Network on Chip (NoC) addresses the communication requirement of different nodes on System on Chip. The bio-inspired algorithms improve the bandwidth utilization, maximize the throughput and reduce the end-to-end latency and inter-flit arrival time. This book exclusively presents in-depth information regarding bio-inspired algorithms solving real world problems focussing on fault-tolerant algorithms inspired by the biological brain and implemented on NoC. It further documents the bio-inspired algorithms in general and more specifically, in the design of NoC. It gives an exhaustive review and analysis of the NoC architectures developed during the last decade according to various parameters. Key Features: Covers bio-inspired solutions pertaining to Network-on-Chip (NoC) design solving real world examples Includes bio-inspired NoC fault-tolerant algorithms with detail coding examples Lists fault-tolerant algorithms with detailed examples Reviews basic concepts of NoC Discusses NoC architectures developed-to-date

"Nature-inspired" includes, roughly speaking, "bio-inspired"+"physical-inspired"+"social-inspired"+ and so on. This book contains highly original contributions about how nature is going to shape networking systems of the future. Hence, it focuses on rigorous approaches and cutting-edge solutions, which encompass three classes of major methods: 1) Those that take inspiration from nature for the development of novel problem solving techniques; 2) Those that are based on the use of networks to synthesize natural phenomena; and 3) Those that employ natural materials to compute or communicate.

The field of application-specific integrated circuits (ASICs) is fast-paced being at the very forefront of modern nanoscale fabrication and presents a deeply engaging career path. ASICs can provide us with high-speed computation in the case of digital circuits. For example, central processing units, graphics processing units, field-programmable gate arrays, and custom-made digital signal processors are examples of ASICs and the transistors they are fabricated from. We can use that same technology complementary metal-oxide semiconductor processes to implement high-precision sensing of or interfacing to the world through analog-to-digital converters, digital-to-analog converters, custom image sensors, and highly integrated micron-scale sensors such as magnetometers, accelerometers, and microelectromechanical machines. ASIC technologies now transitioning toward magneto-resistive and phase-changing materials also offer digital memory capacities that have aided our technological progress. Combining these domains, we have moved toward big data analytics and the new era of artificial intelligence and machine learning. This book provides a small selection of chapters covering aspects of ASIC development and the surrounding business model.

Network on Chip (NoC) addresses the communication requirement of different nodes on System on Chip. The bio-inspired algorithms improve the bandwidth utilization, maximize the throughput and reduce the end-to-end latency and inter-flit arrival time. This book exclusively presents in-depth information regarding bio-inspired algorithms solving real world problems focussing on fault-tolerant algorithms inspired by the biological brain and implemented on NoC. It further documents the bio-inspired algorithms in general and more specifically, in the design of NoC. It gives an exhaustive review and analysis of the NoC architectures developed during the last decade according to various parameters. Key Features: Covers bio-inspired solutions pertaining to Network-on-Chip (NoC) design solving real world examples Includes bio-inspired NoC fault-tolerant algorithms with detail coding examples Lists fault-tolerant algorithms with detailed examples Reviews basic concepts of NoC Discusses NoC architectures developed-to-date

“Look deep into nature and you will understand everything better.” advised Albert Einstein. In recent years, the research communities in Computer Science, Engineering, and other disciplines have taken this message to heart, and a relatively new field of “biologically-inspired computing” has been born. Inspiration is being drawn from nature, from the behaviors of colonies of ants, of swarms of bees and even the human body. This new paradigm in computing takes many simple autonomous objects or agents and lets them jointly perform a complex task, without having the need for centralized control. In this paradigm, these simple objects interact locally with their environment using simple rules. Applications include optimization algorithms, communications networks, scheduling and decision making, supply-chain management, and robotics, to name just a few. There are many disciplines involved in making such systems work: from artificial intelligence to energy aware systems. Often these disciplines have their own field of focus, have their own conferences, or only deal with specialized s- problems (e.g. swarm intelligence, biologically inspired computation, sensor networks). The Second IFIP Conference on Biologically-Inspired Collaborative Computing aims to bridge this separation of the scientific community and bring together researchers in the fields of Organic Computing, Autonomic Computing, Self-Organizing Systems, Pervasive Computing and related areas. We are very pleased to have two very important keynote presentations: Swarm Robotics: The Coordination of Robots via Swarm Intelligence Principles by Marco Dorigo (Université Libre de Bruxelles, Belgium), of which an abstract is included in this volume.

We are very pleased to present this LNCS volume, the proceedings of the 8th InternationalConferenceonParallelProblemSolvingfromNature(PPSNVIII). PPSN is one of the most respected and highly regarded conference series in evolutionary computation and natural computing/computation. This biennial eventwas?rstheldinDortmundin1990,andtheninBrussels(1992),Jerusalem (1994), Berlin (1996), Amsterdam (1998), Paris (2000), and Granada (2002). PPSN VIII continues to be the conference of choice by researchers all over the world who value its high quality. We received a record 358 paper submissions this year. After an extensive peer review process involving more than 1100 reviews, the programme c- mittee selected the top 119 papers for inclusion in this volume and, of course, for presentation at the conference. This represents an acceptance rate of 33%. Please note that review reports with scores only but no textual comments were not considered in the chairs’ ranking decisions. The papers included in this volume cover a wide range of topics, from e- lutionary computation to swarm intelligence and from bio-inspired computing to real-world applications. They represent some of the latest and best research in evolutionary and natural computation. Following the PPSN tradition, all - persatPPSNVIII werepresentedasposters.Therewere7 sessions:eachsession consisting of around 17 papers. For each session, we covered as wide a range of topics as possible so that participants with di?erent interests would ?nd some relevant papers at every session.

This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).