Adaptive Probabilistic Broadcasting over Dense Wireless Ad Hoc Networks

V. Gau, Jenq-Neng Hwang
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引用次数: 3

Abstract

We propose an idle probability-based broadcasting method, iPro, which employs an adaptive probabilistic mechanism to improve performance of data broadcasting over dense wireless ad hoc networks. In multisource one-hop broadcast scenarios, the modeling and simulation results of the proposed iPro are shown to significantly outperform the standard IEEE 802.11 under saturated condition. Moreover, the results also show that without estimating the number of competing nodes and changing the contention window size, the performance of the proposed iPro can still approach the theoretical bound. We further apply iPro to multihop broadcasting scenarios, and the experiment results show that within the same elapsed time after the broadcasting, the proposed iPro has significantly higher Packet-Delivery Ratios (PDR) than traditional methods.
密集无线自组织网络的自适应概率广播
我们提出了一种基于空闲概率的广播方法iPro,它采用自适应概率机制来提高密集无线自组织网络上数据广播的性能。在多源单跳广播场景下,iPro的建模和仿真结果表明,在饱和条件下,iPro的性能明显优于标准IEEE 802.11。此外,结果还表明,在不估计竞争节点数量和改变竞争窗口大小的情况下,所提出的iPro性能仍然接近理论界限。我们进一步将iPro应用于多跳广播场景,实验结果表明,在广播后相同的运行时间内,所提出的iPro具有明显高于传统方法的分组交付率(PDR)。
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