Intelligent Sampling over Wireless Sensor Networks

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Intelligent Sampling over Wireless Sensor Networks"

By

Miss Yongzhen Zhuang


Abstract

Nowadays, Wireless sensor networks (WSN) have been widely used in
environmental monitoring applications because sensors are cheap and
portable. These tiny distributed sensors provide discrete samples of
environmental parameters, for example, temperature, humidity, gas
pressure, decibel levels, and etc. Since sensors are always constrained by
their limited battery power, how to energy efficiently use a large number
of distributed sensors and their samples in an application is of great
importance. In this thesis we have presented a series of intelligent
sampling approaches. It is worthwhile to point out that sampling in sensor
networks has many interesting properties. First, sensor sampling has two
dimensions. The temporal dimension decides how many samples a sensor
should obtain. In our sampling approaches, the temporal sampling is used
to adjust the sensor sampling rates and provide required data quality
under the noisy environment. The spatial dimension distributely selects a
subset of sensors to save the sampling and transmission cost. We also find
that sensor sampling is application dependent. Different applications
(e.g. different queries, data cleaning, pattern search) usually require
different approaches to optimally use the samples and sensors. Even
different scenarios of an application (e.g. in a pattern search
application, the sensory data may have or have no spatial similarity)
affect the design of a sampling approach. This thesis includes three main
parts: (1) intelligent sampling for sum and range queries, (2) intelligent
sampling for a data cleaning application, and (3) intelligent sampling for
some specific sensor applications, such as pattern query over distributed
sensory streams and max regional aggregate query. Our extensive simulation
results demonstrate the effectiveness and efficiency of the proposed
sampling approaches in different applications.


Date:			Tuesday, 3 June 2008

Time:			9:30a.m.-11:30a.m.

Venue:			Room 3416
			Lifts 17-18

Chairman:		Prof. Howard Luong (ECE)

Committee Members:	Prof. Lei Chen (Supervisor)
			Prof. Vincent Shen
			Prof. Ke Yi
			Prof. Xiangru Zhang (CIVL)
			Prof. Jeffrey Yu (Sys. Engg. & Engg. Mgmt., CUHK)


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