Watchdog timer for a multi-stage computing environment

Patent metadata

Field	Value
Publication number	US-11080085-B2
Application number	US-201816221912-A
Country	US
Kind code	B2
Filing date	Dec 17, 2018
Priority date	Dec 17, 2018
Publication date	Aug 3, 2021
Grant date	Aug 3, 2021

Abstract

A computer system manages multi-stage transactions. A plurality of response time values of transaction components for a plurality of transactions are received. Two or more transactions from the plurality of transactions are selected, wherein a quantity of the selected transactions is equal to a number of the transaction components in the plurality of transactions. Eigenvalues are calculated from the response time values for the selected transactions. The selected transactions are determined to have timed out by processing the eigenvalues using a machine learning classifier. Embodiments of the present invention further include a method and program product for managing multi-stage transactions in substantially the same manner described above.

First claim

The invention claimed is:

1. A computer-implemented method of managing multi-stage transactions, comprising:
receiving a plurality of response time values of transaction components for a plurality of transactions;
selecting two or more transactions from the plurality of transactions, wherein a quantity of the selected transactions is equal to a number of the transaction components in the plurality of transactions;
calculating eigenvalues from the response time values for the selected transactions, wherein each row of a square matrix for calculating the eigenvalues comprises response time values from a same transaction; and
determining that the selected transactions have timed out by processing the eigenvalues using a machine learning classifier.

2. The computer-implemented method of claim 1 , wherein the selected transactions are consecutive transactions.

3. The computer-implemented method of claim 1 , wherein the machine learning classifier is a naive Bayes classifier.

4. The computer-implemented method of claim 1 , further comprising:
interrupting the selected transactions in response to determining that the selected transactions have timed out.

5. The computer-implemented method of claim 1 , wherein the plurality of transactions transact in a serverless computing environment.

6. A computer system for managing multi-stage transactions, the computer system comprising:
one or more computer processors;
one or more computer readable storage media;
program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising instructions to:
receive a plurality of response time values of transaction components for a plurality of transactions;
select two or more transactions from the plurality of transactions, wherein a quantity of the selected transactions is equal to a number of the transaction components in the plurality of transactions;
calculate eigenvalues from the response time values for the selected transactions, wherein each row of a square matrix for calculating the eigenvalues comprises response time values from a same transaction; and
determine that the selected transactions have timed out by processing the eigenvalues using a machine learning classifier.

7. The computer system of claim 6 , wherein the selected transactions are consecutive transactions.

8. The computer system of claim 6 , wherein the machine learning classifier is a naive Bayes classifier.

9. The computer system of claim 6 , further comprising instructions to:
interrupt the selected transactions in response to determining that the selected transactions have timed out.

10. The computer system of claim 6 , wherein the plurality of transactions transact in a serverless computing environment.

11. A computer program product for managing multi-stage transactions, the computer program product comprising one or more computer readable storage media collectively having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to:
receive a plurality of response time values of transaction components for a plurality of transactions;
select two or more transactions from the plurality of transactions, wherein a quantity of the selected transactions is equal to a number of the transaction components in the plurality of transactions;
calculate eigenvalues from the response time values for the selected transactions, wherein each row of a square matrix for calculating the eigenvalues comprises response time values from a same transaction; and
determine that the selected transactions have timed out by processing the eigenvalues using a machine learning classifier.

12. The computer program product of claim 11 , wherein the selected transactions are consecutive transactions.

13. The computer program product of claim 11 , wherein the machine learning classifier is a naive Bayes classifier.

14. The computer program product of claim 11 , further comprising instructions to:
interrupt the selected transactions in response to determining that the selected transactions have timed out.

15. The computer program product of claim 11 , wherein the plurality of transactions transact in a serverless computing environment.

Assignees

• IBM

Inventors

• Brady Simon
• Zolotow Clea A
• Hollywood Barry
• Floes Jørgen E
• Soares Pedro
• Xouzafeiris Anastasios

Classifications

• G06F11/0757 Primary

  by exceeding a time limit, i.e. time-out, e.g. watchdogs · CPC title

• G06F9/466 Primary

  Transaction processing · CPC title

• G06F18/24155

  Bayesian classification · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06N20/00

  Machine learning · CPC title