Please use this identifier to cite or link to this item: https://idr.l3.nitk.ac.in/jspui/handle/123456789/10233
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dc.contributor.authorRathod, V.
dc.contributor.authorJeppu, N.
dc.contributor.authorSastry, S.
dc.contributor.authorSingala, S.
dc.contributor.authorTahiliani, M.P.
dc.date.accessioned2020-03-31T08:18:46Z-
dc.date.available2020-03-31T08:18:46Z-
dc.date.issued2019
dc.identifier.citationFuture Generation Computer Systems, 2019, Vol.100, , pp.1053-1072en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/10233-
dc.description.abstractIn this paper, we propose a new congestion control algorithm called CoCoA++ to address the issue of network congestion in Internet of Things (IoT). Unlike the existing congestion control mechanisms that operate on instantaneous Round Trip Time (RTT) measurements in IoT, we use delay gradients to get a better measure of network congestion, and implement a probabilistic backoff to deal with congestion. We integrate the delay gradients and the probability backoff factor with Constrained Application Protocol (CoAP). The proposed algorithm is implemented and evaluated using the Cooja network simulator provided by Contiki OS. Subsequently, it is deployed and evaluated in a real testbed by using the FIT/IoT-LAB. We observe that delay gradients give a more accurate measure of congestion and the Retransmission Time Out (RTO) is reduced significantly, thereby leading to less delays and high packet sending rates. CoCoA++ being a minor improvement over the existing algorithm is easy to deploy. 2019 Elsevier B.V.en_US
dc.titleCoCoA++: Delay gradient based congestion control for Internet of Thingsen_US
dc.typeArticleen_US
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