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Outputs (69)

Automated Artificial Intelligence Framework for Anomaly Detection in Healthcare SD-IoT Networks (2025)
Presentation / Conference Contribution
Algamdi, H., Aujla, G. S., Singh, A., Jindal, A., & Trehan, A. (2024, December). Automated Artificial Intelligence Framework for Anomaly Detection in Healthcare SD-IoT Networks. Presented at GLOBECOM 2024 - 2024 IEEE Global Communications Conference, Cape Town, South Africa

In healthcare IoT networks, network anomalies can disrupt the flow of reliable data, potentially compromising healthcare data's security and integrity. To address this challenge, several anomaly detection methods have been developed using artificial... Read More about Automated Artificial Intelligence Framework for Anomaly Detection in Healthcare SD-IoT Networks.

COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks (2025)
Presentation / Conference Contribution
Singh Aujla, G., Jindal, A., Kaur, K., Garg, S., Chaudhary, R., Sun, H., & Kumar, N. (2025, June). COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

To mitigate various challenges in the edge-cloud ecosystem, such as global monitoring, flow control, and policy modification of legacy networking paradigms, software-defined networks (SDN) have evolved as a major technology. However, the dependency o... Read More about COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks.

Optimizing UAV-Assisted Vehicular Edge Computing With Age of Information: A SAC-Based Solution (2025)
Journal Article
Goudarzi, S., Soleymani, S. A., Anisi, M. H., Jindal, A., & Xiao, P. (2025). Optimizing UAV-Assisted Vehicular Edge Computing With Age of Information: A SAC-Based Solution. IEEE Internet of Things Journal, 12(5), 4555-4569. https://doi.org/10.1109/jiot.2025.3529836

Edge computing improves the Internet of Vehicles (IoV) by offloading heavy computations from in-vehicle devices to high-capacity edge servers, typically roadside units (RSUs), to ensure rapid response times for intensive and latency-sensitive tasks.... Read More about Optimizing UAV-Assisted Vehicular Edge Computing With Age of Information: A SAC-Based Solution.

CIDER: Cyber‐Security in Industrial IoT Using Deep Learning and Ring Learning with Errors (2025)
Journal Article
Tsoi, S. T., & Jindal, A. (2025). CIDER: Cyber‐Security in Industrial IoT Using Deep Learning and Ring Learning with Errors. IET Cyber-Physical Systems: Theory & Applications, 10(1), Article e70015. https://doi.org/10.1049/cps2.70015

Traditional security measures such as access control and authentication need to be more effective against ever‐evolving threats. Moreover, security concerns increase as more industries shift towards adopting the industrial Internet of things (IIoT).... Read More about CIDER: Cyber‐Security in Industrial IoT Using Deep Learning and Ring Learning with Errors.

Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum (2024)
Presentation / Conference Contribution
Dua, A., Singh Aujla, G., Jindal, A., & Sun, H. (2024, December). Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum. Presented at IEEE Global Communications Conference - Workshop on Next-Gen Healthcare Fusion (NgHF): AI-driven Secure Integrated Networks for Healthcare IoT Systems, Cape Town, South Africa

The increasing demand for machine learning (ML) technologies has led to a significant rise in energy consumption and environmental impact, particularly within the context of distributed computing environments like the Edge-Fog-Cloud Continuum. This p... Read More about Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum.

A Vision of 6G URLLC: Physical-Layer Technologies and Enablers (2024)
Journal Article
Pourkabirian, A., Kordafshari, M. S., Jindal, A., & Anisi, M. H. (2024). A Vision of 6G URLLC: Physical-Layer Technologies and Enablers. IEEE Communications Standards Magazine, 8(2), 20-27. https://doi.org/10.1109/mcomstd.0003.2300018

The anticipated advent of 6G communication holds the promise of enabling mission-critical applications such as traffic detection, forest fire recognition, emergency search and rescue, and widespread communication broadcasting. To fulfill these servic... Read More about A Vision of 6G URLLC: Physical-Layer Technologies and Enablers.

Big Data Analytics: Theory, Techniques, Platforms, and Applications (2024)
Book
Demirbaga, Ü., Aujla, G. S., Jindal, A., & Kalyon, O. (2024). Big Data Analytics: Theory, Techniques, Platforms, and Applications. Springer Nature. https://doi.org/10.1007/978-3-031-55639-5

This book introduces readers to big data analytics. It covers the background to and the concepts of big data, big data analytics, and cloud computing, along with the process of setting up, configuring, and getting familiar with the big data analytics... Read More about Big Data Analytics: Theory, Techniques, Platforms, and Applications.

Smart Multimodal In-Bed Pose Estimation Framework Incorporating Generative Adversarial Neural Network (2024)
Journal Article
Singh, S., Anisi, M. H., Jindal, A., & Jarchi, D. (2024). Smart Multimodal In-Bed Pose Estimation Framework Incorporating Generative Adversarial Neural Network. IEEE Journal of Biomedical and Health Informatics, 28(6), 3379 - 3388. https://doi.org/10.1109/jbhi.2024.3384453

Monitoring in-bed pose estimation based on the Internet of Medical Things (IoMT) and ambient technology has a significant impact on many applications such as sleep-related disorders including obstructive sleep apnea syndrome, assessment of sleep qual... Read More about Smart Multimodal In-Bed Pose Estimation Framework Incorporating Generative Adversarial Neural Network.

A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control (2024)
Presentation / Conference Contribution
Khanam, Z., Achari, V., Boukhennoufa, I., Jindal, A., & Singh, A. K. (2024, January). A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control. Presented at Workshop on Next Generation Real-Time Embedded Systems (NG-RES), Munich, Germany

Traffic congestion is one of the growing urban problem with associated problems like fuel wastage, loss of lives, and slow productivity. The existing traffic system uses programming logic control (PLC) with round-robin scheduling algorithm. Recent wo... Read More about A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control.