IP Library Granted Patent US 11,513,718
Granted Patent B2
US 11,513,718 · App. 17/161,298 · Granted Nov 29, 2022

Method, electronic device and computer program product for configuring buffer size associated with backup threads

Inventors: Jie Liu (Chengdu, CN); Qin Liu (Chengdu, CN)
Assignee: EMC IP Holding Company LLC
G06F3/065G06F3/067G06F3/0619G06F3/0653G06F3/0656G06N3/04H04L41/082H04L41/16H04L67/1097H04L67/01
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Quick Facts
Patent No.
US 11,513,718
App. No.
17/161,298
Granted
Nov 29, 2022
Kind
B2
Abstract

A method, electronic device, and computer readable medium for managing a backup system is disclosed. The method includes acquiring a state of the backup system. The backup system includes a backup server and at least one backup client terminal, the backup server using multiple threads to back up data from the at least one backup client terminal to a persistent storage device via a buffer. The method also includes determining a reward score corresponding to the state of the backup system and determining configuration information for the backup system based on the state and the reward score of the backup system. The configuration information indicating at least one of the number of the multiple threads and the size of the buffer. The number of writing threads and the size of the buffer for the persistent storage device may be dynamically adjusted based on the state of the backup system.

Claims (71)

1. A method for managing a backup system, comprising:

acquiring a state of a backup system, wherein the backup system comprises a backup server and at least one backup client terminal, the backup server using multiple threads to back up data from the at least one backup client terminal to a persistent storage device via a buffer, wherein the backup server comprises multiple backup tasks for executing data backup on the at least one backup client terminal, and the state of the backup system indicates an execution time and an execution result of last execution of each of the multiple backup tasks, and determining the reward score comprises:

determining the reward score based on the execution time and the execution result of the last execution of each of the multiple backup tasks;

determining a reward score corresponding to the state of the backup system; and

determining configuration information for the backup system based on the state and the reward score of the backup system, the configuration information indicating at least one of the multiple threads and the size of the buffer.

2. The method according to claim 1 , wherein the state of the backup system comprises at least one of the following:

a server state of the backup server;

a client terminal state of each of the at least one backup client terminal; and

a network state of a network for communication between the at least one backup client terminal and the backup server.

3. The method according to claim 2 , wherein the server state comprises at least one of the following:

a backup success rate of the backup server;

storage usage condition of the persistent storage device;

CPU usage condition of the backup server;

memory usage condition of the backup server; and

input/output operation usage condition for the persistent storage device.

4. The method according to claim 2 , wherein the client terminal state of the backup client terminal comprises at least one of the following:

the number of files to be backed up at the backup client terminal;

the size of data to be backed up at the backup client terminal;

an average execution time for backup tasks of the backup client terminal; and

a success rate for the backup tasks of the backup client terminal.

5. The method according to claim 2 , wherein the network state comprises at least one of the following:

a round-trip delay of the network; and

an available network bandwidth of the network.

6. The method according to claim 1 , wherein determining the configuration information comprises:

determining the configuration information using a neural network and based on the state and the reward score of the backup system.

7. The method according to claim 6 , wherein the neural network comprises an actor network and a critic network, the actor network comprising an actor evaluation network and an actor target network, the critic network comprising a critic evaluation network and a critic target network, and the neural network further comprises a first sub-network for updating a first network parameter of the actor evaluation network and a second sub- network for updating a second network parameter of the critic evaluation network, and wherein

the actor evaluation network is configured to determine the configuration information for the backup system at a current moment based on the state of the backup system acquired at the current moment and the first network parameter of the actor evaluation network, the configuration information being provided to the critic evaluation network;

the actor target network is configured to determine target configuration information for the backup system at the current moment based on the state of the backup system acquired at the current moment, the target configuration information being provided to the critic target network;

the critic evaluation network is configured to determine an assessment for the configuration information based on the state of the backup system acquired at the current moment and the second network parameter of the critic evaluation network, the assessment being provided to the first sub-network and the second sub-network;

the critic target network is configured to determine a target assessment for the target configuration information based on the state of the backup system acquired at the current moment, the target assessment being provided to the second sub-network;

the first sub-network is configured to update the first network parameter based on the assessment; and

the second sub-network is configured to update the second network parameter based on a difference between the assessment and the target assessment as well as the reward score.

8. The method according to claim 1 , wherein the persistent storage device comprises a solid state disk.

9. An electronic device, comprising:

at least one processing unit; and

at least one memory which is coupled to the at least one processing unit and stores instructions for execution by the at least one processing unit, wherein the instructions, when executed by the at least one processing unit, cause the electronic device to perform actions comprising:

acquiring a state of a backup system, wherein the backup system comprises a backup server and at least one backup client terminal, the backup server using multiple threads to back up data from the at least one backup client terminal to a persistent storage device via a buffer, wherein the backup server comprises multiple backup tasks for executing data backup on the at least one backup client terminal, and the state of the backup system indicates an execution time and an execution result of last execution of each of the multiple backup tasks, and determining the reward score comprises:

determining the reward score based on the execution time and the execution result of the last execution of each of the multiple backup tasks;

determining a reward score corresponding to the state of the backup system; and

determining configuration information for the backup system based on the state and the reward score of the backup system, the configuration information indicating at least one of the multiple threads and the size of the buffer.

10. The electronic device according to claim 9 , wherein determining the configuration information comprises:

determining the configuration information using a neural network and based on the state and the reward score of the backup system.

11. The electronic device according to claim 10 , wherein the neural network comprises an actor network and a critic network, the actor network comprising an actor evaluation network and an actor target network, the critic network comprising a critic evaluation network and a critic target network, and the neural network further comprises a first sub-network for updating a first network parameter of the actor evaluation network and a second sub-network for updating a second network parameter of the critic evaluation network, and wherein

the actor evaluation network is configured to determine the configuration information for the backup system at a current moment based on the state of the backup system acquired at the current moment and the first network parameter of the actor evaluation network, the configuration information being provided to the critic evaluation network;

the actor target network is configured to determine target configuration information for the backup system at the current moment based on the state of the backup system acquired at the current moment, the target configuration information being provided to the critic target network;

the critic evaluation network is configured to determine an assessment for the configuration information based on the state of the backup system acquired at the current moment and the second network parameter of the critic evaluation network, the assessment being provided to the first sub-network and the second sub-network;

the critic target network is configured to determine a target assessment for the target configuration information based on the state of the backup system acquired at the current moment, the target assessment being provided to the second sub-network;

the first sub-network is configured to update the first network parameter based on the assessment; and

the second sub-network is configured to update the second network parameter based on a difference between the assessment and the target assessment as well as the reward score.

12. The electronic device according to claim 9 , wherein the persistent storage device comprises a solid state disk.

13. The electronic device according to claim 9 , wherein the state of the backup system comprises at least one of the following:

a server state of the backup server;

a client terminal state of each of the at least one backup client terminal; and

a network state of a network for communication between the at least one backup client terminal and the backup server.

14. The electronic device according to claim 13 , wherein the server state comprises at least one of the following:

a backup success rate of the backup server;

storage usage condition of the persistent storage device;

CPU usage condition of the backup server;

memory usage condition of the backup server; and

input/output operation usage condition for the persistent storage device.

15. The electronic device according to claim 13 , wherein the network state comprises at least one of the following:

a round-trip delay of the network; and

an available network bandwidth of the network.

16. A non-transitory computer readable medium comprising instructions that, when executed by a processor, perform a method for managing a backup system, the method comprising:

acquiring a state of a backup system, wherein the backup system comprises a backup server and at least one backup client terminal, the backup server using multiple threads to back up data from the at least one backup client terminal to a persistent storage device via a buffer, wherein the backup server comprises multiple backup tasks for executing data backup on the at least one backup client terminal, and the state of the backup system indicates an execution time and an execution result of last execution of each of the multiple backup tasks, and determining the reward score comprises:

determining the reward score based on the execution time and the execution result of the last execution of each of the multiple backup tasks;

determining a reward score corresponding to the state of the backup system; and

determining configuration information for the backup system based on the state and the reward score of the backup system, the configuration information indicating at least one of the multiple threads and the size of the buffer.

17. The non-transitory computer readable medium according to claim 16 , wherein

determining the configuration information comprises:

determining the configuration information using a neural network and based on the state and the reward score of the backup system.

Assignments (9)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (055479/0342) Recorded Jun 10, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: EMC IP HOLDING COMPANY LLC; DELL PRODUCTS L.P.
Reel/Frame 062021/0460 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (055479/0051) Recorded Jun 10, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: EMC IP HOLDING COMPANY LLC; DELL PRODUCTS L.P.
Reel/Frame 062021/0663 →
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (056136/0752) Recorded Jun 10, 2022
From: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
To: EMC IP HOLDING COMPANY LLC; DELL PRODUCTS L.P.
Reel/Frame 062021/0771 →
RELEASE OF SECURITY INTEREST AT REEL 055408 FRAME 0697 Recorded Nov 2, 2021
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: DELL PRODUCTS L.P.; EMC IP HOLDING COMPANY LLC
Reel/Frame 058001/0553 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 29, 2021
From: LIU, JIE; LIU, QIN
To: EMC IP HOLDING COMPANY LLC
Reel/Frame 055748/0145 →
SECURITY INTEREST Recorded Mar 3, 2021
From: EMC IP HOLDING COMPANY LLC; DELL PRODUCTS L.P.
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
Reel/Frame 056136/0752 →
SECURITY INTEREST Recorded Mar 3, 2021
From: EMC IP HOLDING COMPANY LLC; DELL PRODUCTS L.P.
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
Reel/Frame 055479/0051 →
SECURITY INTEREST Recorded Mar 3, 2021
From: EMC IP HOLDING COMPANY LLC; DELL PRODUCTS L.P.
To: THE BANK OF NEW YORK MELLON TRUST COMPANY, N.A., AS NOTES COLLATERAL AGENT
Reel/Frame 055479/0342 →
SECURITY AGREEMENT Recorded Feb 25, 2021
From: EMC IP HOLDING COMPANY LLC; DELL PRODUCTS L.P.
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 055408/0697 →
Priority Claims (1)
CN 202010965809.3 · Sep 15, 2020 · national
Continuity (1)
Related Publication 20220083227A1 · Mar 17, 2022
Cited By (1)
US 12,499,003