Difference between revisions of "PMQ"

Revision as of 15:41, 5 March 2017

History

SUSIAccess 1.0

Advantech has been developing the SUSI API series since 2004 to create convenient management solutions for embedded applications. After the original security features of eSOS (a small embedded OS used to boot up a system when the major OS boot-up fails) were introduced in 2009, Advantech launched SUSIAccess in Q2 2011, incorporating the latest cloud computing concepts. This version enables users to remotely control, configure and manage, multiple terminal devices and data, as well as providing system maintenance, backup and recovery.

Trend Forecasting Monitor

Function

For sepecific device or sensor data(HDD Health, System CPU Usage and so on), RMM offers prediction function(Trend Forecasting Monitor). It can help users know abnormal data status as soon as possible to prevent some damages.Predictive Tyoe of Trend Forecasting Monitor are hourly averages of data, and they contain averages of current hour and even next 3 hours. 

Predictive Process

The first condiction is predictive object has at least the newest 48 history hourly averages in Database, and these samples are calculated by time-series prediction algorithm. Time-series prediction algorithm RMM adopts is Exponential Smoothing, and is based on APIs in Weka machinne learning java libary. By the above Process, it can produce values of prediction(averages of current hour and next 3 hours), and Trend Forecasting Monitor takes these values and the newest 3 history hourly averages to compare with hourly averages in yesterday. If there are significant differences between values of prediction and hourly averages in yesterday, the status of analytic result is "Potential Risk". If there are significant differences between the newest 3 history hourly averages and hourly averages in yesterday, the status is "Doubtful Risk". The standard of significant differences is based on Tukey's Range Test, and the formula is: [Q₁-3(Q₃-Q₁), Q3+3(Q₃-Q₁)].Q₁ and Q₃ are the lower and upper quartile of hourly averages in yesterday. If objects are in the above range, there are not significant differences between them., then we can call status of Object is "Normal". 

Predictive Result

Result for each object contains 3 parts: result status, status information and event record list. First, for result status. except "Potential Risk", "Doubtful Risk" and "Normal" in the above statement, there is a "Data Error" situation, and it means disable predicting because of some data problem. For instance, miss some data in the newest 48 hours or query data from database error. Second, according to result status, web UI will show corresponding information, and major statement is explain reason for status and give some suggestion to users.Final, event record list will show total records for significant change, then it can help users to trace initial time of abnormal data.