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CAPTAIN: A data collection algorithm for underwater optical-acoustic sensor networks

机译:CAPPTAIN:水下光声传感器网络的数据收集算法

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Underwater sensor networks are used to collect data from aquatic environments. Nodes from these networks usually communicate via acoustic or optical transmissions due to the poor performance of radiofrequency communication in these environments. Acoustic transmissions achieve longer distances than optical ones, but also consume more energy and have lower bandwidth. Underwater optical-acoustic sensor networks (UOASNs) combine both types of communication to explore the best of each one. In this paper, we propose CAPTAIN, an algorithm to perform data collection with data aggregation in UOASNs. CAPTAIN divides the network into clusters, builds a routing tree, and uses data aggregation to deliver all data collected to the sink node. Experiments showed that, compared to the shortest path algorithm, CAPTAIN led to lower network energy consumption, especially in denser networks, where it was able to consume, on average, up to 73% less. CAPTAIN could also achieve lower average latencies (up to almost 83% lower) and higher rates of data collected per hour by the sink node using fewer acoustic transmissions in clustered networks.
机译:水下传感器网络用于从水生环境收集数据。由于这些环境中射频通信的性能较差,因此来自这些网络的节点通常通过声音或光学传输进行通信。声音传输的距离比光学传输的距离长,但消耗的能量更多,带宽也较低。水下光声传感器网络(UOASN)结合了两种类型的通信,以探索每种通信的最佳性能。在本文中,我们提出了CAPTAIN,一种在UOASN中通过数据聚合执行数据收集的算法。 CAPTAIN将网络划分为群集,构建路由树,并使用数据聚合将收集到的所有数据传递到接收器节点。实验表明,与最短路径算法相比,CAPTAIN可以降低网络能耗,尤其是在密度更高的网络中,该网络平均可以减少多达73%的能耗。 CAPTAIN还可以在集群网络中使用更少的声音传输来实现更低的平均延迟(降低近83%)和更高的接收节点每小时收集的数据速率。

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