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Pubudu N. Pathirana
Researcher at Deakin University
Publications - 270
Citations - 6973
Pubudu N. Pathirana is an academic researcher from Deakin University. The author has contributed to research in topics: Extended Kalman filter & Kalman filter. The author has an hindex of 29, co-authored 266 publications receiving 3942 citations. Previous affiliations of Pubudu N. Pathirana include University of New South Wales & University of Oxford.
Papers
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Optimality analysis of sensor-target localization geometries
TL;DR: The aim of this work is to identify those relative sensor-target geometries which result in a measure of the uncertainty ellipse being minimized, and to show that an optimal sensor- target configuration is not, in general, unique.
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Federated Learning for Internet of Things: A Comprehensive Survey
TL;DR: In this paper, a comprehensive survey of the emerging applications of federated learning in IoT networks is provided, which explores and analyzes the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing and IoT privacy and security.
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Blockchain for Secure EHRs Sharing of Mobile Cloud Based E-Health Systems
TL;DR: A novel EHRs sharing framework that combines blockchain and the decentralized interplanetary file system (IPFS) on a mobile cloud platform is proposed that provides an effective solution for reliable data exchanges on mobile clouds while preserving sensitive health information against potential threats.
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6G Internet of Things: A Comprehensive Survey
Dinh C. Nguyen,Ming Ding,Pubudu N. Pathirana,Aruna Seneviratne,Jun Li,Dusit Niyato,Octavia A. Dobre,H. Vincent Poor +7 more
TL;DR: In this paper, the authors explore the emerging opportunities brought by 6G technologies in IoT networks and applications, by conducting a holistic survey on the convergence of 6G and IoT, and highlight interesting research challenges and point out potential directions to spur further research in this promising area.
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Node localization using mobile robots in delay-tolerant sensor networks
TL;DR: The key idea in this scheme is to use this robot to perform location estimation for the sensor nodes it passes based on the signal strength of the radio messages received from them, which eliminates the processing constraints of static sensor nodes and the need for static reference beacons.