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Surender Redhu
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2020 – today
- 2023
- [j7]Micheal Dutt, Surender Redhu, Morten Goodwin, Christian W. Omlin:
SleepXAI: An explainable deep learning approach for multi-class sleep stage identification. Appl. Intell. 53(13): 16830-16843 (2023) - [j6]Aditya Singh, Surender Redhu, Baltasar Beferull-Lozano, Rajesh M. Hegde:
Network-aware RF-energy harvesting for designing energy efficient IoT networks. Internet Things 22: 100770 (2023) - [j5]Deepali Kushwaha, Surender Redhu, Christopher G. Brinton, Rajesh M. Hegde:
Optimal Device Selection in Federated Learning for Resource-Constrained Edge Networks. IEEE Internet Things J. 10(12): 10845-10856 (2023) - 2022
- [c16]Poorva Sironja, Surender Redhu, Rajesh M. Hegde, Baltasar Beferull-Lozano:
Cluster-based 3D-Beam Power Management in Resource-Constrained Wireless Networks. COMSNETS 2022: 590-594 - [c15]Micheal Dutt, Surender Redhu, Morten Goodwin, Christian W. Omlin:
Sleep Stage Identification based on Single-Channel EEG Signals using 1-D Convolutional Autoencoders. HealthCom 2022: 94-99 - [c14]Aditya Singh, Surender Redhu, Rajesh M. Hegde:
UAV Altitude Optimization for Efficient Energy Harvesting in IoT Networks. NCC 2022: 350-355 - [c13]Aditya Singh, Surender Redhu, Rajesh M. Hegde:
Energy-Efficient UAV Trajectory Planning in Rechargeable IoT Networks. SPCOM 2022: 1-5 - [c12]Sarang Kumar, Mohamed Elnourani, Baltasar Beferull-Lozano, Surender Redhu:
A Deep Learning-Based Channel Aware Single Step Signal Detection in Downlink Multi-User NOMA. VTC Fall 2022: 1-6 - [c11]Deepali Kushwaha, Surender Redhu, Rajesh M. Hegde:
Low Latency Federated Learning over Wireless Edge Networks via Efficient Bandwidth Allocation. WF-IoT 2022: 1-6 - [c10]Aditya Singh, Rahul Rustagi, Surender Redhu, Rajesh M. Hegde:
Mobile Energy Transmitter Scheduling in Energy Harvesting IoT Networks using Deep Reinforcement Learning. WF-IoT 2022: 1-6 - 2021
- [c9]Surender Redhu, Amrendra P. Singh, Rajesh M. Hegde, Baltasar Beferull-Lozano:
A Cluster based Sensor-Selection Scheme for Energy-Efficient Agriculture Sensor Networks. CCNC 2021: 1-4 - [c8]Shraddha Tripathi, Surender Redhu, Rajesh M. Hegde:
Clustering-Assisted 3D Beamforming for Throughput Maximization in mmWave Networks. ICC Workshops 2021: 1-6 - [c7]Aditya Singh, Surender Redhu, Rajesh M. Hegde:
Context-Aware RF-Energy Harvesting for IoT Networks. WF-IoT 2021: 77-82 - 2020
- [j4]Surender Redhu, Rajesh M. Hegde:
Optimal relay node selection in time-varying IoT networks using apriori contact pattern information. Ad Hoc Networks 98 (2020) - [j3]Surender Redhu, Rajesh M. Hegde:
Cooperative Network Model for Joint Mobile Sink Scheduling and Dynamic Buffer Management Using Q-Learning. IEEE Trans. Netw. Serv. Manag. 17(3): 1853-1864 (2020)
2010 – 2019
- 2019
- [j2]Surender Redhu, Rajesh M. Hegde:
Network lifetime improvement using landmark-assisted mobile sink scheduling for cyber-physical system applications. Ad Hoc Networks 87: 37-48 (2019) - [j1]Surender Redhu, Mayank Anupam, Rajesh M. Hegde:
Optimal Relay Node Selection for Robust Data Forwarding Over Time-Varying IoT Networks. IEEE Trans. Veh. Technol. 68(9): 9178-9190 (2019) - [c6]Surender Redhu, Rajesh M. Hegde:
Multi-Sensor Data Fusion for Cluster-based Data Aggregation in IoT Applications. ANTS 2019: 1-6 - [c5]Surender Redhu, Rajesh M. Hegde:
Low complexity landmark-node tracing in WSNs using multi-agent random walks. ICDCN 2019: 261-266 - 2018
- [c4]Surender Redhu, Pratyush Garg, Rajesh M. Hegde:
Joint Mobile Sink Scheduling and Data Aggregation in Asynchronous Wireless Sensor Networks Using Q-Learning. ICASSP 2018: 6438-6442 - [c3]Surender Redhu, Mukund Maheshwari, Kshitij Yeotikar, Rajesh M. Hegde:
Poster: Joint Data Latency and Packet Loss Optimization for Relay-Node Selection in Time-Varying IoT Networks. MobiCom 2018: 711-713 - [c2]Surender Redhu, Rahul Mahavar, Rajesh M. Hegde:
Energy-efficient wake-up radio protocol using optimal sensor-selection for IoT. WCNC 2018: 1-6 - 2017
- [c1]Surender Redhu, Rajesh M. Hegde:
Energy-efficient landmark tracing in WSNs using random walks on network graphs. COMSNETS 2017: 399-400
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