Autonomic Networking-on-Chip: Bio-Inspired Specification, Development, and Verification By Phan Cong-Vinh
2011 | 270 Pages | ISBN: 143982911X | PDF | 5 MB
Despite the growing mainstream importance and unique advantages of autonomic networking-on-chip (ANoC) technology, Autonomic Networking-On-Chip: Bio-Inspired Specification, Development, and Verification is among the first books to evaluate research results on formalizing this emerging NoC paradigm, which was inspired by the human nervous system.
The FIRST Book to Assess Research Results, Opportunities, & Trends in 揃ioChipNets?br />The third book in the Embedded Multi-Core Systems series from CRC Press, this is an advanced technical guide and reference composed of contributions from prominent researchers in industry and academia around the world. A response to the critical need for a global information exchange and dialogue, it is written for engineers, scientists, practitioners, and other researchers who have a basic understanding of NoC and are now ready to learn how to specify, develop, and verify ANoC using rigorous approaches.
Offers Expert Insights Into Technical Topics Including:
How to map applications onto ANoC
ANoC for FPGAs and structured ASICs
Methods to apply formal methods in ANoC development
Ways to formalize languages that enable ANoC
Methods to validate and verify techniques for ANoC
Use of 搒elf-?processes in ANoC (self-organization, configuration, healing, optimization, protection, etc.)
Use of calculi for reasoning about context awareness and programming models in ANoC
With illustrative figures to simplify contents and enhance understanding, this resource contains original, peer-reviewed chapters reporting on new developments and opportunities, emerging trends, and open research problems of interest to both the autonomic computing and network-on-chip communities. Coverage includes state-of-the-art ANoC architectures, protocols, technologies, and applications. This volume thoroughly explores the theory behind ANoC to illustrate strategies that enable readers to use formal ANoC methods yet still make sound judgments and allow for reasonable justifications in practice.
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