Sybot:用于wifi网络的自适应移动频谱测量系统

Kyu-Han Kim, Alexander W. Min, K. Shin
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引用次数: 18

摘要

关于特定站点频谱特性的信息对于评估和改进无线网络的性能至关重要。然而,在异构无线环境中,获取准确的频谱状况信息通常是非常昂贵的。本文提出了一种新的频谱测量系统——Sybot(频谱测量机器人),它可以指导网络工程师有效地监测WiFi网络的频谱状况(如RSS)。Sybot有效地控制移动性,并采用三种不同的监测技术-完整,选择性和诊断-帮助生成和维护准确的频谱状况地图,以应对具有挑战性的室内WiFi网络。通过自适应触发三种技术中最合适的一种,Sybot捕捉到了频谱条件下的时空变化。此外,Sybot根据监测结果自动确定几个关键的测量参数,如特定地点的测量时间和空间粒度。Sybot已经在商用IEEE 802.11路由器和Linux操作系统上进行了原型设计,并进行了实验评估,证明了它能够生成准确的频谱状况图,同时减少了56%以上的测量工作量(空间和时间)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sybot: an adaptive and mobile spectrum survey system for wifi networks
Information on site-specific spectrum characteristics is essential to evaluate and improve the performance of wireless networks. However, it is usually very costly to obtain accurate spectrum-condition information in heterogeneous wireless environments. This paper presents a novel spectrum-survey system, called Sybot (Spectrum survey robot), that guides network engineers to efficiently monitor the spectrum condition (e.g., RSS) of WiFi networks. Sybot effectively controls mobility and employs three disparate monitoring techniques - complete, selective, and diagnostic - that help produce and maintain an accurate spectrum-condition map for challenging indoor WiFi networks. By adaptively triggering the most suitable of the three techniques, Sybot captures spatio-temporal changes in spectrum condition. Moreover, based on the monitoring results, Sybot automatically determines several key survey parameters, such as site-specific measurement time and space granularities. Sybot has been prototyped with a commodity IEEE 802.11 router and Linux OS, and experimentally evaluated, demonstrating its ability to generate accurate spectrum-condition maps while reducing the measurement effort (space, time) by more than 56%.
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