RPL*: An Explainable AI-based routing protocol for Internet of Mobile Things

dc.contributor.authorShenoy, Meetha V.
dc.date.accessioned2024-12-11T11:16:33Z
dc.date.available2024-12-11T11:16:33Z
dc.date.issued2024-10
dc.description.abstractThe Internet of Mobile Things (IoMT) is an emerging paradigm of Internet of Things (IoT) with special focus on enabling mobility to the ‘things’. Several IoMT applications such as group of robots or drones performing collaborative search and rescue operation, identification of mines, warehouse management, goods delivery, etc can be considered as examples of IoMT systems. In the applications mentioned above, the nodes may send the information in a multi-hop manner to the root or coordinator node which may be static or mobile. While the Routing Protocol for Low Power and Lossy Networks (RPL) is extensively utilized in static IoT networks, it encounters significant limitations in handling mobility and providing resilience against routing attacks in mobile IoT networks. In this work, we propose a modified RPL, RPL* which is robust to handling mobility in nodes and is resilient towards routing attacks. In RPL*, any deviation from the normal behaviors of the network are identified as anomalies using an unsupervised Explainable Artificial Intelligence (XAI) strategy. In RPL*, we propose a novel mobility detection mechanism that will identify the mobility in the network in an energy efficient manner without incurring additional communication overhead. To maintain the connectivity with parent node, we propose a novel proactive connectivity management mechanism in RPL* which will ensure a smooth transition from one parent to another if required, thus avoiding the network partitioning due to mobility. The performance analysis of the system has demonstrated an improvement in packet delivery ratio of the mobile nodes by 40% due to the proposed RPL* when compared to RPL. Also, the proposed XAI strategy provided an F1-score of over 95% for the detection of sink hole and black hole attacks in the tested IoMT network scenarios. It was observed that RPL* improves the performance of the IoMT network when compared to RPL. However it may be noted that the mechanisms introduced to support mobility does not lead to a drop in PDR or increase in control packet overhead for static networks. Hence, RPL* can be considered as an alternative to RPL for IoT as well as IoMT networks.en_US
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S2542660524002245?via%3Dihub
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16581
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectEEEen_US
dc.subjectInternet of Things (IoT)en_US
dc.subjectInternet of Mobile Things (IoMT)en_US
dc.subjectRoutingen_US
dc.subjectAnomalyen_US
dc.subjectMachine learning (ML)en_US
dc.titleRPL*: An Explainable AI-based routing protocol for Internet of Mobile Thingsen_US
dc.typeArticleen_US

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