Algorithmic Aspects of Wireless Sensor Networks

This book introduces resource-aware data fusion algorithms to gather and combine data from multiple sources (e.g., sensors) in order to achieve inferences. These techniques can be used in centralized

Topology control is fundamental to solving scalability and capacity problems in large-scale wireless ad hoc and sensor networks. Forthcoming wireless multi-hop networks such as ad hoc and sensor net

International contributors present the latest research developments in wireless sensor networks (WSNs), with chapters grouped in sections on general issues, protocols and middlewares, security and pri

This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing t

This book shows how reconfigurable hardware technology like field-programmable gate arrays (FPGAs) offer cost-effective, flexible platforms for implementing WMSNs. Offers a complete specification of a

For students, researchers, and academics, Sarkar (electronics and telecommunication engineering, Jadavpur U., India) discusses the implementation and use of wireless ad hoc and sensor networks. He cov

Although wireless sensor networks (WSNs) have been employed across a wide range of applications, there are very few books that emphasize the algorithm description, performance analysis, and applicatio

This publication represents the best thinking and solutions to a myriad of contemporary issues in wireless networks. Coverage includes wireless LANs, multihop wireless networks, and sensor networks. R

This book introduces resource-aware data fusion algorithms that generate inferences by combining data from multiple sources techniques useful in centralized and distributed systems to overcome sensor

This book aims to develop a reader’s thorough understanding of the opportunities and challenges of k-covered wireless sensor networks, where each point in a deployment field is covered (or sensed) by

Algorithmic Aspects of Graph Connectivity is the first comprehensive book on this central notion in graph and network theory, emphasizing its algorithmic aspects. Because of its wide applications in the fields of communication, transportation, and production, graph connectivity has made tremendous algorithmic progress under the influence of the theory of complexity and algorithms in modern computer science. The book contains various definitions of connectivity, including edge-connectivity and vertex-connectivity, and their ramifications, as well as related topics such as flows and cuts. The authors thoroughly discuss new concepts and algorithms that allow for quicker and more efficient computing, such as maximum adjacency ordering of vertices. Covering both basic definitions and advanced topics, this book can be used as a textbook in graduate courses in mathematical sciences, such as discrete mathematics, combinatorics, and operations research, and as a reference book for specialists i

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible, tractable models that better capture not what makes machine learning hard, but what makes it easy. Theoretical computer scientists will be introduced to important models in machine learning and to the main questions within the field. Machine learning researchers will be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method of moments, tensor decompositions and convex programming relaxations. The treatment beyond worst-case analysis is to build a rigorous understanding about the approaches used in practice and to facilitate the discovery of exciting, new ways to solve important long-standing problems.

This book bridges theoretical computer science and machine learning by exploring what the two sides can teach each other. It emphasizes the need for flexible, tractable models that better capture not what makes machine learning hard, but what makes it easy. Theoretical computer scientists will be introduced to important models in machine learning and to the main questions within the field. Machine learning researchers will be introduced to cutting-edge research in an accessible format, and gain familiarity with a modern, algorithmic toolkit, including the method of moments, tensor decompositions and convex programming relaxations. The treatment beyond worst-case analysis is to build a rigorous understanding about the approaches used in practice and to facilitate the discovery of exciting, new ways to solve important long-standing problems.

Algorithmic Aspects of Graph Connectivity is the first comprehensive book on this central notion in graph and network theory, emphasizing its algorithmic aspects. Because of its wide applications in the fields of communication, transportation, and production, graph connectivity has made tremendous algorithmic progress under the influence of the theory of complexity and algorithms in modern computer science. The book contains various definitions of connectivity, including edge-connectivity and vertex-connectivity, and their ramifications, as well as related topics such as flows and cuts. The authors thoroughly discuss new concepts and algorithms that allow for quicker and more efficient computing, such as maximum adjacency ordering of vertices. Covering both basic definitions and advanced topics, this book can be used as a textbook in graduate courses in mathematical sciences, such as discrete mathematics, combinatorics, and operations research, and as a reference book for specialists i

The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vi

The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vi

This book introduces the theoretical elements at the basis of various classes of algorithms commonly employed in the physical layer (and, in part, in MAC layer) of wireless communications systems. It

The desire for precise knowledge about the location of a moving object at any time has recently motivated a great deal of scientific research. This is owing to the steady expansion of the range of ena

Scientists and engineers in computers, information, and electronics offer a broad reference on networks of visual sensors. They cover foundations of visual information processing in wireless sensor ne

This book emphasizes the increasingly important role that Computational Intelligence (CI) methods are playing in solving a myriad of entangled Wireless Sensor Networks (WSN) related problems. The book

This book investigates the possible circuit solutions to overcome the temperature and supply voltage-sensitivity of fully-integrated time references for ultra-low-power communication in wireless senso

Wireless sensor Networks: Vehicle and Space Applications describes the practical perspectives in using wireless sensor networks (WSN) to develop real world applications that can be used for space expl

Wireless Ad Hoc and Sensor Networks: A Cross-Layer Design Perspective deals with the emerging design trend that transcends traditional communication layers for performance gains in ad hoc and sensor

A model-based approach to the design and implementation of Computational Sensor Networks (CSNs) is proposed. This high-level paradigm for the development and application of sensor device networks pro

The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sens

The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sens