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DGCCF: Data Gathering Based on Closeness Centrality Forwarding in Opportunistic Mobile Sensor Networks

机译:DGCCF:机会移动传感器网络中基于紧密集中转发的数据收集

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Opportunistic Mobile Sensor Networks (OMSN) can be applied in many scenarios where the sensor data usually need to be transmitted from the source node to one of the multiple sink nodes. We propose the DGCCF (Data Gathering based on Closeness Centrality Forwarding) algorithm, which adopts "store-carry-forward" paradigm to transmit data from sensors to the sink nodes. In DGCCF, each sensor node keeps the Closeness Centrality (CC) to all sink nodes based on encounter history between the node and all the sink nodes. When two nodes encounter, the node with the lower CC value forwards its messages to the other nodes, until the messages are delivered to one of the sink nodes. Experimental results reveal that DGCCF can provide better performance on both the delivery ration and delivery latency than ZebraNet and the Random Forwarding algorithm.
机译:机会移动传感器网络(OMSN)可以应用在通常需要将传感器数据从源节点传输到多个接收节点之一的许多情况下。我们提出了DGCCF(基于近距离集中性转发的数据收集)算法,该算法采用“存储转发”范式将数据从传感器传输到接收器节点。在DGCCF中,每个传感器节点都基于节点与所有接收器节点之间的遭遇历史记录来保持对所有接收器节点的接近中心性(CC)。当遇到两个节点时,具有较低CC值的节点会将其消息转发到其他节点,直到将消息传递到宿节点之一。实验结果表明,与ZebraNet和随机转发算法相比,DGCCF可以在传递比率和延迟方面提供更好的性能。

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