AUTOMATIC HEALTH-CHECK METHOD AND DEVICE FOR ON-LINE SYSTEM

• US 20140372602A1
• Filed: 12/13/2012
• Published: 12/18/2014
• Est. Priority Date: 12/13/2011
• Status: Active Grant

• Current Assignee: China Unionpay Company Limited
• Original Assignee: China Unionpay Company Limited
• Inventors: Ji, Naigeng, Fu, Yisheng, Tian, Longhui, Wu, Jianzhao
• Granted Patent: US 9,774,514 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: G06F 11/3055 Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available error or fault processing without redundancy G06F11/0703; error detection or correction by redundancy in data representation G06F11/08; error detection or correction by redundancy in operation G06F11/14; error detection or correction by redundancy in hardware G06F11/16
• CPC Class Codes: G06F 11/3452 Performance evaluation by statistical analysis
• CPC Class Codes: H04L 43/0847 Transmission error
• CPC Class Codes: H04L 43/16 Threshold monitoring

Abstract

The invention provides an automatic health check method for on-line system, comprising the following steps: receiving current status data of the on-line system from the on-line system; updating historical status statistical data based on the current status data, wherein the historical status statistical data is a statistical result for the status data of the on-line system until a previous moment from the moment when the on-line system starts to operate; transmitting the updated historical status statistical data to the on-line system; and the on-line system determining whether it is operating normally according to the updated historical status statistical data. In addition, the present invention correspondingly provides an automatic health check apparatus for on-line system. The method and apparatus according to the present invention can provide an effective and reliable health check mechanism for an on-line system such as bank POS transaction system.

Claims

1. An automatic health check method for an on-line system, characterized by comprising the following steps:

receiving current status data of the on-line system from the on-line system;

updating historical status statistical data based on the current status data, wherein the historical status statistical data is a statistical result for the status data of the on-line system until a previous moment from the moment when the on-line system starts to operate;

transmitting the updated historical status statistical data to the on-line system; and

the on-line system determining whether it is operating normally according to the updated historical status statistical data.

2. The method according to claim 1, characterized in that updating historical status statistical data based on the current status data comprises:

comparing the current status data with the historical status statistical data;

determining whether the current status data is abnormal data according to the result of comparison;

maintaining the historical status statistical data unchanged when the current status data is determined as abnormal data; and

incorporating the current status data into the historical status statistical data when the current status data is not determined as abnormal data.

3. The method according to claim 2, characterized in that incorporating the current status data into the historical status statistical data comprises incorporating the current status data into the historical status statistical data according to the following formula:

F_t=α

X_t+(1-α

)F_t-1

wherein X_t represents the current status data;

F_t represents the current historical status statistical data;

F_t-1 represents the historical status statistical data at the previous moment; and

a is a weighting constant, the value range of which is (0.5, 1].

4. The method according to claim 2, characterized in that incorporating the current status data into the historical status statistical data comprises calculating an average of all periods for the current status data and the historical status statistical data.

5. The method according to claim 2, characterized in that comparing the current status data with the historical status statistical data comprises calculating a discrepancy rate between the current status data and the historical status statistical data, wherein the discrepancy rate is a ratio of the difference between the current status value and the historical status statistical value to the historical status statistical value.

6. The method according to claim 5, characterized in that determining whether the current status data is abnormal data according to the result of comparison comprises determining the current status data as abnormal data when the discrepancy rate is larger than a predetermined threshold.

7. The method according to claim 1, characterized in that the current status data is based on a single transaction on a process in the on-line system or multiple transactions on a process in the on-line system.

8. The method according to claim 1, characterized in that the status data of the on-line system is occurrence rate of error code, processing time for a single transaction on a process in the on-line system, idle time of the process or the number of pending tasks on the process.

9. The method according to claim 1, characterized in that the status data of the on-line system is the usage of disk space in the system or the usage of physical memory.

10. An automatic health check apparatus for an on-line system, characterized by comprising:

a historical status statistical database for storing historical status statistical data, the historical status statistical data is a statistical result for the status data of the on-line system until a previous moment from the moment when the on-line system starts to operate;

a status collecting module for receiving current status data of the on-line system from the on-line system;

a statistic analysis module for updating the historical status statistical data based on the current status data; and

a result feedback module for transmitting the updated historical status statistical data to the on-line system, wherein the on-line system determines whether it is operating normally according to the updated historical status statistical data.

11. The apparatus according to claim 10, characterized in that updating historical status statistical data based on the current status data comprises:

comparing the current status data with the historical status statistical data;

determining whether the current status data is abnormal data according to the result of comparison;

maintaining the historical status statistical data unchanged when the current status data is determined as abnormal data; and

incorporating the current status data into the historical status statistical data when the current status data is not determined as abnormal data.

12. The apparatus according to claim 11, characterized in that incorporating the current status data into the historical status statistical data comprises incorporating the current status data into the historical status statistical data according to the following formula:

F_t=α

X_t+(1-α

)F_t-1

wherein X_t represents the current status data;

F_t represents the current historical status statistical data;

F_t-1 represents the historical status statistical data at the previous moment; and

a is a weighting constant, the value range of which is of (0.5, 1].

13. The apparatus according to claim 11, characterized in that incorporating the current status data into the historical status statistical data comprises calculating an average of all periods for the current status data and the historical status statistical data.

14. The apparatus according to claim 11, characterized in that comparing the current status data with the historical status statistical data comprises calculating a discrepancy rate between the current status data and the historical status statistical data, wherein the discrepancy rate is a ratio of the difference between the current status value and the historical status statistical value to the historical status statistical value.

15. The apparatus according to claim 14, characterized in that determining whether the current status data is abnormal data according to the result of comparison comprises determining the current status data as abnormal data when the discrepancy rate is larger than a predetermined threshold.