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

Abstract

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.

Keywords

• wireless ap
• abnormal data recognition
• data warehouse
• iot