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With the rapid growth of technology in society, communication networks have become a heavily researched topic. Implementing these advanced systems is a challenge, however, due to the abundance of optimization problems within these networks. The use of meta-heuristic algorithms and nature-inspired computing has become a prevalent technique among researchers for solving these complex problems within communication networks. Despite its popularity, this specific computing technique lacks the appropriate amount of research that is needed for professionals to grasp a definite understanding. Nature-Inspired Computing Applications in Advanced Communication Networks is a collection of innovative research on the methods and applications of natural computation techniques and algorithms within communication systems such as wireless sensor networks, vehicular adhoc networks, and internet of things. While highlighting topics including mobile sensor deployment, routing optimization, and sleep scheduling, this book is ideally designed for researchers, network professionals, computer scientists, mathematicians, developers, scholars, educators, and students seeking to enhance their understanding of nature-inspired computing and its solutions within various advanced communication networks.
The advances in low-power electronic devices integrated with wireless communication capabilities are one of recent areas of research in the field of Wireless Sensor Networks (WSNs). One of the major challenges in WSNs is uniform and least energy dissipation while increasing the lifetime of the network. This is the first book that introduces the energy efficient wireless sensor network techniques and protocols. The text covers the theoretical as well as the practical requirements to conduct and trigger new experiments and project ideas. The advanced techniques will help in industrial problem solving for energy-hungry wireless sensor network applications.
Collecting and processing data is a necessary aspect of living in a technologically advanced society. Whether it’s monitoring events, controlling different variables, or using decision-making applications, it is important to have a system that is both inexpensive and capable of coping with high amounts of data. As the application of these networks becomes more common, it becomes imperative to evaluate their effectiveness as well as other opportunities for possible implementation in the future. Sensor Technology: Concepts, Methodologies, Tools, and Applications is a vital reference source that brings together new ways to process and monitor data and to put it to work in everything from intelligent transportation systems to healthcare to multimedia applications. It also provides inclusive coverage on the processing and applications of wireless communication, sensor networks, and mobile computing. Highlighting a range of topics such as internet of things, signal processing hardware, and wireless sensor technologies, this multi-volume book is ideally designed for research and development engineers, IT specialists, developers, graduate students, academics, and researchers.
This book constitutes the refereed proceedings of the 9th International Conference on Distributed Computing and Internet Technology, ICDCIT 2013, held in Bhubaneswar, India, in February 2013. The 40 full papers presented together with 5 invited talks in this volume were carefully reviewed and selected from 164 submissions. The papers cover various research aspects in distributed computing, internet technology, computer networks, and machine learning.
The energy efficiency paradigm is a major bottleneck for the development of wireless sensor networks (WSNs) and Internet of Things (IoT) architectures and technologies. This edited book presents comprehensive coverage of energy harvesting sources and techniques that can be used for WSN and IoT systems.
Wireless sensors and sensor networks (WSNs) are nowadays becoming increasingly important due to their decisive advantages. Different trends towards the Internet of Things (IoT), Industry 4.0 and 5G Networks address massive sensing and admit to have wireless sensors delivering measurement data directly to the Web in a reliable and easy manner. These sensors can only be supported, if sufficient energy efficiency and flexible solutions are developed for energy-aware wireless sensor nodes. In the last years, different possibilities for energy harvesting have been investigated showing a high level of maturity. This book gives therefore an overview on fundamentals and techniques for energy harvesting and energy transfer from different points of view. Different techniques and methods for energy transfer, management and energy saving on network level are reported together with selected interesting applications. The book is interesting for researchers, developers and students in the field of sensors, wireless sensors, WSNs, IoT and manifold application fields using related technologies. The book is organized in four major parts. The first part of the book introduces essential fundamentals and methods, while the second part focusses on vibration converters and hybridization. The third part is dedicated to wireless energy transfer, including both RF and inductive energy transfer. Finally, the fourth part of the book treats energy saving and management strategies. The main contents are: Essential fundamentals and methods of wireless sensors Energy harvesting from vibration Hybrid vibration energy converters Electromagnetic transducers Piezoelectric transducers Magneto-electric transducers Non-linear broadband converters Energy transfer via magnetic fields RF energy transfer Energy saving techniques Energy management strategies Energy management on network level Applications in agriculture Applications in structural health monitoring Application in power grids Prof. Dr. Olfa Kanoun is professor for measurement and sensor technology at Chemnitz university of technology. She is specialist in the field of sensors and sensor systems design.
This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intelligence and working on these topics.
Underwater wireless sensor networks (UWSN) are envisioned as an aquatic medium for a variety of applications including oceanographic data collection, disaster management or prevention, assisted navigation, attack protection, and pollution monitoring. Similar to terrestrial wireless sensor networks (WSN), UWSNs consist of sensor nodes that collect the information and pass it to a base station; however, researchers have to face many challenges in executing the network in an aquatic medium. Energy-Efficient Underwater Wireless Communications and Networking is a crucial reference source that covers existing and future possibilities of the area as well as the current challenges presented in the implementation of underwater sensor networks. While highlighting topics such as digital signal processing, underwater localization, and acoustic channel modeling, this publication is ideally designed for machine learning experts, IT specialists, government agencies, oceanic engineers, communication experts, researchers, academicians, students, and environmental agencies concerned with optimized data flow in communication network, securing assets, and mitigating security attacks.
Compared with conventional communications, cooperative communication allows multiple users in a wireless network to coordinate their packet transmissions and share each other's resources, thus achieving high-performance gain and better service coverage and reliability. Energy Efficient Cooperative Wireless Communication and Networks provides a comprehensive look at energy efficiency and system design of cooperative wireless communication. Introducing effective cooperative wireless communication schemes, the book supplies the understanding and methods required to improve energy efficiency, reliability, and end-to-end protocol designs for wireless communication systems. It explains the practical benefits and limitations of cooperative transmissions along with the associated designs of upper-layer protocols, including MAC, routing, and transport protocol. The book considers power efficiency as a main objective in cooperative communication to ensure quality-of-service (QoS) requirements. It explains how to bring the performance gain at the physical layer up to the network layer and how to allocate network resources dynamically through MAC/scheduling and routing to trade off the performance benefits of given transmissions against network costs. Because the techniques detailed in each chapter can help readers achieve energy efficiency and reliability in wireless networks, they have the potential to impact a range of industry areas, including wireless communication, wireless sensor networks, and ad hoc networks. The book includes numerous examples, best practices, and models that capture key issues in real-world applications. Along with algorithms and tips for effective design, the book supplies the understanding you will need to achieve high-performing and energy efficient wireless networks with improved service coverage and reliability.
Wireless sensor network (WSN) is an ad-hoc network technology comprising even thousands of autonomic and self-organizing nodes that combine environmental sensing, data processing, and wireless networking. The applications for sensor networks range from home and industrial environments to military uses. Unlike the traditional computer networks, a WSN is application-oriented and deployed for a specific task. WSNs are data centric, which means that messages are not send to individual nodes but to geographical locations or regions based on the data content. A WSN node is typically battery powered and characterized by extremely small size and low cost. As a result, the processing power, memory, and energy resources of an individual sensor node are limited. However, the feasibility of a WSN lies on the collaboration between the nodes. A reference WSN node comprises a Micro-Controller Unit (MCU) having few Million Instructions Per Second (MIPS) processing speed, tens of kilobytes program memory, few kilobytes data memory. In addition, the node contains a short-range radio, and a set of sensors. Supply power is typically obtained with small batteries. Assuming a target lifetime of one year using AA-size batteries, the available power budget is around 1 mW. This book covers the low-power WSNs services ranging from hardware platforms and communication protocols to network deployment, and sensor data collection and actuation. The implications of resource constraints and expected performance in terms of throughput, reliability and latency are explained. As a case study, this book presents experiments with low-energy TUTWSN technology to illustrate the possibilities and limitations of WSN applications.