Time-Dependent Ad-Hoc Routing Structure for Delivering Delay-Sensitive Data Using UAVs
In disaster scenarios where communication networks have broken down, it is important to ensure a reliable data delivery from an emergency operations center to the local target nodes within its effective time limit. We propose a hybrid data delivery mechanism that exploits the load-carry-and-delivery...
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Veröffentlicht in: | IEEE access 2020, Vol.8, p.36322-36336 |
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Sprache: | eng |
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Zusammenfassung: | In disaster scenarios where communication networks have broken down, it is important to ensure a reliable data delivery from an emergency operations center to the local target nodes within its effective time limit. We propose a hybrid data delivery mechanism that exploits the load-carry-and-delivery by UAVs with a mixture of localized ad-hoc routing over partially connected terrestrial networks. We aim to achieve reliable on-time data delivery to the target nodes, while preserving the low routing cost. Our proposed routing methodology consists of three steps: 1) localized network construction, 2) network probing by UAVs, and 3) localized ad-hoc routing based on a dynamic depth routing tree depending on the data urgency. Here, we present an innovative cost-effective local data sharing structure called localized minimal routing tree that balances with the direct data delivery by UAVs. After the initial network setup and probing procedure, each UAV makes a series of near-optimal decisions of which grid points to visit considering its localized network topology and data urgency. Our time-dependent routing mechanism dynamically decides data recipient nodes to serve more urgent data delivery with a higher priority at a time. The simulation experiments validated our combined path planning and routing approach, achieving 71% higher reliability than the best possible performance by using only the network nodes and consuming 20% lower energy than the UAV-only approach, while maintaining high reliability. Thus, our work makes a strong case for systematically combining the two approaches. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2020.2974553 |