subhrajit barick | IIT KGP (original) (raw)
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National Institute of Technology, Calicut
Graduate Center of the City University of New York
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Papers by subhrajit barick
IEEE Access
The evolution and popular adaptation of drone technology in diverse applications has necessitated... more The evolution and popular adaptation of drone technology in diverse applications has necessitated advancement of UAV communication framework. UAVs inherently support features like mobility, flexibility, adaptive altitude, which make them a preferable option for dynamic surveillance of remote locations. Multiple UAVs can cooperatively work to accomplish surveillance missions more efficiently. However, the intermittent network connectivity and the limited onboard energy storage impose a great challenge on UAV-assisted remote surveillance. This paper presents an Energy-efficient Collaborative Multi-UAV Surveillance (ECMS) system for surveillance of inaccessible regions. The system employs an optimal Multi-UAV Collaborative Monocular Vision (MCMV) topology to facilitate the surveillance with zero blind spot using minimum number of drones. We also propose an application-aware Multi-Path Weighted Load-balancing (MWL) routing protocol for handling congestion by distributing traffic among all available resources in UAV network and adaptively selecting the of source datarate (i.e. switching video resolution). The simulation results demonstrate that the proposed surveillance system achieves coverage with lesser number of UAVs compared to the existing systems. It also achieves higher throughput, higher packet-delivery ratio, higher residual energy of UAVs, and lower end-to-end delay.
IEEE Access, 2022
Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectivel... more Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectively assist in IoT systems. The inherent features of UAV such as mobility, flexibility, and fast deployment make it preferable for emergency Internet of Things (IoT) applications. In this paper, we consider a multi-UAV assisted wireless network to support uplink communication for IoT devices distributed over a disaster area. The network involves two types of UAVs: sector UAV (SU) and anchor UAV (AU). The SU hovers at a fixed height over the sector around the temporary base station (TBS), collects the information from the respective IoT devices and relays them to the TBS via AU. The AU revolves continuously around the TBS and relays the information between the SUs and TBS periodically. We aim to improve the uplink capacity of the system. To achieve this, we employ non-orthogonal multiple access (NOMA), where we jointly optimize the positions of SUs and the power control of IoT devices. We propose a two-step approach to solve this. First, we optimize the position of SU in each sector by minimizing the sum distances of SU from the respective IoT devices. Then, by considering the optimal SU location, we optimize the transmit power of IoT devices using Lagrange dual method. Finally, the experimental results show that the proposed scheme improves the system capacity by 22% compared to the state-of-the-art schemes. INDEX TERMS UAV network, Internet-of-Things, uplink transmission, NOMA, system capacity.
IEEE Access
The evolution and popular adaptation of drone technology in diverse applications has necessitated... more The evolution and popular adaptation of drone technology in diverse applications has necessitated advancement of UAV communication framework. UAVs inherently support features like mobility, flexibility, adaptive altitude, which make them a preferable option for dynamic surveillance of remote locations. Multiple UAVs can cooperatively work to accomplish surveillance missions more efficiently. However, the intermittent network connectivity and the limited onboard energy storage impose a great challenge on UAV-assisted remote surveillance. This paper presents an Energy-efficient Collaborative Multi-UAV Surveillance (ECMS) system for surveillance of inaccessible regions. The system employs an optimal Multi-UAV Collaborative Monocular Vision (MCMV) topology to facilitate the surveillance with zero blind spot using minimum number of drones. We also propose an application-aware Multi-Path Weighted Load-balancing (MWL) routing protocol for handling congestion by distributing traffic among all available resources in UAV network and adaptively selecting the of source datarate (i.e. switching video resolution). The simulation results demonstrate that the proposed surveillance system achieves coverage with lesser number of UAVs compared to the existing systems. It also achieves higher throughput, higher packet-delivery ratio, higher residual energy of UAVs, and lower end-to-end delay.
IEEE Access, 2022
Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectivel... more Unmanned aerial vehicle (UAV) communication has become a prominent technology that can effectively assist in IoT systems. The inherent features of UAV such as mobility, flexibility, and fast deployment make it preferable for emergency Internet of Things (IoT) applications. In this paper, we consider a multi-UAV assisted wireless network to support uplink communication for IoT devices distributed over a disaster area. The network involves two types of UAVs: sector UAV (SU) and anchor UAV (AU). The SU hovers at a fixed height over the sector around the temporary base station (TBS), collects the information from the respective IoT devices and relays them to the TBS via AU. The AU revolves continuously around the TBS and relays the information between the SUs and TBS periodically. We aim to improve the uplink capacity of the system. To achieve this, we employ non-orthogonal multiple access (NOMA), where we jointly optimize the positions of SUs and the power control of IoT devices. We propose a two-step approach to solve this. First, we optimize the position of SU in each sector by minimizing the sum distances of SU from the respective IoT devices. Then, by considering the optimal SU location, we optimize the transmit power of IoT devices using Lagrange dual method. Finally, the experimental results show that the proposed scheme improves the system capacity by 22% compared to the state-of-the-art schemes. INDEX TERMS UAV network, Internet-of-Things, uplink transmission, NOMA, system capacity.