OPAR：协作UAV网络的优化预测自适应路由
OPAR: Optimized Predictive and Adaptive Routing for Cooperative UAV Networks
摘要：
无人机协同组网在军事和民用领域的应用越来越广泛。然而，由于无人机网络的三维高度动态性和网络中节点分布的不均匀性，以寻找最短路径为目标的典型ad-hoc路由协议会导致网络性能的显著下降。本文提出了OPAR，一个优化的预测和自适应路由协议，面对这一挑战性的问题。我们建模的路由问题与线性规划（LP），其中的目标是最大限度地提高网络的性能，同时考虑路径的生命周期和路径长度。该模型依赖于精确的链路寿命预测机制。我们支持LP问题的轻量级算法，以找到最佳的解决方案，计算复杂度为$O(|E|^2)$，其中$|E|$是网络链路的数量。我们评估OPAR的性能，并将其与著名的路由算法AODV，DSDV和OLSR进行比较，以涵盖广泛的主动和被动协议以及距离矢量和链路状态技术。我们进行了广泛的模拟不同的网络密度和流动性模式，使用ns-3模拟器。实验结果表明，OPAR能有效地防止大量的路由流量，使成功投递率提高了$30\%$以上，平均吞吐量提高了$25\%$，流完成时间平均降低了$35\%$ .
英文摘要：
Cooperative UAV networks are becoming increasingly popular in military and civilian applications. Alas, the typical ad-hoc routing protocols, which aim at finding the shortest path, lead to significant performance degradation because of the 3-dimension highly-dynamic nature of UAV networks and the uneven distribution of nodes across the network. This paper proposes OPAR, an optimized predictive and adaptive routing protocol, to face this challenging problem. We model the routing problem with linear programming (LP), where the goal is to maximize network performance, considering the path lifetime and path-length together. This model relies on a precise link lifetime prediction mechanism. We support the LP problem with a lightweight algorithm to find the optimized solution with a computation complexity of $O(|E|^2)$, where $|E|$ is the number of network links. We evaluate the OPAR performance and compare it with the well-known routing algorithms AODV, DSDV, and OLSR to cover a wide range of proactive and reactive protocols as well as distance vector and link-state techniques. We performed extensive simulations for different network densities and mobility patterns using the ns-3 simulator. Results show that OPAR prevents a high volume of routing traffic, increases the successful delivery by more than $30\%$, improves the throughput $25\%$ on average, and decreases the flow completion time by an average of $35\%$.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
