Method and system for dynamic upgrade predictions for a multi-component product

Patent metadata

Field	Value
Publication number	US-11474803-B2
Application number	US-201916730310-A
Country	US
Kind code	B2
Filing date	Dec 30, 2019
Priority date	Dec 30, 2019
Publication date	Oct 18, 2022
Grant date	Oct 18, 2022

Abstract

Techniques are disclosed for generating a dynamic upgrade prediction. The prediction includes generating an initial upgrade prediction for an upgrade to be performed on a subset of component nodes; performing a real time progress review, using a centralized management node, of the upgrade, wherein each of the component nodes includes a number of stages; performing an upgrade duration comparison between the initial upgrade prediction and a real time upgrade time for a subset of the stages; and generating an updated upgrade prediction for the multi-component product upgrade based on the comparison between the initial upgrade prediction and the real time upgrade time.

First claim

What is claimed is:

1. A computer implemented method of generating a dynamic upgrade prediction comprising:
generating an initial upgrade prediction for a predicted time of an upgrade to be performed on a subset of a plurality of component nodes of a multi-component product;
performing a real time progress review, using a centralized management node, of the upgrade, wherein each of the plurality of component nodes includes a plurality of stages;
performing an upgrade duration comparison between the initial upgrade prediction and a real time upgrade time for a subset of the plurality of stages; and
generating an updated upgrade prediction for the upgrade of the multi-component product based on the upgrade duration comparison between the initial upgrade prediction and the real time upgrade time, wherein generating the updated upgrade prediction varies based on whether the upgrade duration comparison indicates that the initial upgrade prediction was an overestimation or an underestimate as compared to the real time upgrade time,
wherein the initial upgrade prediction, Tinit, is generated according to:

T
init

=

∑

m
=
1

M

⁢

∑

n
=
1

N
⁡

[
m
]

⁢

T
⁡

[
m
]

⁡

[
n
]

,

wherein M is a number of component nodes of the multi-component product, each component node has N[m] stages, and T[m][n] is an estimated time expected to be spent on a stage n for a component node m, and
wherein the updated upgrade prediction is dynamically increased when the real time progress review indicates that one of the plurality of stages spends more time than the initial upgrade prediction.

2. The computer implemented method as in claim 1 , wherein only a subset of the plurality of component nodes of the multi-component product are being upgraded, and the initial upgrade prediction is generated based on an analysis of the subset of the plurality of component nodes.

3. The computer implemented method as in claim 1 , wherein the updated upgrade prediction, Testimate, is generated according to:

T
estimate

=

⁢

{

T
init

-

∑

m
=
1

x

⁢

∑

n
=
1

y

⁢

T
⁡

[
m
]

⁡

[
n
]

+

T
⁡

[
x
]

⁡

[
y
]

-

Δ
⁢

⁢

t
xy

,

Δ
⁢

⁢

t
xy

≤

T
⁡

[
x
]

⁡

[
y
]

T
init

-

∑

m
=
1

Assignees

• Emc Ip Holding Co Llc

Inventors

• Su Lihui
• Zhang Scott
• Liang Zak
• Morton James
• Che Roger Hongyi

Classifications

• G06Q30/0282 Primary

  Rating or review of business operators or products · CPC title

• G06F8/65 Primary

  Updates (security arrangements therefor G06F21/57) · CPC title

• G06N5/04

  Inference or reasoning models · CPC title