Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. In this book, we explore how bio-inspired methods can solve different problems linked to computer networks.Future networks are expected to be autonomous, scalable and adaptive. During millions of years of evolution, nature has developed a number of different systems that present these and other characteristics required for the next generation networks. Indeed, a series of bio-inspired methods have been successfully used to solve the most diverse problems linked to computer networks. This book presents some of these techniques from a theoretical and practical point of view. - Discusses the key concepts of bio-inspired networking to aid you in finding efficient networking solutions - Delivers examples of techniques both in theoretical concepts and practical applications - Helps you apply nature's dynamic resource and task management to your computer networks

Seeking new methods to satisfy increasing communication demands, researchers continue to find inspiration from the complex systems found in nature. From ant-inspired allocation to a swarm algorithm derived from honeybees, Bio-Inspired Computing and Networking explains how the study of biological systems can significantly improve computing, networki

Bio-inspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. Bio-Inspired Computation in Telecommunications reviews the latest developments in bio-inspired computation from both theory and application as they relate to telecommunications and image processing, providing a complete resource that analyzes and discusses the latest and future trends in research directions. Written by recognized experts, this is a must-have guide for researchers, telecommunication engineers, computer scientists and PhD students.

Biologically Inspired Networking and Sensing: Algorithms and Architectures offers current perspectives and trends in biologically inspired networking, exploring various approaches aimed at improving network paradigms. Research contained within this compendium of research papers and surveys introduces researches in the fields of communication networks, performance modeling, and distributed computing to new advances in networking.

The mystique of biologically inspired (or bioinspired) paradigms is their ability to describe and solve complex relationships from intrinsically very simple initial conditions and with little or no knowledge of the search space. Edited by two prominent, well-respected researchers, the Handbook of Bioinspired Algorithms and Applications reveals the

"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.

"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.

This book includes selected papers from the 5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2021), held in Coimbatore, India, during November 25–26, 2021. This book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. It also contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

Self-Organization in Sensor and Actor Networks explores self-organization mechanisms and methodologies concerning the efficient coordination between intercommunicating autonomous systems.Self-organization is often referred to as the multitude of algorithms and methods that organise the global behaviour of a system based on inter-system communication. Studies of self-organization in natural systems first took off in the 1960s. In technology, such approaches have become a hot research topic over the last 4-5 years with emphasis upon management and control in communication networks, and especially in resource-constrained sensor and actor networks. In the area of ad hoc networks new solutions have been discovered that imitate the properties of self-organization. Some algorithms for on-demand communication and coordination, including data-centric networking, are well-known examples. Key features include: Detailed treatment of self-organization, mobile sensor and actor networks, coordination between autonomous systems, and bio-inspired networking. Overview of the basic methodologies for self-organization, a comparison to central and hierarchical control, and classification of algorithms and techniques in sensor and actor networks. Explanation of medium access control, ad hoc routing, data-centric networking, synchronization, and task allocation issues. Introduction to swarm intelligence, artificial immune system, molecular information exchange. Numerous examples and application scenarios to illustrate the theory. Self-Organization in Sensor and Actor Networks will prove essential reading for students of computer science and related fields; researchers working in the area of massively distributed systems, sensor networks, self-organization, and bio-inspired networking will also find this reference useful.

Honey bee colonies demonstrate robust adaptive efficient agent-based communications and task allocations without centralized controls – desirable features in network design. This book introduces a multipath routing algorithm for packet-switched telecommunication networks based on techniques observed in bee colonies. The algorithm, BeeHive, is dynamic, simple, efficient, robust and flexible, and it represents an important step towards intelligent networks that optimally manage resources. The author guides the reader in a survey of nature-inspired routing protocols and communication techniques observed in insect colonies. He then offers the design of a scalable framework for nature-inspired routing algorithms, and he examines a practical application using real networks of Linux routers. He also utilizes formal techniques to analytically model the performance of nature-inspired routing algorithms. In the last chapters of the book, he introduces an immune-inspired security framework for nature-inspired algorithms, and uses the wisdom of the hive for routing in ad hoc and sensor networks. Finally, the author provides a comprehensive bibliography to serve as a reference for nature-inspired solutions to networking problems. This book bridges the gap between natural computing and computer networking. What sets this book apart from other texts on this subject is its natural engineering approach in which the challenges and objectives of a real-world system are identified before its solution, nature-inspired or otherwise, is discussed. This balanced exposition of the book makes it equally suitable for telecommunication network designers and theorists, and computer science researchers engaged with artificial intelligence, agents, and nature-inspired techniques.