Adaptive data packing

Patent metadata

Field	Value
Publication number	US-10887246-B2
Application number	US-201916261683-A
Country	US
Kind code	B2
Filing date	Jan 30, 2019
Priority date	Jan 30, 2019
Publication date	Jan 5, 2021
Grant date	Jan 5, 2021

Abstract

Techniques and a system for adaptive data packing are provided. In one example, a system includes a container component and a computing node component. The container component monitors one or more resources for container data in a network environment and determines variability data representative of a variability of the one or more resources for the container data during a period of time. The computing node component that selects a computing node in the network environment for particular container data based on the variability data.

First claim

What is claimed is:

1. A system, comprising:
a memory that stores computer executable components;
a processor that executes computer executable components stored in the memory, wherein the computer executable components comprise:
a container component that monitors one or more resources for container data in a network environment and determines variability data representative of a variability of the one or more resources for the container data during a period of time, wherein the variability data comprises a coefficient of variation associated with the one or more resources for the container data; and
a computing node component that selects a computing node in the network environment for particular container data based on the variability data.

2. The system of claim 1 , wherein the variability data is first variability data and the one or more resources are one or more first resources, and wherein the computing node component determines second variability data representative of a variability of one or more second resources for a set of computing nodes in the network environment during the period of time.

3. The system of claim 2 , wherein the computing node component selects the computing node in the network environment for the particular container data based on the first variability data and the second variability data.

4. The system of claim 2 , wherein the computing node component selects the computing node in the network environment for the particular container data based on an equalization measure of the first variability data and the second variability data.

5. The system of claim 2 , wherein the computing node component selects the computing node in the network environment for the particular container data based on a Euclidean distance between the first variability data and the second variability data.

6. The system of claim 2 , wherein the computing node component determines a coefficient of variation associated with the one or more second resources for the set of computing nodes.

7. The system of claim 1 , wherein the coefficient of variation represents a measure of variability of one or more needs for the one or more resources.

8. The system of claim 1 , wherein the computing node component selects the computing node to optimize resource usage in the network environment.

9. A computer-implemented method, comprising:
monitoring, by a system operatively coupled to a processor, one or more resources in a computing network during a period of time;
determining, by the system, variability data representative of a variability of the one or more resources during the period of time, wherein the variability data comprises a coefficient of variation associated with the one or more resources; and
selecting, by the system, a computing node in the computing network for container data based on the variability data.

10. The method of claim 9 , wherein the variability data is first variability data and the one or more resources are one or more first resources, and wherein the computer-implemented method further comprises:
determining, by the system, second variability data representative of a variability of one or more second resources for a set of computing nodes in the computing network during the period of time.

11. The method of claim 10 , wherein the computer-implemented method further comprises:
selecting, by the system, the computing node in the computing network for the container data based on the first variability data and the second variability data.

12. The method of claim 10 , wherein the computer-implemented method further comprises:
selecting, by the system, the computing node in the computing network for the container data based on an equalization measure of the first variability data and the second variability data.

13. The method of claim 10 , wherein the computer-implemented method further comprises:
selecting, by the system, the computing node in the computing network for the container data based on a Euclidean distance between the first variability data and the second variability data.

14. The method of claim 10 , wherein the computer-implemented method further comprises:
determining, by the system, a coefficient of variation associated with the one or more second resources for the set of computing nodes.

15. The method of claim 9 , wherein the selecting the computing node comprises optimizing resource usage in the computing network.

16. A computer program product for facilitating adaptive data packing, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
monitor, by the processor, one or more resources in a network environment during a period of time;
determine, by the processor, first variability data representative of a variability of one or more first resources during the period of time, wherein the first variability data comprises a coefficient of variation associated with the one or more first resources;
determine, by the processor, second variability data representative of a variability of one or more second resources for a set of computing nodes in the network environment during the period of time; and
select, by the processor, a computing node in the network environment for container data based on the first variability data and the second variability data.

17. The computer program product of claim 16 , wherein the program instructions are further executable by the processor to cause the processor to:
select, by the processor, the computing node in the network environment for the container data based on an equalization measure of the first variability data and the second variability data.

18. The computer program product of claim 16 , wherein the program instructions are further executable by the processor to cause the processor to:
select, by the processor, the computing node in the network environment for the container data based on a Euclidean distance between the first variability data and the second variability data.

19. The computer program product of claim 16 , wherein the
coefficient of variation represents a measure of variability of one or more needs for the one or more first resources.

20. The computer program product of claim 16 , wherein the program instructions are further executable by the processor to cause the processor to:
determine, by the processor, a coefficient of variation associated with the one or more second resources.

Assignees

• IBM

Inventors

• Tantawi Asser Nasreldin
• Steinder Malgorzata

Classifications

• H04L47/70 Primary

  Admission control; Resource allocation · CPC title

• H04L67/1097

  for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS] · CPC title

• H04L47/78 Primary

  Architectures of resource allocation · CPC title

• H04L67/10

  in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) · CPC title

• H04L43/08

  Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters · CPC title