https://www.ronpub.com/ojiot/OJIOT_2017v3i1n09_Sparber.html Channel of the paper: Tommy Sparber, Carlo Alberto Boano, Salil S. Kanhere and Kay Römer: Mitigating Radio Interference in Large IoT Networks through Dynamic CCA Adjustment, Open Journal of Internet Of Things (OJIOT), 3 (1), pages 103-113, URN: urn:nbn:de:101:1-2017080613511, 2017, Special Issue: Proceedings of the International Workshop on Very Large Internet of Things (VLIoT 2017) in conjunction with the VLDB 2017 Conference in Munich, Germany. en-us https://www.ronpub.com/ojiot/OJIOT_2017v3i1n09_Sparber.html http://nbn-resolving.de/urn:nbn:de:101:1-2017080613511 The performance of low-power wireless sensor networks used to build Internet of Things applications often suffers from radio interference generated by co-located wireless devices or from jammers maliciously placed in their proximity. As IoT devices typically operate in unsupervised large-scale installations, and as radio interference is typically localized and hence affects only a portion of the nodes in the network, it is important to give low-power wireless sensors and actuators the ability to autonomously mitigate the impact of surrounding interference. In this paper we present our approach DynCCA, which dynamically adapts the clear channel assessment threshold of IoT devices to minimize the impact of malicious or unintentional interference on both network reliability and energy efficiency. First, we describe how varying the clear channel assessment threshold at run-time using only information computed locally can help to minimize the impact of unintentional interference from surrounding devices and to escape jamming attacks. We then present the design and implementation of DynCCA on top of ContikiMAC and evaluate its performance on wireless sensor nodes equipped with IEEE 802.15.4 radios. Our experimental investigation shows that the use of DynCCA in dense IoT networks can increase the packet reception rate by up to 50% and reduce the energy consumption by a factor of 4.