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010   $a3-030-17732-7
024 7 $a10.1007/978-3-030-17732-4
035   $a(CKB)4100000007992444
035   $a(MiAaPQ)EBC5754998
035   $a(DE-He213)978-3-030-17732-4
035   $a(PPN)235666556
035   $a(EXLCZ)994100000007992444
100   $a20190417d2020      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aCongestion Control for 6LoWPAN Wireless Sensor Networks: Toward the Internet of Things /$fby Hayder Al-Kashoash
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (182 pages)
225 1 $aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5053
311   $a3-030-17731-9 
327   $aIntroduction -- 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.
330   $aThe Internet of Things (IoT) is the next big challenge for the research community. The IPv6 over low power wireless personal area network (6LoWPAN) protocol stack is considered a key part of the IoT. In 6LoWPAN networks, heavy network traffic causes congestion which significantly degrades network performance and impacts on quality of service aspects. This book presents a concrete, solid and logically ordered work on congestion control for 6LoWPAN networks as a step toward successful implementation of the IoT and supporting the IoT application requirements. The book addresses the congestion control issue in 6LoWPAN networks and presents a comprehensive literature review on congestion control for WSNs and 6LoWPAN networks. An extensive congestion analysis and assessment for 6LoWPAN networks is explored through analytical modelling, simulations and real experiments. A number of congestion control mechanisms and algorithms are proposed to mitigate and solve the congestion problem in 6LoWPAN networks by using and utilizing the non-cooperative game theory, multi-attribute decision making and network utility maximization framework. The proposed algorithms are aware of node priorities and application priorities to support the IoT application requirements and improve network performance in terms of throughput, end-to-end delay, energy consumption, number of lost packets and weighted fairness index.
410  0$aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5053
606   $aComputer engineering
606   $aInternet of things
606   $aEmbedded computer systems
606   $aApplication software
606   $aElectrical engineering
606   $aCyber-physical systems, IoT$3https://scigraph.springernature.com/ontologies/product-market-codes/T24080
606   $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040
606   $aCommunications Engineering, Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/T24035
615  0$aComputer engineering.
615  0$aInternet of things.
615  0$aEmbedded computer systems.
615  0$aApplication software.
615  0$aElectrical engineering.
615 14$aCyber-physical systems, IoT.
615 24$aInformation Systems Applications (incl. Internet).
615 24$aCommunications Engineering, Networks.
676   $a004.678
700   $aAl-Kashoash$b Hayder$4aut$4http://id.loc.gov/vocabulary/relators/aut$01064585
906   $aBOOK
912   $a9910366611503321
996   $aCongestion Control for 6LoWPAN Wireless Sensor Networks: Toward the Internet of Things$92539296
997   $aUNINA