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Work-in-progress: A new random walk for data collection in sensor networks

机译:工作过程:传感器网络中的数据收集的新随机步行

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摘要

Motivated by the problem of efficient sensor network data collection via a mobile sink, we present undergoing research in accelerated random walks on Random Geometric Graphs. We first propose a new type of random walk, called the α-stretched random walk, and compare it to three known random walks. We also define a novel performance metric called Proximity Cover Time which, along with other metrics such us visit overlap statistics and proximity variation, we use to evaluate the performance properties and features of the various walks. Finally, we present future plans on investigating a relevant combinatorial property of Random Geometric Graphs that may lead to new, faster random walks and metrics.
机译:通过移动水槽有效传感器网络数据收集的问题,我们在随机几何图上进行加速随机漫步的研究。 我们首先提出了一种新型的随机散步,称为α - 伸展随机步行,并将其与三个已知的随机散步进行比较。 我们还定义了一种名为Proximity覆盖时间的新型性能度量,以及我们访问的其他度量,我们访问重叠统计和邻近变化,我们用于评估各种散步的性能属性和功能。 最后,我们提出了对调查可能导致新的随机几何图的相关组合属性的未来计划,这些属性可能导致新的,更快的随机漫步和指标。

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