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EFFICIENT DATA COLLECTION IN WIRELESS SENSOR NETWORKS:
MODELING AND ALGORITHMS
by
Lorenzo Rossi
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ELECTRICAL ENGINEERING)
December 2011
Copyright 2011 Lorenzo Rossi
Object Description
| Title | Efficient data collection in wireless sensor networks: modeling and algorithms |
| Author | Rossi, Lorenzo |
| Author email | lrossi@usc.edu;lorenzo.rossi@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Electrical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2011-11-26 |
| Date submitted | 2011-11-26 |
| Date approved | 2011-11-28 |
| Restricted until | 2012-05-26 |
| Date published | 2012-05-26 |
| Advisor (committee chair) | Kuo, C.-C. Jay |
| Advisor (committee member) |
Krishnamachari, Bhaskar Golubchik, Leana |
| Abstract | This dissertation focuses on data gathering for wireless sensor networks. Data gathering deals with the problem of transmitting measurements of physical phenomena from the sensor nodes to one or more sinks in the most efficient manner. It is usually the main task performed by a sensor network and therefore the main cause of energy depletion for the nodes. The research efforts presented here propose insightful models for the phenomena sampled by sensor networks with the purpose of designing more energy efficient data gathering schemes. ❧ We first focus on phenomena that can be characterized by a diffusive process. We propose to model the data via discretized diffusion partial differential equations (PDEs). The rationale is that few equation coefficient plus initial and contour conditions may have the potential to completely describe such spatio-temporal phenomena in a compact manner. We propose and study an algorithm for the in-network identification of the diffusion coefficients. Then, we adopt a spatially non stationary correlation model and we study how this impacts correlation based data gathering and, in particular, the problem of optimally placing a sink node in a sensor network region. Finally, we view each round of sensor measurements as a still image and we represent it via intensity histograms. This way, we can adopt image content analysis tools (intensity histograms matching) to analyze the data and determine which rounds of measurements are of interest to the final users. Therefore energy can be saved by transmitting only some rounds of measurements to the base station. We study the above models and the performance of data collection algorithms via analysis and experiments on synthetic and real data. |
| Keyword | digital signal processing; information theory; pattern recognition; wireless sensor networks; partial differential equations; spatially non-stationary correlations |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Rossi, Lorenzo |
| Physical access | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@lib.usc.edu |
| Archival file | uscthesesreloadpub_Volume6/etd-RossiLoren-438-1.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Repository email | cisadmin@lib.usc.edu |
| Full text | EFFICIENT DATA COLLECTION IN WIRELESS SENSOR NETWORKS: MODELING AND ALGORITHMS by Lorenzo Rossi A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (ELECTRICAL ENGINEERING) December 2011 Copyright 2011 Lorenzo Rossi |
