Energy Efficiency And Reliability In Wireless Sensor Networks

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.

Wireless sensor networks (WSNs) are rapidly being adopted in a wide range of applications, from continuous health monitoring to automated industrial infrastructures, and soon will have a major environmental, financial and societal impact. Some of the main technical challenges in designing and deploying WSNs are meeting their communications reliability and energy consumption requirements. In order to address these two challenges, this thesis proposes new coding schemes and communication protocols, a novel paradigm for information acquisition, and the design and implementation of specific, circuits architectures. The reliability and energy efficiency trade-offs of splitting the inserted redundancy in multiple layers of the network stack are investigated through analysis and over-the-air experiments. Not only appropriate and efficient coding schemes for each layer are examined, but their interaction and synergistic functioning are explored. The energy benefits of each approach are quantified by designing a low-power custom transmitter using a 65nm TSMC process, integrating the first hardware implementation of a multi-rate forward error correction (FEC) and random linear network coding (RLNC) accelerator. In addition, a physical layer (PHY) independent partial packet reception (PPR) scheme is proposed for asymmetric networks, i.e. WSNs with a star topology, called packetized rateless algebraic consistency (PRAC). PRAC reduces the number of retransmissions by harnessing information contained in partial packets. Experiments with off-the-shelf transceivers validate our analysis results on the data reliability and energy consumption benefits of the proposed scheme. Apart from communicating information, acquiring the signals of interest can account for a significant fraction of the power consumption of a sensor node. For this reason, the thesis proposes a nonuniform sampling scheme in order to exploit the inherent compressibility and sparse structure of typical signals encountered in many WSNs. Simulations results with real datasets and an energy comparison against the state-of-the-art sampling schemes demonstrate its rate and energy efficiency advantages. Finally, the thesis studies the joint fundamental performance bounds of acquiring and transmitting sparse signals through noisy channels. An integrated source representation-to-transmission scheme, called AdaptCast, is proposed and, using rate distortion analysis, its asymptotically optimal performance is proved. Based on simulation results in the context of a health monitoring application, AdaptCast's performance benefits are demonstrated against other coding schemes and PHY architectures in terms of the provided data reliability and reconstruction distortion.

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.

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.

Provides the fundamentals, technologies, and best practices in designing, constructing and managing mission critical, energy efficient data centers Organizations in need of high-speed connectivity and nonstop systems operations depend upon data centers for a range of deployment solutions. A data center is a facility used to house computer systems and associated components, such as telecommunications and storage systems. It generally includes multiple power sources, redundant data communications connections, environmental controls (e.g., air conditioning, fire suppression) and security devices. With contributions from an international list of experts, The Data Center Handbook instructs readers to: Prepare strategic plan that includes location plan, site selection, roadmap and capacity planning Design and build "green" data centers, with mission critical and energy-efficient infrastructure Apply best practices to reduce energy consumption and carbon emissions Apply IT technologies such as cloud and virtualization Manage data centers in order to sustain operations with minimum costs Prepare and practice disaster reovery and business continuity plan The book imparts essential knowledge needed to implement data center design and construction, apply IT technologies, and continually improve data center operations.

"This book focuses on wireless sensor networks and their operation, covering topics including routing, energy efficiency and management"--

Wireless Sensor Networks (WSNs) have promising features that presents unique opportunities to observe both urban and rural environments. Unlike traditional monitoring systems, WSNs components are small, inexpensive, and easy to deploy. These characteristics of WSNs offer not only capability of monitoring wider and broader areas but also prolonging the observation time without any intervention. However, implementation of WSNs brings about its own theoretical and practical challenges particularly in regards to energy efficiency, reliability, fault tolerance, and scalability. We employ distributed algorithms as our basic tool to overcome these challenges. Distributed algorithms research has an extensive repertoire of reliable and scalable methods. Starting with these methods, we design WSN specific solutions where energy efficiency, resource limitations and unreliable communication are key concerns. We specifically target reliability and energy efficiency issues.^While reliability is studied within distributed algorithms research, common models and assumptions are not compatible with WSNs. The issue of energy efficiency is not studied at all, instead constraints such as memory limitations and execution time take precedence. We utilize "programming abstractions'' and "mobility'' approaches to provide solutions for reliability and energy efficiency problems. Through programming abstractions approach, we aspire to generate more expressive primitives simplifying the implementations of distributed algorithms. For constructing these primitives in reliable and energy efficient manners, we make use of some of the characteristics of the low power radios frequently used in WSN nodes. Mobility, more specifically mobile basestations approach, addresses the spatio-temporal features of WSNs.^We propose that relocating basestation in cooperation with WSN eliminates many challenges emerging due to the dynamic nature of data generation in applications such as tracking and detection. We present analytical discussions, discrete event simulations, as well as experimental results from WSN deployments. Our initial results indicate that our approaches have the potential of improving reliability and energy efficiency in WSN deployments.

Overview and Goals Wireless communication technologies are undergoing rapid advancements. The last few years have experienced a steep growth in research in the area of wireless sensor networks (WSNs). In WSNs, communication takes place with the help of spatially distributedautonomoussensornodesequippedtosensespeci?cinformation. WSNs, especially the ones that have gained much popularity in the recent years, are, ty- cally, ad hoc in nature and they inherit many characteristics/features of wireless ad hoc networks such as the ability for infrastructure-less setup, minimal or no reliance on network planning, and the ability of the nodes to self-organize and self-con?gure without the involvement of a centralized network manager, router, access point, or a switch. These features help to set up WSNs fast in situations where there is no existing network setup or in times when setting up a ?xed infrastructure network is considered infeasible, for example, in times of emergency or during relief - erations. WSNs ?nd a variety of applications in both the military and the civilian population worldwide such as in cases of enemy intrusion in the battle?eld, object tracking, habitat monitoring, patient monitoring, ?re detection, and so on. Even though sensor networks have emerged to be attractive and they hold great promises for our future, there are several challenges that need to be addressed. Some of the well-known challenges are attributed to issues relating to coverage and deployment, scalability, quality-of-service, size, computational power, energy ef?ciency, and security.