Effective communication for message prioritization in DTN for disaster scenarios
[EN] When disaster strikes, effective communication is crucial for emergency responses and accessing a victim¿s location. Using smartphone-based Delay Tolerant Networks (DTNs) is the prevalent proposed approach to work around network disruptions. One of the challenges in these networks is high-traff...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/232885 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/232885 |
| Access Level: | acceso abierto |
| Palabra clave: | Delay tolerant networks Congestion Disaster scenarios Resilience 09.- Desarrollar infraestructuras resilientes, promover la industrialización inclusiva y sostenible, y fomentar la innovación 11.- Conseguir que las ciudades y los asentamientos humanos sean inclusivos, seguros, resilientes y sostenibles |
| Sumario: | [EN] When disaster strikes, effective communication is crucial for emergency responses and accessing a victim¿s location. Using smartphone-based Delay Tolerant Networks (DTNs) is the prevalent proposed approach to work around network disruptions. One of the challenges in these networks is high-traffic congestion since buffer limitation produces messages that get dropped before they are delivered. This article presents a congestion control strategy using message prioritization for DTNs to increase network resilience facing high message congestion. We measure congestion by considering the free space in the buffer of the nodes involved in the routing or by counting the messages deleted from the buffer in a fixed period to improve the availability and immediacy of information for disaster scenarios. We evaluated the proposed strategies using The ONE simulator to test different mobility models and communication protocols. Results show that the strategy improved delivery rate, buffer usage, eliminated messages, overhead, and latency for the highest priority messages. The best results were obtained in terms of latency, which fits our disaster scenario since timely information is vital. The trade-offs are a slightly lower average delivery rate and a decrease in the lowest priority message delivery rate. |
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