EFFECTIVELY OPERATING AND ADJUSTING AN INFRASTRUCTURE FOR SUPPORTING DISTRIBUTED APPLICATIONS

• US 20160344597A1
• Filed: 05/22/2015
• Published: 11/24/2016
• Est. Priority Date: 05/22/2015
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Liu, Hongqiang, Calder, Matthew J., Zhang, Ming, Padhye, Jitendra D., Mahajan, Ratul, Akella, Srinivasa Aditya, Viswanathan, Raajay
• Application Number:
  US14/720,653
• Publication Number:
  US 20160344597A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 9/50 Allocation of resources, e.g. of the central processing unit [CPU]
• CPC Class Codes: G06F 9/505 considering the load
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: H04L 41/0896 Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 41/5096 wherein the managed service relates to distributed or central networked applications
• CPC Class Codes: H04L 43/0817 by checking functioning

Abstract

A facility for managing distributed system for delivering online services is described. For each of a plurality of distributed system components of the first type, the facility receives operating statistics for the infrastructure component of the first type. For each of a plurality of distributed system components of a second type, the facility receives operating statistics for the infrastructure component of the second type. The facility uses the received operating statistics for distributed system components of the first and second types to generate a model predicting operating statistics for the distributed system for a future period of time.

Claims

1. A computing system for controlling the operation of an infrastructure for delivering online services, comprising:

a prediction subsystem configured to apply a stochastic linear program model to predict operating metrics for heterogeneous components of the infrastructure for a future period of time based upon operating metrics for a past period of time; and

an adaptation subsystem configured to use the operating metrics predicted by the modeling subsystem as a basis for reallocating resources provided by the components of the infrastructure to different portions of a load on the infrastructure.

2. The computing system of claim 1, further comprising a modeling subsystem configured to generate the model applied by the modeling subsystem.

3. The computing system of claim 1 wherein the applied model utilizes a second-order cone program.

4. The computing system of claim 1, further comprising a resource variation subsystem configured to use the operating metrics predicted by the prediction subsystem as a basis for adding and removing components of the infrastructure.

5. The computing system of claim 1 wherein the adaptation subsystem is configured to use the operating metrics predicted by the prediction subsystem as a basis for reallocating resources provided by the components of the infrastructure to different portions of a load on the infrastructure on a periodic basis.

6. The computing system of claim 1 wherein the prediction subsystem predicts operating metrics as a function of time.

7. The computing system of claim 1 wherein the adaptation subsystem is configured to reallocate resources to different portions of the load on the infrastructure in units including connections having creation times, and wherein the reallocation affects only connections created subsequent to the reallocation.

8. The computing system of claim 1 wherein the prediction subsystem is configured to apply the model in a manner to determine overall prediction error by performing statistical multiplexing on error distributions affecting different aspects of the infrastructure.

9. The computing system of claim 1 wherein the adaptation subsystem is further configured to use the operating metrics predicted by the modeling subsystem as a basis for selecting portions of demand on the infrastructure to reject.

10. A computer-readable medium having contents configured to cause a computing system to, in order to manage a distributed system for delivering online services:

from each of a plurality of distributed system components of a first type, receive operating statistics for the distributed system component of the first type;

from each of a plurality of distributed system components of a second type distinct from the first type, receive operating statistics for the component of the second type; and

use the received operating statistics for distributed system components of the first and second types to generate a model predicting operating statistics for the distributed system for a future period of time.

11. The computer-readable medium of claim 10 wherein the infrastructure components of the first type are wide area network entry points.

12. The computer-readable medium of claim 10 wherein the infrastructure components of the first type are data centers.

13. The computer-readable medium of claim 10 wherein the infrastructure components of the first type are wide area network links.

14. A computer-readable medium storing an online services infrastructure model data structure, the data structure comprising:

data representing a stochastic system of linear equations whose solution yields a set of weights specifying;

for each of a plurality of infrastructure resource types,

for each of a plurality of combinations of (1) a group of client devices with (2) one of a plurality of infrastructure resource instances of the infrastructure resource type,

the extent to which the group of client devices should be served by the infrastructure resource instance during a future period of time, the linear equations of this stochastic system being based on operating measurements of the infrastructure during a past period of time.

15. The computer-readable medium of claim 14 wherein the stochastic system of linear equations comprises a stochastic linear program model.

16. The computer-readable medium of claim 14 wherein the stochastic system of linear equations comprises a second-order cone program.

17. The computer-readable medium of claim 14 wherein the stochastic system of linear equations further determines overall prediction error by performing statistical multiplexing on error distributions affecting different aspects of the infrastructure.

18. The computer-readable medium of claim 17 wherein the weights yielded by the solution of the stochastic system of linear equations seek to limit the likelihood that the overall prediction error will cause a utilization rate for any infrastructure resource instance will exceed a threshold level.