Conference Papers

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Subject: search.filters.subject.Internet of things (IoT)

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    HTmRPL++ : A Trust-Aware RPL Routing Protocol for Fog Enabled Internet of Things
    (Institute of Electrical and Electronics Engineers Inc., 2020) Subramanian, N.; Mitra, S.; Martin, J.P.; Chandrasekaran, K.
    With the proliferation of Fog computing, computation is moved to edge devices and is not based on a purely centralized approach. In a Fog computing network, the network topology is dynamic. New nodes will join and leave. One of the major issues in Fog computing is trust. Trust is the level of assurance that an object will behave in a satisfactory manner. The Routing Protocol for Low Power and Lossy Networks (RPL) is a protocol used for routing in IoT networks. RPL provides meager protection against routing or other forms of attacks. The resource-constrained nature of Fog nodes prevents the use of heavyweight cryptographic algorithms to achieve secured communication. A lightweight mechanism is thus essential to impart security in Fog-IoT networks. Trust analysis provides a behavior-based analysis of entities in the system with the power to predict future behavior. In this paper, a lightweight Recommendation based Trust Mechanism is proposed to impart security to RPL. © 2020 IEEE.
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    Enhancing Disaster Preparedness in Mountainous Regions: A Review of IoT and Machine Learning Techniques
    (Springer Science and Business Media Deutschland GmbH, 2025) Varun Menon, O.; Kolathayar, S.
    This paper presents an extensive examination of contemporary methodologies, encompassing the integration of sensor networks within the framework of the Internet of Things (IoT) and the utilization of diverse machine learning (ML) techniques, including both statistical and image processing methodologies. These innovative approaches are employed with the specific aim of enhancing hazard preparedness and establishing early warning systems for catastrophic events, such as earthquakes and landslides, in the mountainous regions of India. The study places a significant emphasis on a comprehensive review of prior research endeavors, which collectively contribute to the progressive advancement of the field of geotechnical engineering. By exploring this interdisciplinary terrain, the research endeavors to bridge the gap between traditional geotechnical engineering and the cutting-edge application of IoT and machine learning methods. This comprehensive review holds substantial potential for prospective engineers and policymakers, offering valuable insights and guidance. The objective is to support the pursuit of the United Nations’ Sustainable Development Goals (SDGs), ultimately fostering a secure and sustainable societal development trajectory. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.