Optimized Compression Policy for Flying Ad hoc Networks
Optimized Compression Policy for Flying Ad hoc Networks
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DOI：
10.1109/ccnc.2019.8651761
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Arnau Rovira-Sugranes;F. Afghah;Abolfazl Razi
中科院分区：
文献类型：
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作者：
Arnau Rovira-Sugranes;F. Afghah;Abolfazl Razi
管理计算和通信的能耗是飞行自组织网络 (FANET) 延长网络寿命的关键要求。在许多应用中，无人机的主要作用是收集图像信息并将其转发到地面站以进行进一步处理和决策。在本文中，我们提出了一种预测压缩策略，以最大限度地提高因通信和计算成本而受到影响的端到端图像质量。这个想法是针对给定的路由算法预测到目的地的剩余链路的数量，并使用它来重新压缩中间节点的图像帧，从而最小化总体能量消耗。数值结果证实，该方法的性能与全局最优值相差 4% 以内，并且明显高于当前的固定利率政策。
Managing energy consumption for computation and communication is a key requirement for flying ad hoc networks (FANET) to prolong the network lifetime. In many applications, the main role of drones is to collect imagery information and relay them to a ground station for further processing and decision making. In this paper, we present a predictive compression policy to maximize the end-to-end image quality penalized by the communication and computation costs. The idea is to predict the number of remaining links to the destination for a given routing algorithm and use it to re-compress image frames at intermediate nodes such that the overall energy consumption is minimized. Numerical results confirm that the performance of this method is within 4% of the global optima and higher than the current fixed-rate policies with a significant margin.