Finally, we study a typical heterogeneous network, Wireless Biomedical Sensor Network (WBSN), as it consists of various types of biosensors to monitor different physiological parameters. WBSN will help to enhance medical services with its unique advantages in long-term monitoring, easy network deployment, wireless connections, and ambulatory capabilities. (Abstract shortened by UMI.) / Secondly, for the purpose of providing geographical information for the topology management, we investigate the problem of power adaptive localization based on received signal strength (RSS), aiming at tackling the problem of inconsistent signal strength observation caused by tuning power levels. We propose a localization algorithm based on the particle filtering technique for sensor networks assisted by multiple transmission power levels. As a result, the novel contribution in this part is to intelligently incorporate changing transmission power levels into the particle filtering process as dynamic evidences and make an accurate localization. The proposed particle filtering technique based localization algorithm effectively circumvents the inconsistent observations under different power settings. It picks up the information of RSS from the beacons or the neighboring nodes to infer position information, without requiring additional instrumentation. We then evaluate the power adaptive localization algorithm via simulation studies and the results indicate that the proposed algorithm outperforms the algorithm of iterative least-square estimation, which does not utilize multiple power levels. In addition, we proposed a particle-filtering localization based on the acoustic asymmetric patterns of the acoustic sensors. As a result, the proposed particle filter based localization algorithms can facilitate the topology management in heterogeneous sensor networks. / We start by formulating the problem of topology optimization in the context of game theory and then analyze the equilibrium resulted from the decentralized interactions between the heterogeneous sensors. Majority of the existing topology control approaches require a centralized controller to obtain a global network graph and formulate the issue as a problem of transmission range assignment. The centralized algorithms are inapplicable for large-scale sensor networks due to the heavy communication overhead. In addition, these algorithms rarely consider the cross-layer consequences of the power adjustment, such as the quality of received signals at physical layer, the network connectivity, and the spatial reuse at network layer. Considering the aforementioned cross-layer interactive effects caused by power scheduling, we study the utility function that balances the physical layer link quality characterized by the frame success rate and the network layer robustness characterized by K-connectivity, while minimizing the power consumption. We prove the existence of the Nash equilibrium for complete-information game formulation. Because the heterogeneous sensors typically react to neighboring environment based on local information and the states of sensors are evolving over time, the power-scheduling problem in WHSN is further formulated into a more realistic incomplete-information dynamic game model. We then analyze the separating equilibrium, one of the perfect Bayesian equilibriums resulted from the dynamic game, with the sensors revealing their operational states from the actions. The sufficient and necessary conditions of the separating equilibrium existence are derived for the dynamic Bayesian game, which provide theoretical basis to the proposed power scheduling algorithms. / Wireless Heterogeneous Sensor Network (WHSN) is constructed from various sensor nodes with diverse capabilities in sensing units, transmission power levels, and energy resources, among a few others. The primary objective of the research reported in this thesis is to address the problem of power efficient topology optimization in WHSN, which is a much more complicated issue for network reliability, compared with homogeneous wireless sensor network (WSN). Two fundamental problems of topology management are addressed in this thesis: power scheduling based topology control and power adaptive localization. Distributed power scheduling offers an efficient way for the dynamic construction of network topology to meet its connectivity and reliability requirements. Power adaptive localization provides geographical information for topology management during the process of power adjustment. / Ren, Hongliang. / "February 2008." / Adviser: Qing-Hu Max Meng. / Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 4944. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 140-157). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_344131 |
| Date | January 2008 |
| Contributors | Ren, Hongliang., Chinese University of Hong Kong Graduate School. Division of Electronic Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, theses |
| Format | electronic resource, microform, microfiche, 1 online resource (xiv, 157 p. : ill.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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