Minimizing overhead over-provisioning costs in machine configurations

Patent metadata

Field	Value
Publication number	US-2016291990-A1
Application number	US-201514674902-A
Country	US
Kind code	A1
Filing date	Mar 31, 2015
Priority date	Mar 31, 2015
Publication date	Oct 6, 2016
Grant date	—

Abstract

A method and apparatus for substantially minimizing overhead over-provisioning costs in machine configurations is disclosed. The method involves the steps of: clustering a plurality of given machine configurations into a quantity of clusters less than or equal to a pre-specified amount; determining a respective dominant provisioning machine configuration for each cluster of the quantity of clusters; and determining an overall over-provisioning resource cost associated with the respective quantity of clusters and associated respective dominant provisioning machine configurations; and assigning to a mapping function the respective associated dominant provisioning machine configuration of each respective cluster of the quantity of clusters as the target for the given machine configurations of each respective cluster of the quantity of clusters. The method for substantially minimizing overhead over-provisioning costs in machine configurations provides advantages over systems known in the art by allowing minimization of average overhead due to over-provisioning costs as well as minimizing the maximum overhead due to over-provisioning costs.

First claim

What is claimed is:

1 . A method of identifying a set of pre-provisioned machine configurations and an associated mapping function for mapping each of a plurality of given machine configurations to said set of pre-provisioned machine configurations so as to produce a resource cost for said set of pre-provisioned machine configurations, the method comprising the steps of:
clustering said plurality of given machine configurations into a quantity of clusters less than or equal to a pre-specified amount; determining a respective dominant provisioning machine configuration for each cluster of said quantity of clusters; and determining an overall over-provisioning resource cost associated with the respective quantity of clusters and associated respective dominant provisioning machine configurations; and assigning to said mapping function the respective associated dominant provisioning machine configuration of each respective cluster of said quantity of clusters as the target for the given machine configurations of each respective cluster of said quantity of clusters.

2 . A method as claimed in claim 1 wherein
said resource cost is selected from the group consisting of an average cost, a maximum cost, and a maximum cost quantified using ratio points.

3 . A method as claimed in claim 2 further comprising the steps of:
varying said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
using that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

4 . A method as claimed in claim 2 wherein
said set of respective dominant provisioning machine configurations is selected from a pre-provisioned set of provisioned machine configurations.

5 . A method as claimed in claim 4 further comprising the steps of:
varying said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
using that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

6 . A method as claimed in claim 4 further comprising the steps of:
associating an operating cost with each of said given set of provisioned machine configurations; and
including said operating costs in the determining step.

7 . A method as claimed in claim 6 further comprising the steps of
varying said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
using that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

8 . A method as claimed in claim 1 wherein
varying said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
using that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

9 . A method as claimed in claim 1 wherein
said set of respective dominant provisioning machine configurations is selected from a pre-provisioned set of provisioned machine configurations.

10 . A method as claimed in claim 9 further comprising the steps of:
varying said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
using that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

11 . A method as claimed in claim 9 further comprising the steps of:
associating an operating cost with each of said given set of provisioned machine configurations; and
including said operating costs in the determining step.

12 . A method as claimed in claim 11 further comprising the steps of
varying said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
using that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

13 . A method as claimed in claim 1 further comprising the steps of:
associating an operating cost with each of said given set of provisioned machine configurations; and
including said operating costs in the determining step.

14 . A method as claimed in claim 13 further comprising the steps of
varying said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
using that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

15 . An apparatus for identifying a set of pre-provisioned machine configurations and an associated mapping function for mapping each of a plurality of given machine configurations to said set of pre-provisioned machine configurations so as to produce a resource cost for said set of pre-provisioned machine configurations, the apparatus comprising:
a data storage; and a processor communicatively connected to the data storage, the processor being configured to: cluster said plurality of given machine configurations into a quantity of clusters less than or equal to a pre-specified amount; determine a respective dominant provisioning machine configuration for each cluster of said quantity of clusters; and determine an overall over-provisioning resource cost quantified using point ratios associated with the respective quantity of clusters and associated respective dominant provisioning machine configurations; and assign to said mapping function the respective associated dominant provisioning machine configuration of each respective cluster of said quantity of clusters as the target for the given machine configurations of each respective cluster of said quantity of clusters.

16 . An apparatus as claimed in claim 15 wherein
said resource cost is selected from the group consisting of an average cost, a maximum cost, and a maximum cost quantified using ratio points.

17 . An apparatus as claimed in claim 16 wherein the processor is further configured to
vary said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
use that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

18 . An apparatus as claimed in claim 16 wherein
said set of respective dominant provisioning machine configurations is selected from a pre-provisioned set of provisioned machine configurations.

19 . An apparatus as claimed in claim 18 wherein the processor is further configured to
vary said quantity of clusters to determine a quantity less than said pre-specified amount for which said overall over-provisioning resource cost is substantially minimized; and
use that quantity of clusters for which said overall over-provisioning resource cost is substantially minimized in the assigning step.

20 . An apparatus as claimed in claim 18 wherein the proce

Assignees

• Alcatel Lucent Usa Inc

Inventors

• Bhatia Randeep S
• Gupta Bhawna
• Rosensweig Elisha

Classifications

• G06F9/5011

  the resources being hardware resources other than CPUs, Servers and Terminals · CPC title

• G06F9/44505 Primary

  Configuring for program initiating, e.g. using registry, configuration files · CPC title

• G06F2009/45562

  Creating, deleting, cloning virtual machine instances · CPC title

• G06F9/45558

  Hypervisor-specific management and integration aspects · CPC title