SYSTEM AND METHOD FOR MANAGEMENT OF CLOUD-BASED SYSTEMS

• US 20160020964A1
• Filed: 09/29/2015
• Published: 01/21/2016
• Est. Priority Date: 02/06/2012
• Status: Active Grant

• Current Assignee: Alcatel-Lucent USA, Inc. (Nokia Corporation)
• Original Assignee: Deepfield Networks Inc. (Nokia Corporation)
• Inventors: Eggleston, Joseph E., Labovitz, Craig H.
• Granted Patent: US 10,033,649 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04L 41/00 Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
• CPC Class Codes: H04L 41/12 Discovery or management of network topologies
• CPC Class Codes: H04L 41/40 using virtualisation of network functions or resources, e.g. SDN or NFV entities
• CPC Class Codes: H04L 41/5009 Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF]
• CPC Class Codes: H04L 41/508 based on type of value added network service under agreement
• CPC Class Codes: H04L 43/026 using flow identification
• CPC Class Codes: H04L 43/062 related to network traffic
• CPC Class Codes: H04L 43/0882 Utilisation of link capacity
• CPC Class Codes: H04L 47/10 Flow control; Congestion control
• CPC Class Codes: H04L 47/2441 relying on flow classification, e.g. using integrated services [IntServ]
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46

Abstract

System and method for reporting usage of a network infrastructure includes obtaining a map that includes at least one flow-mapping that correlates a flow feature with a service and that correlates a flow feature with an endpoint type, wherein the endpoint types include at least a subscriber type and a service type; at a first computer, receiving flow telemetry of a network infrastructure, the flow telemetry representing at least the destination and source attributes for network traffic in the flow telemetry; categorizing the flow telemetry into at least a subscriber flow category based on the source and destination endpoint types of the traffic; for subscriber flow telemetry of a subscriber, processing the subscriber flow telemetry into at least one flow feature; identifying at least one service to attribute to at least a portion of the subscriber flow telemetry, the service identified through the processed flow feature and a flow-mapping.

Claims

1. A method comprising:

compiling a map module that comprises;

retrieving component addresses of services, and adding the component addresses to the map module as flow features correlated to a service, and

at a first client, automating traffic of a first service and adding service components identified in traffic of the first client as flow features correlated to the first service in the map;

collecting flow telemetry of a network;

applying the map module to processing of flow telemetry; and

deriving service traffic breakdown of the flow telemetry.

2. The method of claim 1, wherein compiling a map module further comprises, determining subscriber addresses and setting a flow feature of the map module for the subscriber correlated addresses.

3. The method of claim 2, wherein compiling a map module further comprises, determining services that correspond to an Internet protocol (IP) address from the domain name service (DNS) network telemetry and setting a flow feature for the services that correspond to an IP address.

4. The method of claim 3, further comprising categorizing flow telemetry into at least subscriber flow telemetry, wherein the map module is applied to processing of flow telemetry of each subscriber, and wherein applying the map module to processing of flow telemetry comprises identifying component usage patterns correlated with a service.

5. The method of claim 4, wherein component usage patterns comprises sequence component usage patterns and proportional component usage patterns.

6. The method of claim 2, further comprising at a second client with differing network locality compared to the first client, simulating traffic of the first service and adding service components identified in traffic of the second client as flow features correlated to the first service in the map.

7. The method of claim 6, wherein the second client is simulated through a virtual private network connection.

8. A system comprising:

one or more computers programmed to perform operations comprising;

compiling a map module that comprises;

retrieving component addresses of services, and adding the component addresses to the map module as flow features correlated to a service,

and

at a first client, automating traffic of a first service and adding service components identified in traffic of the first client as flow features correlated to the first service in the map;

collecting flow telemetry of a network;

applying the map module to processing of flow telemetry; and

deriving service traffic breakdown of the flow telemetry.

9. The system of claim 8, wherein compiling a map module further comprises, determining subscriber addresses and setting a flow feature of the map module for the subscriber correlated addresses.

10. The system of claim 9, wherein compiling a map module further comprises, determining services that correspond to an Internet protocol (IP) address from the domain name service (DNS) network telemetry and setting a flow feature for the services that correspond to an IP address.

11. The system of claim 10, further comprising categorizing flow telemetry into at least subscriber flow telemetry, wherein the map module is applied to processing of flow telemetry of each subscriber, and wherein applying the map module to processing of flow telemetry comprises identifying component usage patterns correlated with a service.

12. The system of claim 11, wherein component usage patterns comprises sequence component usage patterns and proportional component usage patterns.

13. The system of claim 9, further comprising at a second client with differing network locality compared to the first client, simulating traffic of the first service and adding service components identified in traffic of the second client as flow features correlated to the first service in the map.

14. The system of claim 13, wherein the second client is simulated through a virtual private network connection.

15. A data structure embodied in a computer-readable medium, the data structure comprising:

a plurality of component addresses as flow features correlated to a service, and

one or more components identified in traffic of a client as flow features correlated to the service.