| 書目名稱 | Distributed Network Structure Estimation Using Consensus Methods | | 編輯 | Sai Zhang,Cihan Tepedelenlioglu,Mahesh Banavar | | 視頻video | http://file.papertrans.cn/282/281928/281928.mp4 | | 叢書名稱 | Synthesis Lectures on Communications | | 圖書封面 |  | | 描述 | The area of detection and estimation in a distributed wireless sensor network (WSN) has several applications, including military surveillance, sustainability, health monitoring, and Internet of Things (IoT). Compared with a wired centralized sensor network, a distributed WSN has many advantages including scalability and robustness to sensor node failures. In this book, we address the problem of estimating the structure of distributed WSNs. First, we provide a literature review in: (a) graph theory; (b) network area estimation; and (c) existing consensus algorithms, including average consensus and max consensus. Second, a distributed algorithm for counting the total number of nodes in a wireless sensor network with noisy communication channels is introduced. Then, a distributed network degree distribution estimation (DNDD) algorithm is described. The DNDD algorithm is based on average consensus and in-network empirical mass function estimation. Finally, a fully distributed algorithm forestimating the center and the coverage region of a wireless sensor network is described. The algorithms introduced are appropriate for most connected distributed networks. The performance of the algor | | 出版日期 | Book 2018 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01684-4 | | isbn_softcover | 978-3-031-00556-5 | | isbn_ebook | 978-3-031-01684-4Series ISSN 1932-1244 Series E-ISSN 1932-1708 | | issn_series | 1932-1244 | | copyright | Springer Nature Switzerland AG 2018 |
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