Abstract
The IEEE 802.15.4e standard was published in 2012 as an amendment to the Medium Access Control (MAC) protocol defined by the IEEE 802.15.4-2011 standard. The purpose of this paper is to evaluate the Timeslotted Channel Hopping (TSCH) mode of IEEE 802.15.4e in the context of IoT (Internet of Things) regarding environment and changes in application requirements. A simulation scenario of a typical domestic sensor network is designed to evaluate the TSCH mode in a dynamic environment with the presence of WiFi devices. Also are explored the upper and lower bounds in performance gain due to self-learning. The relatively recent release of such standard accounts for its lack of support in network simulators and this work implements the TSCH in the well known open-source network simulator ns-3. This work enables the preview analysis of TSCH networks, decreasing necessary resources and therefore facilitating the use of such networks for social goods such as health monitoring, The results clearly show that the presence of WiFi signals greatly degrades the IEEE 802.15.4e network performance, in terms of throughput, delay and energy consumption. When applying self-learning techniques to avoid degraded channels, the network can properly function and achieves better performance. Also, a significant decrease in delay is also achieved when adapting the slotframe size according to the number of active devices.
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