Self-Organizing and Scalable Routing Protocol (SOSRP) for Underwater Acoustic Sensor Networks

Las redes de sensores acústicas submarinas (UASN) han ganado mucha importancia en los últimos años: el 71% de la superficie de la Tierra está cubierta por océanos. La mayoría de ellos, aún no han sido explorados. Aplicaciones como prospección de yacimientos, prevención de desastres o recopilación de datos para estudios de biología marina se han convertido en el campo de interés para muchos investigadores. Sin embargo, las redes UASN tienen dos limitaciones: un medio muy agresivo (marino) y el uso de señales acústicas. Ello hace que las técnicas para redes de sensores inalámbricas (WSN) terrestres no sean aplicables. Tras realizar un recorrido por el estado del arte en protocolos para redes UASN, se propone en este TFM un protocolo de enrutamiento denominado "SOSRP", descentralizado y basado en tablas en cada nodo. Se usa como criterio para crear rutas una combinación del valor de saltos hasta el nodo recolector y la distancia. Las funciones previstas del protocolo abarcan: autoorganización de las rutas, tolerancia a fallos y detección de nodos aislados. Mediante la implementación en MATLAB de SOSRP así como de un modelo de propagación y energía apropiados para entorno marino, se obtienen resultados de rendimiento en distintos escenarios (variando nºextremo de paquetes, consumo de energía o longitud de rutas creadas (con y sin fallo). Los resultados obtenidos muestran una operación estable, fiable y adecuada para el despliegue y operación de los nodos en redes UASN

Internode Distance-Based Redundancy Reliable Transport in Underwater Sensor Networks

Underwater communication is a very challenging topic. Protocols used in terrestrial sensor networks cannot be directly applied in the underwater world. High-bit error rate and large propagation delay make the design of transport protocols especially awkward. ARQ-based reliable transport schemes are not appropriate in underwater environments due to large propagation delay, low communication bandwidth, and high error probability. Thus, we focus on redundancy-based transport schemes in this paper. We first investigate three schemes that employ redundancy mechanisms at the bit and/or packet level to increase the reliability in a direct link scenario. Then, we show that the broadcast property of the underwater channel allows us to extend those schemes to a case with node cooperative communication. Based on our analysis, an adaptive redundancy transport protocol (ARRTP) for underwater sensor networks is proposed. We suggest an architecture for implementation. For two kinds of topologies, namely, regular and random, we show that ARRTP presents a better transmission success probability and energy efficiency tradeoff for single- and multihop transmissions. We also offer an integrated case study to show that ARRTP is not only supplying reliability but also has some positive effect in guiding the deployment of underwater sensor nodes

An effective data-collection scheme with AUV path planning in underwater wireless sensor networks

Data collection in underwater wireless sensor networks (UWSNs) using autonomous underwater vehicles (AUVs) is a more robust solution than traditional approaches, instead of transmitting data from each node to a destination node. However, the design of delay-aware and energy-efficient path planning for AUVs is one of the most crucial problems in collecting data for UWSNs. To reduce network delay and increase network lifetime, we proposed a novel reliable AUV-based data-collection routing protocol for UWSNs. The proposed protocol employs a route planning mechanism to collect data using AUVs. The sink node directs AUVs for data collection from sensor nodes to reduce energy consumption. First, sensor nodes are organized into clusters for better scalability, and then, these clusters are arranged into groups to assign an AUV to each group. Second, the traveling path for each AUV is crafted based on the Markov decision process (MDP) for the reliable collection of data. The simulation results affirm the effectiveness and efficiency of the proposed technique in terms of throughput, energy efficiency, delay, and reliability. © 2022 Wahab Khan et al

Distributed space–time cooperative schemes for underwater acoustic communications

Author Posting. © IEEE, 2008. This article is posted here by permission of IEEE for personal use, not for redistribution. The definitive version was published in IEEE Journal of Oceanic Engineering 33 (2008): 489-50, doi:10.1109/JOE.2008.2005338.In resource limited, large scale underwater sensor networks, cooperative communication over multiple hops offers opportunities to save power. Intermediate nodes between source and destination act as cooperative relays. Herein, protocols coupled with space-time block code (STBC) strategies are proposed and analyzed for distributed cooperative communication. Amplify-and-forward-type protocols are considered, in which intermediate relays do not attempt to decode the information. The Alamouti-based cooperative scheme proposed by Hua (2003) for flat-fading channels is generalized to work in the presence of multipath, thus addressing a main characteristic of underwater acoustic channels. A time-reversal distributed space-time block code (TR-DSTBC) is proposed, which extends the dual-antenna TR-STBC (time-reversal space-time block code) approach from Lindskog and Paulraj (2000) to a cooperative communication scenario for signaling in multipath. It is first shown that, just as in the dual-antenna STBC case, TR along with the orthogonality of the DSTBC essentially allows for decoupling of the vector intersymbol interference (ISI) detection problem into separate scalar problems, and thus yields strong performance (compared with single-hop communication) and with substantially reduced complexity over nonorthogonal schemes. Furthermore, a performance analysis of the proposed scheme is carried out to provide insight on the performance gains, which are further confirmed via numerical results based on computer simulations and field data experiments