東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Control and optimization approaches ...

Pourazarm, Sepideh.

Linked to FindBook

Google Book

Amazon

博客來

Control and optimization approaches for energy-limited systems: Applications to wireless sensor networks and battery-powered vehicles.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Control and optimization approaches for energy-limited systems: Applications to wireless sensor networks and battery-powered vehicles./
Author:	Pourazarm, Sepideh.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	253 p.
Notes:	Source: Dissertations Abstracts International, Volume: 78-09, Section: B.
Contained By:	Dissertations Abstracts International78-09B.
Subject:	Applied Mathematics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10253943
ISBN:	9781369652710

Control and optimization approaches for energy-limited systems: Applications to wireless sensor networks and battery-powered vehicles.
Pourazarm, Sepideh.

Control and optimization approaches for energy-limited systems: Applications to wireless sensor networks and battery-powered vehicles. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 253 p.

Source: Dissertations Abstracts International, Volume: 78-09, Section: B.

Thesis (Ph.D.)--Boston University, 2017.

This item must not be sold to any third party vendors.

This dissertation studies control and optimization approaches to obtain energy-efficient and reliable routing schemes for battery-powered systems in network settings. First, incorporating a non-ideal battery model, the lifetime maximization problem for static wireless sensor networks is investigated. Adopting an optimal control approach, it is shown that there exists a time-invariant optimal routing vector in a fixed topology network. Furthermore, under very mild conditions, this optimal policy is robust with respect to the battery model used. Then, the lifetime maximization problem is investigated for networks with a mobile source node. Redefining the network lifetime, two versions of the problem are studied: when there exist no prior knowledge about the source node's motion dynamics vs. when source node's trajectory is known in advance. For both cases, problems are formulated in the optimal control framework. For the former, the solution can be reduced to a sequence of nonlinear programming problems solved on line as the source node trajectory evolves. For the latter, an explicit off-line numerical solution is required. Second, the problem of routing for vehicles with limited energy through a network with inhomogeneous charging nodes is studied. The goal is to minimize the total elapsed time, including traveling and recharging time, for vehicles to reach their destinations. Adopting a game-theoretic approach, the problem is investigated from two different points of view: user-centric vs. system-centric. The former is first formulated as a mixed integer nonlinear programming problem. Then, by exploiting properties of an optimal solution, it is reduced to a lower dimensionality problem. For the latter, grouping vehicles into subflows and including the traffic congestion effects, a system-wide optimization problem is defined. Both problems are studied in a dynamic programming framework as well. Finally, the thesis quantifies the Price Of Anarchy (POA) in transportation net- works using actual traffic data. The goal is to compare the network performance under user-optimal vs. system-optimal policies. First, user equilibria flows and origin- destination demands are estimated for the Eastern Massachusetts transportation net- work using speed and capacity datasets. Then, obtaining socially-optimal flows by solving a system-centric problem, the POA is estimated.

ISBN: 9781369652710Subjects--Topical Terms:

1669109
Applied Mathematics.

Control and optimization approaches for energy-limited systems: Applications to wireless sensor networks and battery-powered vehicles.
LDR:03541nmm a2200337 4500 001 2206788
005 20190906083215.5
008 201008s2017 ||||||||||||||||| ||eng d
020 $a 9781369652710
035 $a (MiAaPQ)AAI10253943
035 $a (MiAaPQ)bu:12626
035 $a AAI10253943
040 $a MiAaPQ $c MiAaPQ
100 1 $a Pourazarm, Sepideh. $3 3433706
245 1 0 $a Control and optimization approaches for energy-limited systems: Applications to wireless sensor networks and battery-powered vehicles.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 253 p.
500 $a Source: Dissertations Abstracts International, Volume: 78-09, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Cassandras, Christos G.
502 $a Thesis (Ph.D.)--Boston University, 2017.
506 $a This item must not be sold to any third party vendors.
520 $a This dissertation studies control and optimization approaches to obtain energy-efficient and reliable routing schemes for battery-powered systems in network settings. First, incorporating a non-ideal battery model, the lifetime maximization problem for static wireless sensor networks is investigated. Adopting an optimal control approach, it is shown that there exists a time-invariant optimal routing vector in a fixed topology network. Furthermore, under very mild conditions, this optimal policy is robust with respect to the battery model used. Then, the lifetime maximization problem is investigated for networks with a mobile source node. Redefining the network lifetime, two versions of the problem are studied: when there exist no prior knowledge about the source node's motion dynamics vs. when source node's trajectory is known in advance. For both cases, problems are formulated in the optimal control framework. For the former, the solution can be reduced to a sequence of nonlinear programming problems solved on line as the source node trajectory evolves. For the latter, an explicit off-line numerical solution is required. Second, the problem of routing for vehicles with limited energy through a network with inhomogeneous charging nodes is studied. The goal is to minimize the total elapsed time, including traveling and recharging time, for vehicles to reach their destinations. Adopting a game-theoretic approach, the problem is investigated from two different points of view: user-centric vs. system-centric. The former is first formulated as a mixed integer nonlinear programming problem. Then, by exploiting properties of an optimal solution, it is reduced to a lower dimensionality problem. For the latter, grouping vehicles into subflows and including the traffic congestion effects, a system-wide optimization problem is defined. Both problems are studied in a dynamic programming framework as well. Finally, the thesis quantifies the Price Of Anarchy (POA) in transportation net- works using actual traffic data. The goal is to compare the network performance under user-optimal vs. system-optimal policies. First, user equilibria flows and origin- destination demands are estimated for the Eastern Massachusetts transportation net- work using speed and capacity datasets. Then, obtaining socially-optimal flows by solving a system-centric problem, the POA is estimated.
590 $a School code: 0017.
650 4 $a Applied Mathematics. $3 1669109
650 4 $a Engineering. $3 586835
650 4 $a Operations research. $3 547123
690 $a 0364
690 $a 0537
690 $a 0796
710 2 $a Boston University. $b Systems Engineering. $3 3276521
773 0 $t Dissertations Abstracts International $g 78-09B.
790 $a 0017
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10253943