浮游生物:一个有效的DTN路由算法

Xiangfa Guo, M. Chan
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引用次数: 24

摘要

本文提出了一种适用于容忍延迟/中断网络(DTN)的路由算法浮游生物(Plankton)。浮游生物利用副本控制来减少开销和接触概率估计,以提高性能。浮游生物有两个主要特征。首先,它结合了短期突发接触和基于长期关联的统计数据进行接触预测。其次,它根据估计的接触概率和投递概率动态调整复制配额。我们对广泛痕迹的评估表明,浮游生物的预测精度明显优于现有的接触概率预测算法。此外,我们表明,与Spray-and-Wait、MaxProp和RAPID相比,浮游生物的通信开销要低得多,节省了14%到88%,它也可以实现类似的传输比率和延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Plankton: An efficient DTN routing algorithm
In this paper, we present an efficient routing algorithm, Plankton, for Delay/Disruptive Tolerant Network (DTN). Plankton utilizes replica control to reduce overhead and contact probability estimates to improve performance. Plankton has two major features. First, it uses a combination of both short-term bursty contacts and long-term association based statistics for contact prediction. Second, it dynamically adjusts replication quotas based on estimated contact probabilities and delivery probabilities. Our evaluation on extensive traces shows that Plankton achieves significantly better prediction accuracy than existing algorithms for contact probability prediction. In addition, we show that while Plankton incurs much lower communication overhead compared to Spray-and-Wait, MaxProp and RAPID with savings from 14% to 88%, it can also achieve similar if not better delivery ratios and latencies.
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