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.
Dr Hayder Al-Kashoash is a Lecturer at Southern Technical University (STU), Basra, Iraq. He received his Bachelor degree and Master degree in Computer Engineering from University of Basra, Iraq and his PhD degree in Electronic and Electrical Engineering from The University of Leeds, UK. He received The FW Carter Prize for writing the best doctoral thesis of the year 2017-2018 in the School of Electronic and Electrical Engineering, The University of Leeds, UK. He was awarded the Iraqi Prime Minister Office Scholarship to pursue the PhD degree. Throughout his undergraduate degree, he graduated first in his school and third in his Faculty and was also the recipient of first student award in his faculty of the year 2006-2007. He has authored more than 11 journal and conference papers and reviewed more than 10 journal papers. His current research interests include congestion control and resource management in WSNs, 6LoWPAN, and LPWAN by utilizing game theory and optimization theory.
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.