Fast Neighbor Discovery in MEMS FSO Networks
Fast Neighbor Discovery in MEMS FSO Networks
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DOI：
10.1109/icnc47757.2020.9049690
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发表时间：
2020-02
期刊：
影响因子：
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通讯作者：
M. Atakora;H. Chenji
中科院分区：
文献类型：
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作者：
M. Atakora;H. Chenji
我们调查是否有可能实现亚毫秒级的延迟发现多个邻居在基于激光的自由空间光（FSO）网络。给出了一个大的可编程微镜阵列，我们提出了使用自适应布尔组合群测试算法，是实用和高效的。即使N是未知的，对于N个邻居，所花费的时间也是O（N log（L/N）），但是没有额外的计算（例如，矩阵求逆）。相比光栅和Lissajous模式为基础的扫描，我们报告的延迟分别减少99.92%和87%，为106微镜阵列（约XGA分辨率）。我们的结论是，它确实是有可能实现亚毫秒延迟给定现实的网络参数。我们提出的算法进行了评估模拟，并与最先进的邻居发现计划。
We investigate whether it is possible to achieve sub-millisecond latency for the discovery of multiple neighbors in laser-based Free Space Optical (FSO) networks. Given a large programmable array of micromirrors, we propose the use of adaptive boolean combinatorial group testing algorithms that are practical and efficient. The time taken scales as O(N log(L/N)) for N neighbors even if N is unknown, but no additional computation (e.g., matrix inversion) is required. Compared to Raster and Lissajous pattern-based scanning, we report 99.92% and 87% reduction in latency, respectively, for an array of 106 micromirrors (approximately XGA resolution). We conclude that it is indeed possible to achieve sub-ms latency given realistic network parameters. Our proposed algorithms are evaluated in simulation, and are compared against state of art neighbor discovery schemes.