Allocating computing resources based upon geographic movement

• US 9,276,827 B2
• Filed: 03/15/2013
• Issued: 03/01/2016
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Voit, Eric A., Pruss, Richard M., McDowall, John E., Medved, Jan
• Primary Examiner(s): Tiv, Backhean
• Application Number:
  US13/843,435
• Publication Number:
  US 20140280898A1
• Time in Patent Office: 1,082 Days
• Field of Search: 709/224
• US Class Current: 1/1
• CPC Class Codes: H04L 43/026 using flow identification
• CPC Class Codes: H04L 43/028 by filtering
• CPC Class Codes: H04L 43/20 the monitoring system or the monitored elements being virtualised, abstracted or software-defined entities, e.g. SDN or NFV
• CPC Class Codes: H04L 45/38 Flow based routing
• CPC Class Codes: H04L 45/42 Centralised routing
• CPC Class Codes: H04L 45/64 using an overlay routing layer
• CPC Class Codes: H04L 45/70 Routing based on monitoring results
• CPC Class Codes: H04L 47/70 Admission control; Resource allocation
• CPC Class Codes: H04L 47/762 triggered by the network
• CPC Class Codes: H04L 47/781 Centralised allocation of resources
• CPC Class Codes: H04L 47/808 User-type aware
• CPC Class Codes: H04L 47/83 based on usage prediction
• CPC Class Codes: H04L 49/30 Peripheral units, e.g. input or output ports
• CPC Class Codes: H04L 61/00 Network arrangements, protocols or services for addressing or naming
• CPC Class Codes: H04L 61/103 across network layers, e.g. resolution of network layer into physical layer addresses or address resolution protocol [ARP]
• CPC Class Codes: H04L 61/4523 using lightweight directory access protocol [LDAP]
• CPC Class Codes: H04L 61/5014 using dynamic host configuration protocol [DHCP] or bootstrap protocol [BOOTP]
• CPC Class Codes: H04L 67/1097 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 Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/568 Storing data temporarily at an intermediate stage, e.g. caching
• CPC Class Codes: H04L 67/5681 : Pre-fetching or pre-delivering data based on network characteristics
• CPC Class Codes: H04W 4/02 : Services making use of location information
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 40/20 : based on geographic position or location
• CPC Class Codes: H04W 64/00 : Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Embodiments described herein use APIs on network devices in a SDN enabled network to monitor the network traffic flowing through the network devices and determine an identity of the client initiating the network traffic. Specifically, the APIs provide a user application with user credentials, IP addresses, MAC addresses, and other identifying information mined from the network flows. Once the identity is found, the application may identify the client'"'"'s current geographic location. The network devices may continue to monitor the network devices to identify any movement events associated with the client. In response to a movement event, the application may reallocate resources proximate to the new geographic location of the client.

Claims

1. A method for allocating resources based on geographic movement of a client, the method comprising:

determining a first geographic location of the client;

receiving identification data for identifying the client from at least one application programming interfaces (API) operating in a network device in a software-defined networking (SDN) enabled network, wherein the API identifies the identification data by filtering a network flow traversing an ingress port of the network device;

associating the network flow to a client ID using the identification data;

determining, based on the network flow, a second geographic location of the client, wherein the first and second geographic locations are different; and

allocating computing resources associated with the client ID in response to the client moving from the first geographic location to the second geographic location.

2. The method of claim 1, further comprising:

configuring an input filter on the network device for filtering the network flow using the API, the API abstracting a control plane of the network device to permit a remote user application to monitor and control data traffic traversing the network device, wherein the filtered data comprises predefined types of data that enable identification of the client ID.

3. The method of claim 2, wherein a plurality of network devices in the SDN enabled network each comprise a respective input filter and a respective monitoring API for monitoring data traffic traversing the plurality of network devices for detecting the identification data.

4. The method of claim 1, wherein the client ID represents a human client, wherein the identification data describes an attribute of the human client.

5. The method of claim 1, wherein allocating resources associated with the client ID further comprises determining local resources proximate to the second geographic location, wherein the local resources provide at least one of a cached content associated with the client, a storage partition associated with the client, re-routing network traffic associated with the client ID, and a network service associated with the client.

6. The method of claim 1, wherein allocating resources associated with the client ID further comprises:

predicting a future geographic location of the client based on the first and second geographic locations; and

reallocating resources associated with the client proximate to the future geographic location before confirming that the client has moved to the future geographic location.

7. The method of claim 1, further comprising:

detecting that the network flow containing the identification data has stopped; and

before determining that the client has moved into another geographic location, deallocating resources associated with the client in the second geographic location, wherein deallocating resources comprises at least one of removing a local content cache associated with the client ID, freeing a local storage partition associated with the client ID, re-routing network traffic associated with the client ID, and discontinuing a network service associated with the client ID.

8. A computer program product for allocating resources based on geographic movements of a client, the computer program product comprising:

computer code that determines a first geographic location of the client;

computer code that receives identification data for identifying the client from at least one application programming interfaces (API) operating in a network device in a software-defined networking (SDN) enabled network, wherein the API identifies the identification data by filtering a network flow traversing an ingress port of the network device;

computer code that associates the network flow to a client ID using the identification data;

computer code that determines, based on the network, a second geographic location of the client, wherein the first and second geographic locations are different;

computer code that allocates computing resources associated with the client ID in response to the client moving from the first geographic location to the second geographic location; and

a non-transitory computer-readable storage medium containing the computer code.

9. The computer program product of claim 8, wherein monitoring the network flow comprises:

computer code that executes an input filter on the network device for monitoring the network flow using the API, the API abstracting a control plane of the network device to permit a remote user application to monitor and control data traffic traversing the network device.

10. The computer program product of claim 9, wherein a plurality of network devices in the SDN enabled network each comprise a respective input filter and a respective monitoring API for monitoring data traffic traversing the plurality of network devices for detecting the identification data.

11. The computer program product of claim 8, wherein the client ID represents a human client, wherein the identification data describes an attribute of the human client.

12. The computer program product of claim 8, wherein allocating resources associated with the client ID further comprises determining local resources proximate to the second geographic location, wherein the local resources provide at least one of a cache of content associated with the client, a storage partition associated with the client, re-routing network traffic associated with the client ID, and a network service associated with the client.

13. The computer program product of claim 8, wherein allocating resources associated with the client ID further comprises:

computer code that predicts a future geographic location of the client based on the first and second geographic locations; and

computer code that reallocates resources associated with the client proximate to the future geographic location before confirming that the client has moved to the future geographic location.

14. The computer program product of claim 8, further comprising:

computer code that detects that the network flow containing the identification data has stopped; and

computer code that, before determining that the client has moved into another geographic location, deallocates resources associated with the client in the second geographic location, wherein deallocating resources comprises at least one of removing a local content cache associated with the client ID, freeing a local storage partition associated with the client ID, re-routing network traffic associated with the client ID, and discontinuing a network service associated with the client ID.

15. A system comprising:

a computer processor; and

a memory containing a program that, when executed on the computer processor, performs an operation comprising;

determining a first geographic location of the client;

receiving identification data for identifying the client from at least one application programming interfaces (API) operating in a network device in a software-defined networking (SDN) enabled network, wherein the API identifies the identification data by filtering a network flow traversing an ingress port of the network device;

associating the network flow to a client ID using the identification data;

determining, based on the network flow, a second geographic location of the client, wherein the first and second geographic locations are different; and

allocating computing resources associated with the client ID in response to the client moving from the first geographic location to the second geographic location.

16. The system of claim 15, wherein monitoring the network flow comprises:

executing an input filter on the network device for monitoring the network flow using the API, the API abstracting a control plane of the network device to permit a remote user application to monitor and control data traffic traversing the network device.

17. The system of claim 16, wherein a plurality of network devices in the SDN enabled network each comprise a respective input filter and a respective monitoring API for monitoring data traffic traversing the plurality of network devices for detecting the identification data.

18. The system of claim 15, wherein the client ID represents a human client, wherein the identification data describes an attribute of the human client.

19. The system of claim 15, wherein allocating resources associated with the client ID further comprises determining local resources proximate to the second geographic location, wherein the local resources provide at least one of a cache of content associated with the client, a storage partition associated with the client, re-routing network traffic associated with the client ID, and a network service associated with the client.

20. The system of claim 15, wherein allocating resources associated with the client ID further comprises:

predicting a future geographic location of the client based on the first and second geographic locations; and

reallocating resources associated with the client proximate to the future geographic location before confirming that the client has moved to the future geographic location.