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Outputs (6)

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.

T-BLAST: Token-Based Leveraging of Autonomous Spectrum Trading (2025)
Presentation / Conference Contribution
Singh, M., Bjorndahl, W., Aujla, G., & Camp, J. (2025, May). T-BLAST: Token-Based Leveraging of Autonomous Spectrum Trading. Presented at IEEE International Symposium on Dynamic Spectrum Access Networks, London

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.

Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems (2025)
Presentation / Conference Contribution
Demirbaga, U., Singh Aujla, G., & Sun, H. (2025, June). Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

As the scale of data continues to grow exponentially, managing resource allocation and energy consumption in big data systems becomes increasingly complex and critical. Moreover, with big data systems, energy efficiency is more important daily. In cl... Read More about Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems.