Localization in underwater sensor networks / Jing Yan, Haiyan Zhao, Yuan Meng, Xinping Guan.
2021
TK7872.D48 Y36 2021
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Details
Title
Localization in underwater sensor networks / Jing Yan, Haiyan Zhao, Yuan Meng, Xinping Guan.
Author
Yan, Jing, author.
ISBN
9789811648311 (electronic bk.)
981164831X (electronic bk.)
9789811648304
9811648301
981164831X (electronic bk.)
9789811648304
9811648301
Published
Singapore : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource (xvii, 220 pages) : illustrations (some color)
Item Number
10.1007/978-981-16-4831-1 doi
Call Number
TK7872.D48 Y36 2021
Dewey Decimal Classification
006.2/5
Summary
Ocean covers 70.8% of the Earths surface, and it plays an important role in supporting all life on Earth. Nonetheless, more than 80% of the oceans volume remains unmapped, unobserved and unexplored. In this regard, Underwater Sensor Networks (USNs), which offer ubiquitous computation, efficient communication and reliable control, are emerging as a promising solution to understand and explore the ocean. In order to support the application of USNs, accurate position information from sensor nodes is required to correctly analyze and interpret the data sampled. However, the openness and weak communication characteristics of USNs make underwater localization much more challenging in comparison to terrestrial sensor networks. In this book, we focus on the localization problem in USNs, taking into account the unique characteristics of the underwater environment. This problem is of considerable importance, since fundamental guidance on the design and analysis of USN localization is very limited at present. To this end, we first introduce the network architecture of USNs and briefly review previous approaches to the localization of USNs. Then, the asynchronous clock, node mobility, stratification effect, privacy preserving and attack detection are considered respectively and corresponding localization schemes are developed. Lastly, the books rich implications provide guidance on the design of future USN localization schemes. The results in this book reveal from a system perspective that underwater localization accuracy is closely related to the communication protocol and optimization estimator. Researchers, scientists and engineers in the field of USNs can benefit greatly from this book, which provides a wealth of information, useful methods and practical algorithms to help understand and explore the ocean.
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Includes bibliographical references.
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text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed November 5, 2021).
Series
Wireless networks (Springer (Firm)) 2366-1445
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Localization in underwater sensor networks.
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Table of Contents
Introduction
Asynchronous localization of underwater sensor networks with mobility prediction
Async-localization of USNs with consensus-based unscented Kalman filtering
Reinforcement learning-based asynchronous localization of USNs
Privacy preserving asynchronous localization of USNs
Privacy-preserving asynchronous localization with attack detection and ray compensation
Deep reinforcement learning based privacy preserving localization of USNs
Future research directions.
Asynchronous localization of underwater sensor networks with mobility prediction
Async-localization of USNs with consensus-based unscented Kalman filtering
Reinforcement learning-based asynchronous localization of USNs
Privacy preserving asynchronous localization of USNs
Privacy-preserving asynchronous localization with attack detection and ray compensation
Deep reinforcement learning based privacy preserving localization of USNs
Future research directions.