A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy Compression

In response of the comprehensive popularization of Institute of Electrical and Electronics Engineers (IEEE) 802.11 in recent years, the rapid increase of Internet of Things (IoT) data has brought about problems such as high network transmission pressure, difficult data management, and high data secu...

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Main Authors: LI Ming, LI Ming-chun, LIU Shi-chao
Format: Article
Language:zho
Published: 《光通信研究》编辑部 2022-10-01
Series:Guangtongxin yanjiu
Subjects:
Online Access:http://www.gtxyj.com.cn/thesisDetails#10.13756/j.gtxyj.2022.05.013
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author LI Ming
LI Ming-chun
LIU Shi-chao
author_facet LI Ming
LI Ming-chun
LIU Shi-chao
author_sort LI Ming
collection DOAJ
description In response of the comprehensive popularization of Institute of Electrical and Electronics Engineers (IEEE) 802.11 in recent years, the rapid increase of Internet of Things (IoT) data has brought about problems such as high network transmission pressure, difficult data management, and high data security risks. Based on years of experience in WiFi wireless Access Point (AP) management and data warehouse implementation, this article expounds a construction method of wireless AP data warehouse based on anomaly identification and lossy compression. The results show that the abnormal identification and lossy compression of data with high repeatability of wireless AP can effectively solve the problems of high storage pressure and communication congestion in distributed data warehouses which caused by the excessive amount of repeated data of network equipment, and greatly reduce the overall cost when the company implement the data warehouse with IoT datas.
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spelling doaj.art-62ed4a8b86c9406ea77597b677c6d2ff2024-05-06T09:51:07Zzho《光通信研究》编辑部Guangtongxin yanjiu1005-87882022-10-01747830983099A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy CompressionLI MingLI Ming-chunLIU Shi-chaoIn response of the comprehensive popularization of Institute of Electrical and Electronics Engineers (IEEE) 802.11 in recent years, the rapid increase of Internet of Things (IoT) data has brought about problems such as high network transmission pressure, difficult data management, and high data security risks. Based on years of experience in WiFi wireless Access Point (AP) management and data warehouse implementation, this article expounds a construction method of wireless AP data warehouse based on anomaly identification and lossy compression. The results show that the abnormal identification and lossy compression of data with high repeatability of wireless AP can effectively solve the problems of high storage pressure and communication congestion in distributed data warehouses which caused by the excessive amount of repeated data of network equipment, and greatly reduce the overall cost when the company implement the data warehouse with IoT datas.http://www.gtxyj.com.cn/thesisDetails#10.13756/j.gtxyj.2022.05.013wireless AP;abnormal data recognition;data warehouse;IOT
spellingShingle LI Ming
LI Ming-chun
LIU Shi-chao
A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy Compression
Guangtongxin yanjiu
wireless AP;abnormal data recognition;data warehouse;IOT
title A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy Compression
title_full A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy Compression
title_fullStr A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy Compression
title_full_unstemmed A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy Compression
title_short A Construction Method of Wireless AP Data Warehouse based on Anomaly Identification and Lossy Compression
title_sort construction method of wireless ap data warehouse based on anomaly identification and lossy compression
topic wireless AP;abnormal data recognition;data warehouse;IOT
url http://www.gtxyj.com.cn/thesisDetails#10.13756/j.gtxyj.2022.05.013
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