METHOD AND SYSTEM FOR DETERMINING A PLURALITY OF SCHEDULING ENDPOINTS IN A GRID NETWORK

• US 20070016590A1
• Filed: 06/28/2006
• Published: 01/18/2007
• Est. Priority Date: 06/29/2005
• Status: Active Grant

• Current Assignee: LinkedIn Corporation (Microsoft Corporation)
• Original Assignee: International Business Machines Corporation
• Inventors: Easton, John, Appleby, Richard
• Granted Patent: US 7,792,957 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 43/00 Arrangements for monitoring or testing data switching networks
• CPC Class Codes: H04L 43/0811 by checking connectivity
• CPC Class Codes: H04L 43/0817 by checking functioning
• CPC Class Codes: H04L 67/61 taking into account QoS or priority requirements
• CPC Class Codes: H04L 67/62 Establishing a time schedule for servicing the requests

Abstract

A method for determining a plurality of scheduling endpoints in a grid network, each scheduling endpoint comprising a device for processing job requests communicated across the network, the method comprising the steps of: examining a communication across the network in order to determine a current activity status of a requesting device; identifying an activity history for the requesting device; comparing the current activity status with the activity history to derive a statistical data set; and analysing the statistical data set to derive a time period in which the requesting device is available for processing job requests.

Claims

1. A method for determining a plurality of scheduling endpoints in a grid network, each scheduling endpoint comprising a device for processing job requests communicated across the network, the method comprising the steps of:

examining a communication across the network in order to determine a current activity status of a requesting device;

identifying an activity history for the requesting device;

comparing the current activity status with the activity history to derive a statistical data set; and

analysing the statistical data set to derive a time period in which the requesting device is available for processing job requests.

2. A method as claimed in claim 1, wherein the analysing step further comprises deriving a probability score indicative of a likelihood of a pattern of activity re-occurring.

3. A method as claimed in claim 1, wherein the examining step further comprises extracting a set of network parameters from the communication, the set of network parameters comprising an IP address of the requesting device, an IP address of a destination address, and a type of resource the requesting device is requesting.

4. A method as claimed in claim 3, wherein the examining step further comprises analysing the destination IP address and the type of resource to determine a category of device the requesting device falls into.

5. A method as claimed in claim 4, wherein on determining the category of device, deriving an activity characteristic for the requesting device.

6. A method as claimed in claim 5, wherein the activity characteristic in combination with the activity history and the current activity status form parameters for the statistical data set.

7. A method as claimed in claim 1, wherein on examining a communication from a requesting device indicates the requesting device is active and available on the network.

8. A method as claimed in claim 1, further comprising identifying a type of data packet and performing a lookup, in a data store, to identify a format of the data within the identified data packet type.

9. A method as claimed in claim 8, wherein network parameters are extracted from the data packet and stored in accordance with the format of the data packet type.

10. A method as claimed in claim 9, wherein the extracted network parameters further comprise a vendor extension identifying hardware and software installed on the requesting device.

11. A system for determining a plurality of scheduling endpoints in a grid network, each scheduling endpoint comprising a device for processing job requests communicated across the network, the system comprising:

an examining component for examining a communication across the network in order to determine a current activity status of a requesting device;

an identifying component for identifying an activity history for the requesting device;

a comparing component for comparing the current activity status with the activity history to derive a statistical data set; and

an analysing component for analysing the statistical data set to derive a time period in which the requesting device is available for processing job requests.

12. A system as claimed in claim 11, wherein the analysing component further comprises deriving a probability score indicative of a likelihood of a pattern of activity re-occurring.

13. A system as claimed in claim 11, wherein the examining component further comprises an extracting component for extracting a set of network parameters from the communication, the set of network parameters comprising an IP address of the requesting device, an IP address of a destination address, and a type of resource the requesting device is requesting.

14. A system as claimed in claim 12, wherein the examining component analyses the destination IP address and the type of resource to determine a category of device the requesting device falls into.

15. A system as claimed in claim 14, wherein on determining the category of device, the examining component derives an activity characteristic for the requesting device.

16. A system as claimed in claim 15, wherein the activity characteristic in combination with historical activity and the current activity status form parameters for the statistical data set.

17. A system as claimed in claim 11, wherein on the examining component examining the communication from a requesting device, the communication indicates the requesting device is active and available on the network.

18. A system as claimed in claim 11, further comprising the identifying component identifying a type of data packet and performing a lookup, in a data store, to identify a format of the data within the identified data packet type.

19. A system as claimed in claim 18, wherein network parameters are extracted from the data packet and stored in accordance with the format of the data packet type.

20. A system as claimed in claim 19, wherein the extracted network parameters may further comprise a vendor extension identifying hardware and software installed on the requesting device.

21. A computer program product loadable into the internal memory of a digital computer for determining a plurality of scheduling endpoints in a grid network, each scheduling endpoint comprising a device for processing job requests communicated across the network, comprising software code portions for performing, when said product is run on a computer, for:

examining a communication across the network in order to determine a current activity status of a requesting device;

identifying an activity history for the requesting device;

comparing the current activity status with the activity history to derive a statistical data set; and

analysing the statistical data set to derive a time period in which the requesting device is available for processing job requests.