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Integrating Mobile Agents and Distributed Sensors in Wireless Sensor Networks.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Integrating Mobile Agents and Distributed Sensors in Wireless Sensor Networks./
Author:	Zeng, Jiemin.
Description:	1 online resource (128 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 78-04(E), Section: B.
Contained By:	Dissertation Abstracts International78-04B(E).
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9781369378566

Integrating Mobile Agents and Distributed Sensors in Wireless Sensor Networks.
Zeng, Jiemin.

Integrating Mobile Agents and Distributed Sensors in Wireless Sensor Networks. - 1 online resource (128 pages)

Source: Dissertation Abstracts International, Volume: 78-04(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

As computers become more ubiquitous in the prominent phenomenon of the Internet of Things, we encounter many unique challenges in the field of wireless sensor networks. A wireless sensor network is a group of small, low powered sensors with wireless capability to communicate with each other. The goal of these sensors, also called nodes, generally is to collect some information about their environment and report it back to a base station. Depending on the nature of the nodes or the environment, they may be placed in a deterministic pattern, deployed randomly, or mobile (i.e. cars on a highway). Due to the varying nature of these types of networks, they need specialized algorithms tailored to their scenarios and optimized to make efficient use of the limited power resources of the nodes. In this report, we provide upper and lower bounds for the following six different wireless sensor network problems.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369378566Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Integrating Mobile Agents and Distributed Sensors in Wireless Sensor Networks.
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100 1 $a Zeng, Jiemin. $3 1180377
245 1 0 $a Integrating Mobile Agents and Distributed Sensors in Wireless Sensor Networks.
264 0 $c 2016
300 $a 1 online resource (128 pages)
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337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 78-04(E), Section: B.
500 $a Adviser: Jie Gao.
502 $a Thesis (Ph.D.) $c State University of New York at Stony Brook $d 2016.
504 $a Includes bibliographical references
520 $a As computers become more ubiquitous in the prominent phenomenon of the Internet of Things, we encounter many unique challenges in the field of wireless sensor networks. A wireless sensor network is a group of small, low powered sensors with wireless capability to communicate with each other. The goal of these sensors, also called nodes, generally is to collect some information about their environment and report it back to a base station. Depending on the nature of the nodes or the environment, they may be placed in a deterministic pattern, deployed randomly, or mobile (i.e. cars on a highway). Due to the varying nature of these types of networks, they need specialized algorithms tailored to their scenarios and optimized to make efficient use of the limited power resources of the nodes. In this report, we provide upper and lower bounds for the following six different wireless sensor network problems.
520 $a • Spanner on Imprecise Points: We consider the construction of a Euclidean spanner for imprecise points where we take advantage of prior, inexact knowledge of our input.
520 $a • Distributed Mobile Sensor Coverage: We consider the problem of covering a domain by mobile sensors and the design of an efficient schedule that reduces unnecessary sensor overlap and energy consumption.
520 $a • The Data Gathering Problem: A data mule tours around a sensor network and helps with network maintenance such as data collection and battery recharging/replacement. We assume that each sensor has a fixed data generation rate and a capacity (upper bound on storage size). If the data mule arrives after the storage capacity is met, additional data generated is lost. We aim to schedule a tour for the mule such that it optimally services the network.
520 $a • The Shortest Separating Cycle Problem: Given a set of pairs of points in the plane, the goal of the minimum length separating cycle problem is to find a simple tour of minimum length that separates the two points of each pair on different sides.
520 $a • r-gather Clustering: Given a set of points in Euclidean space and a value r, the aim of the r-gather problem is to cluster the points into groups of at least r points each such that the largest diameter of the clusters is minimized.
520 $a • Geographical Routing in 3D: Given a graph on vertices embedded in R3, the objective is to add the minimum number of virtual edges such that greedy routing succeeds for any source and destination pair.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
650 4 $a Applied mathematics. $3 1069907
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0364
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a State University of New York at Stony Brook. $b Computer Science. $3 1180378
773 0 $t Dissertation Abstracts International $g 78-04B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10193121 $z click for full text (PQDT)