Chapter 13Conclusions

In this book, we presented novel methods for modeling and optimization of parallel and distributed embedded systems. We illustrated our modeling and optimization of distributed embedded systems using our research and experimental evaluation, which focused on distributed embedded wireless sensor networks (EWSNs). Specifically, we developed and tested our dynamic optimization methodologies on an embedded senor node's tunable parameter value settings for EWSNs and modeled application metrics, such as lifetime and reliability. We demonstrated our modeling and optimization methods for parallel embedded systems using our research on multicore-based parallel embedded systems.

Chapter 1 introduced the modeling and optimization of embedded systems and further discussed various diverse embedded system application domains including cyber-physical systems (CPSs), space, medical, and automotive. The chapter presented an overview of modeling, modeling objectives, and various modeling paradigms.

Chapter 2 presented our proposed architecture for heterogeneous hierarchical multicore embedded wireless sensor networks (MCEWSNs). The increased computation power afforded by multicore embedded sensor nodes benefits a myriad of compute-intensive tasks, such as information fusion, encryption, network coding, and software-defined radio, which are prevalent in many application domains. MCEWSNs are especially beneficial for wireless sensor networking application domains, such as ...

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