Autonomic Networking-On-Chip: Bio-Inspired Specification, Development, and Verification (Hardcover) (ISBN-13: 9781439829110)

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 "BioChipNets"

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:

• Bio-inspired NoC
• 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 "self-" 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.