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Dissertation/Thesis Abstract

Target tracking based on extended min-max approximation with ad-hoc on-demand distance vector protocol in wireless sensor networks
by Thottikat, Vishnu K., M.S., California State University, Long Beach, 2015, 32; 1603975
Abstract (Summary)

Wireless sensor networks has been rapidly growing over the past few decades. It has its significance in many fields (e.g., recording temperature in an area, data collecting, health care monitoring etc.). One such application is tracking a target with the use of sensor networks. The problem arises when the mobile target is not following the path that is predicted. In this paper, we consider the problem of both navigation and tracking of a mobile target using Ad-Hoc On-demand Distance Vector Protocol (AODV). For this model, we propose a new approach called extended min max approximation to detect the position of the target and navigation simultaneously. In addition to it, we use semi definite programming relaxation which helps in solving this problem effectively. We here use AODV routing protocol instead of Dynamic Source Routing (DSR) and a cubic function is used to navigate the mobile sensors effectively.

Indexing (document details)
Advisor: Chang, Chin
Commitee: Ary, James, Sodagari, Shabnam
School: California State University, Long Beach
Department: Electrical Engineering
School Location: United States -- California
Source: MAI 55/02M(E), Masters Abstracts International
Subjects: Communication, Electrical engineering
Keywords: Min max approximation, Target tracking, Wireless sensors
Publication Number: 1603975
ISBN: 978-1-339-25851-5
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