Surender Redhu - Research

Static Wireless Sensors and IoT Networks

In static IoT networks, the sensor nodes are deployed randomly with limited power resources which demands energy-efficient data transmission schemes. Energy-efficiency of sensor nodes can be improved by network clustering, adaptive wake-up scheduling, mobile sink deployment, and adaptive sampling rate techniques. Design and development of cooperative data transmission models is an emerging area that can help overcome the limitations of conventional methods.

In static IoT networks, the sensor nodes are deployed randomly with limited power resources which demands energy-efficient data transmission schemes. Energy-efficiency of sensor nodes can be improved by network clustering, adaptive wake-up scheduling, mobile sink deployment, and adaptive sampling rate techniques. Design and development of cooperative data transmission models is an emerging area that can help overcome the limitations of conventional methods.

S. Redhu, and R. M. Hegde, "Network lifetime improvement using landmark-assisted mobile sink scheduling for cyber-physical system applications." Elsevier Ad Hoc Networks 87 (2019): 37-48.
S. Redhu, A. Singh, R. M. Hegde, B. Beferull-Lozano, "A Cluster based Sensor-Selection Scheme for Energy-Efficient Agriculture Sensor Networks," Accepted at IEEE Consumer Communications and Networking Conference (CCNC), 2021.
S. Redhu and R. M. Hegde, “Energy-Efficient Landmark Tracing in WSNs using Random Walks on Network Graphs,” in 2017 9th International Conference on Communication Systems and Networks (COMSNETS), Jan 2017, pp. 399–400.
S. Redhu, R. Mahavar and R. M. Hegde, "Energy-efficient wake-up radio protocol using optimal sensor-selection for IoT," 2018 IEEE Wireless Communications and Networking Conference (WCNC), Barcelona, 2018, pp. 1-6.
S. Redhu, and R. M. Hegde, "Low complexity landmark-node tracing in WSNs using multi-agent random walks." Proceedings of the 20th Annual International Conference on Distributed Computing and Networking. (ACM ICDCN), 2019.

In time-varying IoT networks such as vehicular networks, where the nodes are mobile, require a completely different approach for efficient data transmission. Cooperative data transmission models with low-latency and high-reliability are becoming a necessity in such time-varying IoT networks.

Surender Redhu, Mayank Anupam, and Rajesh M. Hegde, “Optimal Relay Node Selection for Robust Data Forwarding over Time-Varying IoT Networks” IEEE Transactions on Vehicular Technology, vol. 68, no. 9, pp. 9178-9190, Sep. 2019.
S. Redhu, and R. M. Hegde, ''Optimal Relay Node Selection in Time-varying IoT Networks using Network Contact Patterns.'' (Accepted to appear at Elsevier Ad Hoc Networks)
S. Redhu, et al. "Joint Data Latency and Packet Loss Optimization for Relay-Node Selection in Time-Varying IoT Networks." Proceedings of the 24th Annual International Conference on Mobile Computing and Networking. (ACM MobiCom), 2018.

S. Redhu, P. Garg and R. M. Hegde, "Joint Mobile Sink Scheduling and Data Aggregation in Asynchronous Wireless Sensor Networks using Q-Learning", IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP 2018), Calgary, Alberta, Canada, Apr. 2018.
S. Redhu, and R. M. Hegde, ''Joint Mobile Sink Scheduling and Buffer Overflow Management in Cooperative Wireless Sensor Networks using Q-Learning.'' Accepted to appear at IEEE Transaction on Network and Service Management, DOI: 10.1109/TNSM.2020.3002828.

S. Redhu, and R. M. Hegde, "Multi-Sensor Data Fusion for Clustered-based Data Aggregation for IoT Applications " (IEEE ANTS), 2019.
A. Singh, S. Redhu, R. Hegde, "Context-Aware RF-Energy Harvesting for IoT Networks" (Accepted at proceedings of WF-IoT, 2021).
S. Tripathi, S. Redhu, R. Hegde, "Clustering-Assisted 3D Beamforming for Throughput Maximization in mmWave Networks" (Accepted at proceedings of ICC Workshops, 2021).