first discusses the challenges imposed by multi-core architectures in designing time-predictable embedded systems. It goes on to describe, in detail, a comprehensive solution to guarantee time-predictable execution on multi-core platforms. It also discusses various techniques and surveys the state-of-the-art in terms of available solutions. Throughout the text, the aim is to provide a solid background on recent trends in research towards achieving time-predictability on multi-cores.

It also highlights the limitations of the state-of-the-art and discusses future research opportunities and challenges to accomplish time-predictable execution on multi-core platforms. The monograph is an ideal reference for embedded systems designers and researchers interested in having a foundation for building time-predictable software on multi-core platforms. It will also help the research community to address the existing challenges in this area.