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Optimization in Multi-radio Multi-ch...

Zhou, Lei.

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Optimization in Multi-radio Multi-channel Wireless Networks with Directional Antennas.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimization in Multi-radio Multi-channel Wireless Networks with Directional Antennas./
Author:	Zhou, Lei.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	74 p.
Notes:	Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Contained By:	Dissertation Abstracts International79-11B(E).
Subject:	Computer engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10808237
ISBN:	9780438124752

Optimization in Multi-radio Multi-channel Wireless Networks with Directional Antennas.
Zhou, Lei.

Optimization in Multi-radio Multi-channel Wireless Networks with Directional Antennas. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 74 p.

Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.

Thesis (Ph.D.)--Illinois Institute of Technology, 2018.

In this thesis throughput optimal and delay minimization problems are discussed in multi-radio multi-channel (MRMC) wireless networks with directional antennas (DR). As for throughput optimal problem, we adopt a multi dimensional conflict graph (MDCG) in MRMC-DR network under protocol interference model, using the concept of Link-Radio-Antenna-Channel tuple links, to facilitate mapping the original MRMC-DA network into a simple virtual single-radio single-channel (SRSC) network, on which the capacity optimization problem can be formulated as a linear program. To circumvent searching the exponentially many independent sets, we apply the delayed column generation (DCG) method to design our algorithm. On the other hand, with regard to delay minimization problem, we present a minimum length schedule (MLS) to minimize end-to-end delay while satisfying required demand. A tuple-based model is applied to help address this problem, and a more realistic model--physical interference model is adopted here to better present interference relationships between wireless links. DCG is also used here to avoid going through all independent sets, and different strategies have been raised to address situations with fixed transmission rate or variable transmission rate. Moreover, both routing and scheduling can be jointly achieved by searching for optimal solutions of our problem formulation.

ISBN: 9780438124752Subjects--Topical Terms:

621879
Computer engineering.

Optimization in Multi-radio Multi-channel Wireless Networks with Directional Antennas.
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300 $a 74 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
500 $a Adviser: Yu Cheng.
502 $a Thesis (Ph.D.)--Illinois Institute of Technology, 2018.
520 $a In this thesis throughput optimal and delay minimization problems are discussed in multi-radio multi-channel (MRMC) wireless networks with directional antennas (DR). As for throughput optimal problem, we adopt a multi dimensional conflict graph (MDCG) in MRMC-DR network under protocol interference model, using the concept of Link-Radio-Antenna-Channel tuple links, to facilitate mapping the original MRMC-DA network into a simple virtual single-radio single-channel (SRSC) network, on which the capacity optimization problem can be formulated as a linear program. To circumvent searching the exponentially many independent sets, we apply the delayed column generation (DCG) method to design our algorithm. On the other hand, with regard to delay minimization problem, we present a minimum length schedule (MLS) to minimize end-to-end delay while satisfying required demand. A tuple-based model is applied to help address this problem, and a more realistic model--physical interference model is adopted here to better present interference relationships between wireless links. DCG is also used here to avoid going through all independent sets, and different strategies have been raised to address situations with fixed transmission rate or variable transmission rate. Moreover, both routing and scheduling can be jointly achieved by searching for optimal solutions of our problem formulation.
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