Biblio

Embedded systems must address a multitude of potentially conflicting design constraints such as resiliency, energy, heat, cost, performance, security, etc., all in the face of highly dynamic operational behaviors and environmental conditions. By incorporating elements of intelligence, the hope is that the resulting “smart” embedded systems will function correctly and within desired constraints in spite of highly dynamic changes in the applications and the environment, as well as in the underlying software/hardware platforms. Since terms related to “smartness” (e.g., self-awareness, self-adaptivity, and autonomy) have been used loosely in many software and hardware computing contexts, we first present a taxonomy of “self-x” terms and use this taxonomy to relate major “smart” software and hardware computing efforts. A major attribute for smart embedded systems is the notion of self-awareness that enables an embedded system to monitor its own state and behavior, as well as the external environment, so as to adapt intelligently. Toward this end, we use a System-on-Chip perspective to show how the CyberPhysical System-on-Chip (CPSoC) exemplar platform achieves self-awareness through a combination of cross-layer sensing, actuation, self-aware adaptations, and online learning. We conclude with some thoughts on open challenges and research directions.