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Adaptive Forwarding Delay Control for VANET Data Aggregation

机译:VANET数据聚合的自适应转发延迟控制

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摘要

In-network data aggregation is a useful technique to reduce redundant data and to improve communication efficiency. Traditional data aggregation schemes for wireless sensor networks usually rely on a fixed routing structure to ensure data can be aggregated at certain sensor nodes. However, they cannot be applied in highly mobile vehicular environments. In this paper, we propose an adaptive forwarding delay control scheme, namely Catch-Up, which dynamically changes the forwarding speed of nearby reports so that they have a better chance to meet each other and be aggregated together. The Catch-Up scheme is designed based on a distributed learning algorithm. Each vehicle learns from local observations and chooses a delay based on learning results. The simulation results demonstrate that our scheme can efficiently reduce the number of redundant reports and achieve a good trade-off between delay and communication overhead.
机译:网络内数据聚合是减少冗余数据和提高通信效率的有用技术。用于无线传感器网络的传统数据聚合方案通常依赖于固定的路由结构,以确保可以在某些传感器节点上聚合数据。但是,它们不能应用于高度移动的车辆环境中。在本文中,我们提出了一种自适应转发延迟控制方案,即Catch-Up,它可以动态更改附近报告的转发速度,从而使它们有更好的机会互相见面并聚集在一起。追赶方案是基于分布式学习算法设计的。每辆车都从当地观察中学习,并根据学习结果选择延迟时间。仿真结果表明,我们的方案可以有效地减少冗余报告的数量,并在延迟和通信开销之间取得良好的折衷。

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