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Congestion control for 6LoWPAN wirel...

Al-Kashoash, Hayder.

Congestion control for 6LoWPAN wireless sensor networkstoward the internet of things /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Congestion control for 6LoWPAN wireless sensor networksby Hayder Al-Kashoash.
Reminder of title:	toward the internet of things /
Author:	Al-Kashoash, Hayder.
Published:	Cham :Springer International Publishing :2020.
Description:	xxxi, 159 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Internet of things.
Online resource:	https://doi.org/10.1007/978-3-030-17732-4
ISBN:	9783030177324$q(electronic bk.)

Congestion control for 6LoWPAN wireless sensor networkstoward the internet of things /
Al-Kashoash, Hayder.

Congestion control for 6LoWPAN wireless sensor networkstoward the internet of things /[electronic resource] :by Hayder Al-Kashoash. - Cham :Springer International Publishing :2020. - xxxi, 159 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Literature Review -- Comprehensive Congestion Analysis for 6LoWPANs -- Congestion-Aware Routing Protocol for 6LoWPANs -- Game Theory Based Congestion Control Framework -- Optimization Based Hybrid Congestion Alleviation -- Conclusions and Future Work.

The Internet of Things (IoT) is the next big challenge for the research community. The IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is considered a key part of the IoT. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects. This book presents a concrete, solid and logically ordered work on congestion control for 6LoWPAN networks as a step toward successful implementation of the IoT and supporting the IoT application requirements. The book addresses the congestion control issue in 6LoWPAN networks and presents a comprehensive literature review on congestion control for WSNs and 6LoWPAN networks. An extensive congestion analysis and assessment for 6LoWPAN networks is explored through analytical modelling, simulations and real experiments. A number of congestion control mechanisms and algorithms are proposed to mitigate and solve the congestion problem in 6LoWPAN networks by using and utilizing the non-cooperative game theory, multi-attribute decision making and network utility maximization framework. The proposed algorithms are aware of node priorities and application priorities to support the IoT application requirements and improve network performance in terms of throughput, end-to-end delay, energy consumption, number of lost packets and weighted fairness index.

ISBN: 9783030177324$q(electronic bk.)

Standard No.: 10.1007/978-3-030-17732-4doiSubjects--Topical Terms:

670954
Internet of things.

LC Class. No.: TK5105.8857 / .A453 2020

Dewey Class. No.: 004.678

Congestion control for 6LoWPAN wireless sensor networkstoward the internet of things /
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520 $a The Internet of Things (IoT) is the next big challenge for the research community. The IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is considered a key part of the IoT. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects. This book presents a concrete, solid and logically ordered work on congestion control for 6LoWPAN networks as a step toward successful implementation of the IoT and supporting the IoT application requirements. The book addresses the congestion control issue in 6LoWPAN networks and presents a comprehensive literature review on congestion control for WSNs and 6LoWPAN networks. An extensive congestion analysis and assessment for 6LoWPAN networks is explored through analytical modelling, simulations and real experiments. A number of congestion control mechanisms and algorithms are proposed to mitigate and solve the congestion problem in 6LoWPAN networks by using and utilizing the non-cooperative game theory, multi-attribute decision making and network utility maximization framework. The proposed algorithms are aware of node priorities and application priorities to support the IoT application requirements and improve network performance in terms of throughput, end-to-end delay, energy consumption, number of lost packets and weighted fairness index.
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