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All Outputs (177)

DRL-based Carbon Emission Optimization Method for the Vehicular Reverse Offloading System (2025)
Presentation / Conference Contribution
Tang, H., Liu, C., Liu, J., Sun, H., Jiao, P., & Wu, H. (2025, August). DRL-based Carbon Emission Optimization Method for the Vehicular Reverse Offloading System. Paper presented at IEEE/CIC International Conference on Communications in China, Shanghai, China

The rapid development of Intelligent Transportation Systems (ITS) and the Internet of Vehicles (IoV) has revolutionized transportation networks by enabling real-time communication between vehicles, road infrastructure, and cloud systems. One such adv... Read More about DRL-based Carbon Emission Optimization Method for the Vehicular Reverse Offloading System.

HYBIC: An Improved Congestion Control Algorithm for Integrated Satellite-Terrestrial Networks in 5G and Beyond Communications (2025)
Presentation / Conference Contribution
Bisu, A. A., Gallant, A., & Sun, H. (2024, October). HYBIC: An Improved Congestion Control Algorithm for Integrated Satellite-Terrestrial Networks in 5G and Beyond Communications. Presented at 2024 IEEE Future Networks World Forum (FNWF), Dubai, UAE

In this paper, we propose an improved Transmission Control Protocol (TCP) algorithm called HYBIC, building upon existing CUBIC and HYBLA algorithms. This HYBIC algorithm is designed for improving capacity utilisation and transmission rate of heteroge... Read More about HYBIC: An Improved Congestion Control Algorithm for Integrated Satellite-Terrestrial Networks in 5G and Beyond Communications.

Joint Optimization based on Two-phase GNN in RIS-and DF-assisted MISO Systems with Fine-grained Rate Demands (2025)
Journal Article
Tang, H., Zhang, J., Zhao, Z., Wu, H., Sun, H., & Jiao, P. (online). Joint Optimization based on Two-phase GNN in RIS-and DF-assisted MISO Systems with Fine-grained Rate Demands. IEEE Transactions on Wireless Communications, https://doi.org/10.1109/TWC.2025.3576298

Reconfigurable intelligent Surfaces (RIS) and half-duplex decoded and forwarded (DF) relays can collaborate to optimize wireless signal propagation in communication systems. Users typically have different rate demands and are clustered into groups in... Read More about Joint Optimization based on Two-phase GNN in RIS-and DF-assisted MISO Systems with Fine-grained Rate Demands.

Zero-Energy RIS-Assisted Communications With Noise Modulation and Interference-Based Energy Harvesting (2025)
Journal Article
Tota Khel, M., Ikhlef, A., Ding, Z., & Sun, H. (2025). Zero-Energy RIS-Assisted Communications With Noise Modulation and Interference-Based Energy Harvesting. IEEE Transactions on Green Communications and Networking, https://doi.org/10.1109/TGCN.2025.3578423

To advance towards carbon-neutrality and improve the limited performance of conventional passive wireless communications, in this paper, we investigate the integration of noise modulation with zero-energy reconfigurable intelligent surfaces (RISs). I... Read More about Zero-Energy RIS-Assisted Communications With Noise Modulation and Interference-Based Energy Harvesting.

A Scalable and Resilient Protection Framework for Hybrid Microgrids Using Zero Injection Cluster and Graph Learning (2025)
Journal Article
Goyal, A., Jiang, J., Koley, E., Ghosh, S., Harsh, P., & Sun, H. (2025). A Scalable and Resilient Protection Framework for Hybrid Microgrids Using Zero Injection Cluster and Graph Learning. Applied Energy, 391, Article 125927. https://doi.org/10.1016/j.apenergy.2025.125927

Hybrid microgrids in spite of offering a promising solution to meet rising energy demands, have not received wider acceptance by power utilities because of the complexity of their protection schemes. Real-world microgrids are highly susceptible to di... Read More about A Scalable and Resilient Protection Framework for Hybrid Microgrids Using Zero Injection Cluster and Graph Learning.

An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning (2025)
Presentation / Conference Contribution
Liu, J., Kazemtabrizi, B., Du, H., Matthews, P., & Sun, H. (2024, November). An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning. Presented at 50th Annual Conference of the IEEE Industrial Electronics Society, Chicago, USA

With the increasing integration of renewable energy sources into the power grid, accurate and reliable ultra-short-term forecasting of wind power is critical for optimizing grid stability and energy efficiency, especially for a highly dynamic and var... Read More about An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning.

Compressive Sensing in Power Engineering: A Comprehensive Survey of Theory and Applications, and a Case Study (2025)
Journal Article
Chandran, L. R., Karuppasamy, I., Nair, M. G., Sun, H., & Krishnakumari, P. K. (2025). Compressive Sensing in Power Engineering: A Comprehensive Survey of Theory and Applications, and a Case Study. Journal of Sensor and Actuator Networks, 14(2), Article 28. https://doi.org/10.3390/jsan14020028

Compressive Sensing (CS) is a transformative signal processing framework that enables sparse signal acquisition at rates below the Nyquist limit, offering substantial advantages in data efficiency and reconstruction accuracy. This survey explores the... Read More about Compressive Sensing in Power Engineering: A Comprehensive Survey of Theory and Applications, and a Case Study.

Integrated Satellite-Terrestrial Network for Smart Grid Communications in 6G Era (2025)
Presentation / Conference Contribution
Bisu, A. A., Sun, H., & Gallant, A. (2025, January). Integrated Satellite-Terrestrial Network for Smart Grid Communications in 6G Era. Presented at 2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC), University of Nevada, Las Vegas, USA

In this work, we developed and proposed a real testbed with Integrated Satellite-Terrestrial Network (ISTN) scenario. This topology was used to measure the actual parameters that were used as the Smart Grid (SG) Quality of Service (QoS) metrics. Perf... Read More about Integrated Satellite-Terrestrial Network for Smart Grid Communications in 6G Era.

Swarm Intelligence-driven Multi-objective Optimization for Microgrid Energy Management and Trading considering DERs and EVs integration: Case Studies from Green Energy Park, Morocco (2025)
Journal Article
Rochd, A., Raihani, A., Mahir, O., Kissaoui, M., Laamim, M., Lahmer, A., El-Barkouki, B., El-Qasery, M., Sun, H. J., & Guerrero, J. M. (2025). Swarm Intelligence-driven Multi-objective Optimization for Microgrid Energy Management and Trading considering DERs and EVs integration: Case Studies from Green Energy Park, Morocco. Results in engineering, 25, Article 104400. https://doi.org/10.1016/j.rineng.2025.104400

The objective of this study is to develop and validate a comprehensive multi-objective optimization approach for energy management and trading in microgrids, with a particular focus on the integration of Distributed Energy Resources (DERs) and Electr... Read More about Swarm Intelligence-driven Multi-objective Optimization for Microgrid Energy Management and Trading considering DERs and EVs integration: Case Studies from Green Energy Park, Morocco.

Scalable and Reliable Data Framework for Sensor-enabled Virtual Power Plant Digital Twin (2025)
Journal Article
Singh, A., Demirbaga, U., Singh Aujla, G., Jindal, A., Jiang, J., & Sun, H. (2025). Scalable and Reliable Data Framework for Sensor-enabled Virtual Power Plant Digital Twin. IEEE Journal of Selected Areas in Sensors, 2, 108-120. https://doi.org/10.1109/JSAS.2025.3540956

Sensor-enabled distributed energy resources (DERs) provide various advantages, including a lower carbon footprint, yet effective management of millions of DERs is still an issue. Virtual power plants (VPP) can integrate several DERs into a unified op... Read More about Scalable and Reliable Data Framework for Sensor-enabled Virtual Power Plant Digital Twin.

Weather Impact on DER Long-term Performance: A Formal Verification Approach (2025)
Presentation / Conference Contribution
Santana, M. A., Stefanakos, I., Fang, X., Garg, A., Sun, H., & Osman, A. (2024, November). Weather Impact on DER Long-term Performance: A Formal Verification Approach. Presented at 2024 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia), Bangalore, India

Distributed energy resources (DERs), such as solar photovoltaic (PV) panels, are essential to modern energy systems, providing resilience and producing clean, local energy. However, their long-term performance is vulnerable to environmental factors,... Read More about Weather Impact on DER Long-term Performance: A Formal Verification Approach.

A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response † (2025)
Journal Article
Chen, W., Sun, H., You, M., Jiang, J., & Rivera, M. (2025). A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response †. Energies, 18(4), Article 833. https://doi.org/10.3390/en18040833

Within smart homes, consumers could generate a vast amount of data that, if analyzed effectively, can improve the convenience of consumers and reduce energy consumption. In this paper, we propose to organize household appliance data into a knowledge... Read More about A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response †.

Energy Self-Sufficiency Assessment of a Novel Low-Light Enhanced Photovoltaic Model in the Residential Sector (2025)
Presentation / Conference Contribution
Celis, A. A., Sun, H., Groves, C., & Harsh, P. (2024, October). Energy Self-Sufficiency Assessment of a Novel Low-Light Enhanced Photovoltaic Model in the Residential Sector. Presented at 2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024, Phoenix, AZ, USA

Increased photovoltaic (PV) penetration in the low-voltage residential sector highlights the intrinsic problems with Silicon PV (Si-PV) in seasonal power output fluctuations. Exploring the potential performance of emerging PV materials, such as Perov... Read More about Energy Self-Sufficiency Assessment of a Novel Low-Light Enhanced Photovoltaic Model in the Residential Sector.

Stochastic Incentive-based Demand Response Program for Virtual Power Plant with Distributed Energy Resources (2025)
Journal Article
Harsh, P., Sun, H., Das, D., Goyal, A., & Jiang, J. (online). Stochastic Incentive-based Demand Response Program for Virtual Power Plant with Distributed Energy Resources. IEEE Transactions on Industry Applications, https://doi.org/10.1109/TIA.2025.3535847

The growing integration of distributed energy resources (DERs) into the power grid necessitates an effective coordination strategy to maximize their benefits. Acting as an aggregator of DERs, a virtual power plant (VPP) facilitates this coordination,... Read More about Stochastic Incentive-based Demand Response Program for Virtual Power Plant with Distributed Energy Resources.

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.

Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks (2025)
Presentation / Conference Contribution
Dua, A., Jindal, A., Singh Aujla, G., & Sun, H. (2025, June). Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

6G applications rely on data-intensive AI models for network optimization. These demand a scalable and energy-efficient framework to handle massive device networks with stringent latency requirements which current solutions struggle to support. Even... Read More about Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G 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.

Efficient Context-Aware Barring Scheme for Low-Latency 2-Step RACH in 5G Networks (2025)
Presentation / Conference Contribution
Nie, D., Yu, W., Foh, C. H., Ni, Q., Chen, L., Berri, S., Chorti, A., & Sun, H. (2025, May). Efficient Context-Aware Barring Scheme for Low-Latency 2-Step RACH in 5G Networks. Presented at IEEE INFOCOM 2025: IEEE International Conference on Computer Communications - Workshop, London

The random access channel (RACH) procedure is critical for uplink synchronization and connection establishment in massive machine-type communication (mMTC). While 3GPP Release 16 introduced the 2-step RACH to reduce signaling overhead, latency incurr... Read More about Efficient Context-Aware Barring Scheme for Low-Latency 2-Step RACH in 5G Networks.

Multi-Objective Optimisation for Energy Scheduling in Smart Grids using Peer-to-Peer Trading (2024)
Presentation / Conference Contribution
Ezeokafor, C., Harsh, P., & Sun, H. (2024, November). Multi-Objective Optimisation for Energy Scheduling in Smart Grids using Peer-to-Peer Trading. Presented at IEEE PES Australasian Universities Power Engineering Conference (AUPEC), Sydney, Australia

Efficient scheduling of the sources within a community is essential to reduce the electricity-related cost as well as the carbon emissions from the community. A novel energy management strategy for community grids is introduced in this research, leve... Read More about Multi-Objective Optimisation for Energy Scheduling in Smart Grids using Peer-to-Peer Trading.