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Outputs (144)

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.

Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective (2024)
Journal Article
Rathore, N., Gupta, R., Thakkar, N., Gohil, K., Tanwar, S., Aujla, G. S., Alqahtani, F., & Tolba, A. (2025). Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective. Ad Hoc Networks, 169, Article 103727. https://doi.org/10.1016/j.adhoc.2024.103727

This paper explores artificial intelligence (AI) and edge–fog interplay to strengthen healthcare informatics (HCI), while also considering the blockchain perspective for securing HCI to transform cloud-based HCI to edge–fog-based HCI to serve real-ti... Read More about Intelligent edge–fog interplay for healthcare informatics: A blockchain perspective.

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.

Towards Scalable and Secure Blockchain in Internet of Things: A Preference-Driven Committee Member Auction Consensus Approach (2024)
Journal Article
Mathur, A., Barati, M., Aujla, G. S., & Rana, O. (online). Towards Scalable and Secure Blockchain in Internet of Things: A Preference-Driven Committee Member Auction Consensus Approach. Distributed Ledger Technologies: Research and Practice, https://doi.org/10.1145/3700149

Blockchain technology is acclaimed for eliminating the need for a central authority while ensuring stability, security, and immutability. However, its integration into Internet of Things (IoT) environments is hampered by the limited computational res... Read More about Towards Scalable and Secure Blockchain in Internet of Things: A Preference-Driven Committee Member Auction Consensus Approach.

Two-fold Strategy Towards Sustainable Renewable Energy Networks When Uncertainty is Certain (2024)
Journal Article
Garg, A., Singh, A., Singh Aujla, G., & Sun, H. (online). Two-fold Strategy Towards Sustainable Renewable Energy Networks When Uncertainty is Certain. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/TCE.2024.3475581

With renewable energy sources (RESs) integrated into modern power systems, energy consumers participate in the energy market making the entire network more complex and uncertain. Therefore, adaptive strategies are needed to address the various uncert... Read More about Two-fold Strategy Towards Sustainable Renewable Energy Networks When Uncertainty is Certain.