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Über dieses Buch

This book provides a Mathematical Theory of Distributed Sensor Networks. It introduces the Mathematical & Computational Structure by discussing what they are, their applications and how they differ from traditional systems. It also explains how mathematics are utilized to provide efficient techniques implementing effective coverage, deployment, transmission, data processing, signal processing, and data protection within distributed sensor networks. Finally, it discusses some important challenges facing mathematics to get more incite to the multidisciplinary area of distributed sensor networks. -This book will help design engineers to set up WSN-based applications providing better use of resources while optimizing processing costs. -This book is highly useful for graduate students starting their first steps in research to apprehend new approaches and understand the mathematics behind them and face promising challenges. -This book aims at presenting a formal framework allowing to show how mathematical theories can be used to provide distributed sensor modeling and to solve important problems such as coverage hole detection and repair. -This book aims at presenting the current state of the art in formal issues related to sensor networking. It can be used as a handbook for different classes at the graduate level and the undergraduate level. It is self contained and comprehensive, presenting a complete picture of the discipline of optical network engineering including modeling functions, controlling quality of service, allocation resources, monitoring traffic, protecting infrastructure, and conducting planning. This book addresses a large set of theoretical aspects. It is designed for specialists in ad hoc and wireless sensor networks and does not include discusses on very promising areas such as homotopy, computational geometry, and wavelet transforms.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction to Distributed Sensor Networks

Currently, detection and tracking systems use a large number of different types of sensors. Because of the relatively low cost of sensors, many duplicate sensors of the same type are used to insure increased fault tolerance. The common practice is to assign each sensor of sensor cluster to handle on specific task. For example, while tracking multiple target, one sensor cluster is assigned to track one target only and any information it may collect about other targets is not utilized.
Sitharama S. Iyengar, Kianoosh G. Boroojeni, N. Balakrishnan

Erratum to: Expectation–Maximization for Acoustic Source Localization

Sitharama S. Iyengar, Kianoosh G. Boroojeni, N. Balakrishnan

Optimization Methods

Frontmatter

Chapter 2. Region-Guarding Problem in 3-D Areas

This chapter studies the optimal inspection of autonomous robots in a complex pipeline system. We solve a 3-D region-guarding problem to suggest the necessary inspection spots. The proposed hierarchical integer linear programming (HILP) optimization algorithm seeks the fewest spots necessary to cover the entire given 3-D region. Unlike most existing pipeline inspection systems that focus on designing mobility and control of the explore robots, this chapter focuses on global planning of the thorough and automatic inspection of a complex environment. We demonstrate the efficacy of the computation framework using a simulated environment, where scanned pipelines and existing leaks, clogs, and deformation can be thoroughly detected by an autonomous prototype robot.
Sitharama S. Iyengar, Kianoosh G. Boroojeni, N. Balakrishnan

Chapter 3. Expectation–Maximization for Acoustic Source Localization

Wideband source localization using acoustic sensor networks has been drawing a lot of research interest recently. The maximum likelihood (ML) is the predominant objective which leads to a variety of source localization approaches. However, the robust and efficient optimization algorithms are still being pursuit by researchers since different aspects about the effectiveness of such algorithms have to be addressed on different circumstances.
Sitharama S. Iyengar, Kianoosh G. Boroojeni, N. Balakrishnan

Coverage Problems

Frontmatter

Chapter 4. Coordinate-Free Coverage in Sensor Networks via Homology

We introduce tools from computational homology to verify coverage in an idealized sensor network. Our methods are unique in that, while they are coordinate-free and assume no localization or orientation capabilities for the nodes, there are also no probabilistic assumptions. The key ingredient is the theory of homology from algebraic topology. We demonstrate the robustness of these tools by adapting them to a variety of settings, including static planar coverage, 3-D barrier coverage, and time-dependent sweeping coverage. We also give results on hole repair, error tolerance, optimal coverage, and variable radii. An overview of implementation is given.
Sitharama S. Iyengar, Kianoosh G. Boroojeni, N. Balakrishnan

Chapter 5. Coverage Assessment and Target Tracking in 3D Domains

Recent advances in integrated electronic devices motivated the use of wireless sensor networks (WSNs) in many applications including domain surveillance and mobile target tracking, where a number of sensors are scattered within a sensitive region to detect the presence of intruders and forward related events to some analysis center(s).
Sitharama S. Iyengar, Kianoosh G. Boroojeni, N. Balakrishnan

Security Issues

Frontmatter

Chapter 6. A Stochastic Preserving Scheme of Location Privacy

Continued advances in positioning technologies and mobile devices have increased the demand for location-based services (LBSs) in distributed sensor networks. Every LBS provider requires the sensor nodes to report their location information as the quality of service strongly depends on the information.
Sitharama S. Iyengar, Kianoosh G. Boroojeni, N. Balakrishnan

Backmatter

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