Parameter Estimation Using Consensus Building Strategies with Application to Sensor Networks

PDF Version Also Available for Download.

Description

Sensor network plays a significant role in determining the performance of network inference tasks. A wireless sensor network with a large number of sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in WSN is developing an efficient protocol which has a significant impact on the convergence of the network. Parameter estimation is one of the most important applications of sensor network. In order to model such large and complex networks for estimation, efficient strategies and algorithms which take less time to converge are being developed. To deal with ... continued below

Creation Information

Dasgupta, Kaushani December 2013.

Context

This thesis is part of the collection entitled: UNT Theses and Dissertations and was provided by UNT Libraries to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 73 times . More information about this thesis can be viewed below.

Who

People and organizations associated with either the creation of this thesis or its content.

Chairs

Publisher

Rights Holder

For guidance see Citations, Rights, Re-Use.

  • Dasgupta, Kaushani

Provided By

UNT Libraries

With locations on the Denton campus of the University of North Texas and one in Dallas, UNT Libraries serves the school and the community by providing access to physical and online collections; The Portal to Texas History and UNT Digital Libraries; academic research, and much, much more.

Contact Us

What

Descriptive information to help identify this thesis. Follow the links below to find similar items on the Digital Library.

Degree Information

Description

Sensor network plays a significant role in determining the performance of network inference tasks. A wireless sensor network with a large number of sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in WSN is developing an efficient protocol which has a significant impact on the convergence of the network. Parameter estimation is one of the most important applications of sensor network. In order to model such large and complex networks for estimation, efficient strategies and algorithms which take less time to converge are being developed. To deal with this challenge, an approach of having multilayer network structure to estimate parameter and reach convergence in less time is estimated by comparing it with known gossip distributed algorithm. Approached Multicast multilayer algorithm on a network structure of Gaussian mixture model with two components to estimate parameters were compared and simulated with gossip algorithm. Both the algorithms were compared based on the number of iterations the algorithms took to reach convergence by using Expectation Maximization Algorithm.Finally a series of theoretical and practical results that explicitly showed that Multicast works better than gossip in large and complex networks for estimation in consensus building strategies.

Language

Collections

This thesis is part of the following collection of related materials.

UNT Theses and Dissertations

Theses and dissertations represent a wealth of scholarly and artistic content created by masters and doctoral students in the degree-seeking process. Some ETDs in this collection are restricted to use by the UNT community.

What responsibilities do I have when using this thesis?

When

Dates and time periods associated with this thesis.

Creation Date

  • December 2013

Added to The UNT Digital Library

  • Nov. 8, 2014, 11:56 a.m.

Description Last Updated

  • Nov. 16, 2016, 2:34 p.m.

Usage Statistics

When was this thesis last used?

Yesterday: 0
Past 30 days: 1
Total Uses: 73

Interact With This Thesis

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Dasgupta, Kaushani. Parameter Estimation Using Consensus Building Strategies with Application to Sensor Networks, thesis, December 2013; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc407815/: accessed October 19, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .