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"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.
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
This book presents nature inspired computing applications for the wireless sensor network (WSN). Although the use of WSN is increasing rapidly, it has a number of limitations in the context of battery issue, distraction, low communication speed, and security. This means there is a need for innovative intelligent algorithms to address these issues.The book is divided into three sections and also includes an introductory chapter providing an overview of WSN and its various applications and algorithms as well as the associated challenges. Section 1 describes bio-inspired optimization algorithms, such as genetic algorithms (GA), artificial neural networks (ANN) and artificial immune systems (AIS) in the contexts of fault analysis and diagnosis, and traffic management. Section 2 highlights swarm optimization techniques, such as African buffalo optimization (ABO), particle swarm optimization (PSO), and modified swarm intelligence technique for solving the problems of routing, network parameters optimization, and energy estimation. Lastly, Section 3 explores multi-objective optimization techniques using GA, PSO, ANN, teaching–learning-based optimization (TLBO), and combinations of the algorithms presented. As such, the book provides efficient and optimal solutions for WSN problems based on nature-inspired algorithms.
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.
"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.
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.
In current digital era, information is an important asset for our daily life as well as for small and large-scale businesses. The network technologies are the main enablers that connect the computing devices and resources together to collect, process and share vital information locally as well as globally. The network technologies provide efficient, flexible and seamless communication while maximizing productivity and resources for our day-to-day lives and business operations. For all its importance, this domain has evolved drastically, from the traditional wired networks to Bluetooth, infrared-waves, micro-waves, radio-waves and satellite networks. Nowadays, network technologies are not only restricted to computer laboratories, offices or homes; many other diverse areas have been witnessed where network technologies are being used based on the applications and needs, such as vehicular ad-hoc networks, underwater networks, and the Internet of Things. Along with the hardware-based and physical network technologies, a lot of research has been carried out by researchers from academia and industry to develop emerging software-based network technologies, such as network software architectures, middleware, and protocol stacks. The software-based network technologies become the main driving force behind the paradigm shift in this domain and have invented many new network technologies such as grid computing, cloud computing, fog computing, edge computing, software defined networks, content centric networks and so on. On the other hand, a lot of efforts have been made in cellular network technologies to improve the user experience and as a consequence, emerging cellular network technologies like LTE, VoLTE and 5G have been invented. Due to its demand and importance in present and future scenarios, numerous efforts have been done in the networking domain by the researchers, a lot of work is still ongoing, and many more possibilities have yet to be explored. Therefore, there is a need to keep track of advancements related to the network technologies and further investigate several ongoing research challenges for the ease of users. With this goal in mind, Research Advances in Network Technologies presents the most recent and notable research on network technologies.
Cognitive networks can dynamically adapt their operational parameters in response to user needs or changing environmental conditions. They can learn from these adaptations and exploit knowledge to make future decisions. Cognitive networks are the future, and they are needed simply because they enable users to focus on things other than configuring and managing networks. Without cognitive networks, the pervasive computing vision calls for every consumer to be a network technician. The applications of cognitive networks enable the vision of pervasive computing, seamless mobility, ad-hoc networks, and dynamic spectrum allocation, among others. In detail, the authors describe the main features of cognitive networks clearly indicating that cognitive network design can be applied to any type of network, being fixed or wireless. They explain why cognitive networks promise better protection against security attacks and network intruders and how such networks will benefit the service operator as well as the consumer. Cognitive Networks Explores the state-of-the-art in cognitive networks, compiling a roadmap to future research. Covers the topic of cognitive radio including semantic aspects. Presents hot topics such as biologically-inspired networking, autonomic networking, and adaptive networking. Introduces the applications of machine learning and distributed reasoning to cognitive networks. Addresses cross-layer design and optimization. Discusses security and intrusion detection in cognitive networks. Cognitive Networks is essential reading for advanced students, researchers, as well as practitioners interested in cognitive & wireless networks, pervasive computing, distributed learning, seamless mobility, and self-governed networks. With forewords by Joseph Mitola III as well as Sudhir Dixit.
As technology continues to become more sophisticated, mimicking natural processes and phenomena becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Algorithms for Big Data Frameworks is a collection of innovative research on the methods and applications of extracting meaningful information from data using algorithms that are capable of handling the constraints of processing time, memory usage, and the dynamic and unstructured nature of data. Highlighting a range of topics including genetic algorithms, data classification, and wireless sensor networks, this book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the application of nature and biologically inspired algorithms for handling challenges posed by big data in diverse environments.