1 Department of Informatics and Mathematical Modeling, Technical University of Denmark2 Embedded Systems Engineering, Department of Informatics and Mathematical Modeling, Technical University of Denmark3 Copenhagen Center for Health Technology, Center, Technical University of Denmark
The first part of the thesis presents an overview of the existing theories and practices of modeling and simulation of multiprocessor systems-on-chip. The systematic categorization of the plethora of existing programming models at various levels of abstraction is the main contribution here which is the first such attempt in the published literature. The second part of the thesis deals with the issues related to the development of system-level design methodologies for networked multiprocessor systems-on-chip at various levels of design abstraction with special focus on the modeling and design of wireless integrated sensor networks which are an emerging class of networked embedded computer systems. The work described here demonstrates how to model multiprocessor systems-on-chip at the system level by abstracting away most of the lower-level details albeit retaining the parameters most relevant at the system-level. The multiprocessor modeling framework is then extended to include models of networked multiprocessor systems-on-chip which is then employed to model wireless sensor networks both at the sensor node level as well as the wireless network level. In the third and the final part, the thesis covers the issues related to the design, implementation and testing of a system-on-chip-based wireless sensor node development platform, specifically, for the Hogthrob project. This part also deals with the cycle-accurate model of the multiprocessor system-on-chip and its possible extensions to the transaction-level model. The thesis, as a whole makes contributions by describing a design methodology for networked multiprocessor embedded systems at three layers of abstraction from system-level through transaction-level to the cycle accurate level as well as demonstrating it practically by implementing a wireless sensor node design.