Analysis of Large-Scale Experimental Data from Wireless Networks

被引：0

作者：

Seidel, Stephen A. ^{[1
]}

Mehari, Michael T. ^{[2
]}

Colbourn, Charles J. ^{[1
]}

De Poorter, Eli ^{[2
]}

Moerman, Ingrid ^{[2
]}

Syrotiuk, Violet R. ^{[1
]}

机构：

[1] Arizona State Univ, Sch Comp Informat & Decis Syst Engn, Tempe, AZ 85287 USA

[2] Univ Ghent, IMEC, Dept Informat Technol INTEC, Internet & Data Sci ID Lab, B-9052 Ghent, Belgium

来源：

IEEE INFOCOM 2018 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS) | 2018年

基金：

欧盟地平线“2020”; 美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The experimental design and subsequent analysis of the data collected from experimentation are tightly coupled. This paper considers techniques for the analysis of data collected from experimentation based on a locating array. Because locating arrays can be highly unbalanced, new analysis techniques are required. In order to cope with noise in the measured performance data, a search is conducted to identify the significant parameters and interactions that impact the data. A novel "heavy hitters" bounded breadth-first search (BFS) tree algorithm is proposed for analysis. It is used to validate data collected from large-scale experimentation with a physical wireless network testbed and a wireless network simulator, varying 24 and 75 parameters, respectively.

引用

页码：535 / 540

页数：6

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