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Path Diversity Over Packet Switched Networks: Performance Analysis and Rate Allocation

机译:分组交换网络上的路径分集:性能分析和速率分配

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Path diversity works by setting up multiple parallel connections between the endpoints using the topological path redundancy of the network. In this paper, forward error correction (FEC) is applied across multiple independent paths to enhance the end-to-end reliability. We prove that the probability of irrecoverable loss $(P_E)$ decays exponentially with the number of paths. Furthermore, the rate allocation (RA) problem across independent paths is studied. Our objective is to find the optimal RA, i.e., the allocation that minimizes $P_E$. The RA problem is solved for a large number of paths. Moreover, it is shown that in such asymptotically optimal RA, each path is assigned a positive rate iff its quality is above a certain threshold. Finally, using memoization technique, a heuristic suboptimal algorithm with polynomial runtime is proposed for RA over a finite number of paths. This algorithm converges to the asymptotically optimal RA when the number of paths is large. For a practical number of paths, the simulation results demonstrate the close-to-optimal performance of the proposed algorithm .
机译:路径分集通过使用网络的拓扑路径冗余在端点之间建立多个并行连接来工作。本文将前向纠错(FEC)应用于多个独立路径,以增强端到端可靠性。我们证明了不可恢复的损失$(P_E)$的概率随着路径数量的增加呈指数下降。此外,研究了跨独立路径的速率分配(RA)问题。我们的目标是找到最佳RA,即最小化$ P_E $的分配。针对大量路径解决了RA问题。而且,表明在这种渐近最优RA中,如果其质量高于某个阈值,则为每个路径分配正速率。最后,利用记忆技术,针对有限数量的路径,提出了具有多项式运行时间的启发式次优算法。当路径数量很大时,该算法收敛到渐近最优RA。对于实际数量的路径,仿真结果证明了所提出算法的接近最佳性能。

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