Method and system for preloading resources

• US 20030220984A1
• Filed: 12/12/2002
• Published: 11/27/2003
• Est. Priority Date: 12/12/2001
• Status: Active Grant

• Current Assignee: Valve Corporation
• Original Assignee: Valve Corporation
• Inventors: Jones, Paul David, Newcombe, Christopher Richard, Birum, Derrick Jason, Thompson, Mikel Howard, Ellis, Richard Donald
• Granted Patent: US 7,895,261 B2
• Time in Patent Office: Days
• US Class Current: 709/219
• CPC Class Codes: H04L 2463/101 applying security measures for digital rights management data processing systems or methods, specially adapted for commerce, e.g. marketing, shopping, billing, auctions or e-commerce G06Q30/00
• CPC Class Codes: H04L 2463/121 Timestamp cryptographic mechanisms or cryptographic arrangements involving time stamps H04L9/3297
• 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 61/2514 between local and global IP addresses
• CPC Class Codes: H04L 63/0428 wherein the data content is protected, e.g. by encrypting or encapsulating the payload
• CPC Class Codes: H04L 63/08 for authentication of entities cryptographic mechanisms or cryptographic arrangements for entity authentication H04L9/32
• CPC Class Codes: H04L 63/0807 using tickets, e.g. Kerberos cryptographic mechanisms or cryptographic arrangements for entity authentication using tickets or tokens H04L9/3213
• CPC Class Codes: H04L 63/0846 using time-dependent-passwords, e.g. periodically changing passwords
• CPC Class Codes: H04L 63/123 received data contents, e.g. message integrity
• CPC Class Codes: H04L 63/168 above the transport layer
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/06 specially adapted for file transfer, e.g. file transfer protocol [FTP]
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30
• CPC Class Codes: H04L 67/289 Intermediate processing functionally located close to the data consumer application, e.g. in same machine, in same home or in same sub-network
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/34 involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• CPC Class Codes: H04L 67/51 Discovery or management thereof, e.g. service location protocol [SLP] or web services
• CPC Class Codes: H04L 67/53 using third party service providers
• CPC Class Codes: H04L 67/55 : Push-based network services
• CPC Class Codes: H04L 67/564 : Enhancement of application control based on intercepted application data
• CPC Class Codes: H04L 67/5681 : Pre-fetching or pre-delivering data based on network characteristics
• CPC Class Codes: H04L 67/62 : Establishing a time schedule for servicing the requests
• CPC Class Codes: H04L 69/329 : in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 : Network security protocols

Abstract

A method and system for preloading data is provided. Resources are preloaded on a client before they are needed by an application. Application hints and static resources lists may be used to indicate resources are needed. The application may begin execution before receiving all of the resources associated with the application. Preloading may be done during execution of an application, or when the application is not executing. Preloading allows an application to run smoothly without consuming more resources than are needed by an application. A prediction graph may be generated that is used in predicting the resources that are likely to be needed by the application. An analyzer may also be used to simulate the system and adjust parameters used in creating the prediction graph.

Claims

1. A method for preloading resources for an application, comprising:

determining resources to preload on a client before the application needs the resources; and

preloading the client with the resources;

when the resources are located on a server, then downloading the resources from the server, storing the resources locally on the client; and

obtaining the resources locally when the resources are stored on the client;

wherein the application is configured to execute with a subset of the resources associated with the application.

2. The method of claim 1, wherein determining the resources to preload further comprises using a resource list that contains the resources to supply to the application.

3. The method of claim 2, wherein using the resource list that contains the at least one resource to supply to the application further comprises prioritizing a list of the resources, wherein the list is prioritized according to an order in which the resources are to be preloaded.

4. The method of claim 3, further comprising dynamically changing the priority of the resources within the resource list while the application is executing.

5. The method of claim 1, wherein determining what resources to preload before the application needs the resources further comprises receiving an application hint from the client and generating a resource list of the resources to be preloaded based on the application hint.

6. The method of claim 5, wherein generating the list of the resources to be preloaded based on the application hint further comprises determining a current state of the application.

7. The method of claim 6, wherein using the application hint further comprises storing application resource request states and transitions between those states and analyzing the application resource request states and the transitions between those states to create a prediction graph.

8. The method of claim 7, further comprising using the prediction graph to generate the resource list.

9. The method of claim 5, wherein determining what resources to preload before the application needs the resources further comprises storing information relating to the resources and the application hints and using a predictor to predict the resources that are likely to be needed based on using a prediction graph to predict the likelihood the resource is likely to be needed.

10. The method of claim 9, wherein using the prediction graph further comprises weighting edges of nodes within the prediction graph.

11. The method of claim 9, further comprising determining resources that are available locally and removing the determined resources from the predicted resource list.

12. The method of claim 9, further comprising adjusting a lifetime associated with an already-cached resource based on the resource being referenced by recent predictions made by the predictor.

13. The method of claim 5, further comprising interrupting the preloading based on a change of priority.

14. The method of claim 5, wherein the resource list comprises resources that may be needed by an executing application or a non-executing application.

15. The method of claim 5, wherein preloading the resources further comprises preloading the resources when the application is executing.

16. The method of claim 5, wherein preloading the resources further comprises preloading the resources when the application is in a non-executing state.

17. The method of claim 5, wherein preloading the resources may be enabled and disabled for the application.

18. The method of claim 17, further comprising assigning a priority to preload the resources that are associated with application.

19. The method of claim 7, wherein analyzing the application resource request states and the transitions between those states to create the prediction graph further comprises adjusting parameters that are used in algorithms to process and combine session lists into the prediction graph.

20. The method of claim 19, wherein the parameters are selected from a set comprising:

InfluenceOfElapsedTimeInPredictionWeight, InfluenceOfDistanceFromStepOffPointWhenConsideringRejoinNodes, and InfluenceOfNumberOfSequenceMismatchesWhenConsideringRejoinNodes.

21. The method of claim 19, wherein adjusting the parameters further comprises adjusting the parameters automatically.

22. The method of claim 19, wherein adjusting the parameters further comprises adjusting the parameters manually.

23. The method of claim 19, further comprising generating performance data and determining an effectiveness of the prediction graph based on the performance data.

24. The method of claim 23, wherein the performance data comprises at least one of:

NumberOfCacheMisses, NumberOfFailedPredictions, NumberOfCacheHitsInPredictions, NumberOfCacheHitsNotInCurrentPredictions, HighestNumberOfRetriesToFindARejoinNode, and AverageNumberOfRetriesToFindARejoinNode.

25. The method of claim 23, further comprises adjusting the parameters in response to the performance data.

26. A system for preloading resources for an application on a client, comprising:

a server, comprising;

a network connection configured to communicate with the client;

a memory configured to store resources associated with the application;

a process configured to perform actions including to provide resources to the client;

a client, comprising;

a network connection configured to communicate with the server;

a memory configured to store resources associated with the application; and

a process arranged to receive resources associated with the application; and

an application configured to execute with a subset of the resources associated with the application;

and a preloader configured to perform the following actions;

determining the resources to preload on the client before the application needs the resources; and

preloading the client with the resources;

when the resources are located on a server, then employing the server to supply the client with the resources, and when the resources are located on the client then instructing the client to obtain the resources locally.

27. The system of claim 26, wherein determining the resources to preload further comprises using a resource list that contains the resources to supply to the application.

28. The system of claim 27, wherein using the resource list that contains the at least one resource to supply to the application further comprises prioritizing a list of the resources, wherein the list is prioritized according to an order in which the resources are to be preloaded.

29. The system of claim 28 further comprising dynamically changing the priority of the resources within the resource list while the application is executing.

30. The system of claim 26, wherein determining what resources to preload before the application needs the resources further comprises receiving an application hint from the client and generating a resource list of the resources to be preloaded based on the application hint.

31. The system of claim 30, wherein generating the list of the resources to be preloaded based on the application hint further comprises determining a current state of the application.

32. The system of claim 31, wherein using the application hint further comprises storing the current state of the application and creating a prediction graph based on stored current states.

33. The system of claim 32, further comprising using a predictor utilizing the prediction graph to generate the resource list.

34. The system of claim 33, wherein using the predictor is further configured to weight edges of nodes within the prediction graph such that the nodes are directed.

35. The system of claim 33, further comprising the predictor determining resources that are available locally and removing the determined resources from the resource list.

36. The system of claim 33, further comprising the predictor adjusting the resource list based on using the prediction graph.

37. The system of claim 30, further comprising interrupting the preloading based on a change of priority.

38. The system of claim 30, wherein the resource list comprises resources that may be needed by an executing application or a non-executing application.

39. The system of claim 30, wherein preloading the resources further comprises preloading the resources when the application is executing.

40. The system of claim 30, wherein preloading the resources further comprises preloading the resources when the application is in a non-executing state.

41. The system of claim 30, wherein preloading the resources may be enabled and disabled for the application.

42. The system of claim 41, further comprising assigning a priority to preload the resources that are associated with applications.

43. The system of claim 26, wherein the preloader is located on the server.

44. The system of claim 26, wherein the preloader is located on the client.

45. The system of claim 26, wherein determining what resources to preload before the application needs the resources further comprises generating session lists and using the session lists to generate a prediction graph.

46. The system of claim 42, wherein using the session lists to generate the prediction graph further comprises adjusting parameters to combine the session lists into the prediction graph.

47. The system of claim 43, further comprising an analyzer that is configured to adjust the parameters and simulate the predictor, the application, and the preloader based on the parameters.

48. The system of claim 44, wherein the analyzer is further configured to iteratively adjust the parameters until results of the simulation are at a predetermined level of acceptability.

49. The system of claim 47, wherein the analyzer is further configured to generate performance data that is used in determining the effectiveness of the system.

50. The system of claim 49, wherein the performance data comprises at least one of:

NumberOfCacheMisses, NumberOfFailedPredictions, NumberOfCacheHitsInPredictions, NumberOfCacheHitsNotInCurrentPredictions, HighestNumberOfRetriesToFindARejoinNode, and AverageNumberOfRetriesToFindARejoinNode.

51. The system of claim 49, wherein the analyzer is further configured to adjust the parameters in response to the performance data.

52. A system for preloading resources for an application, comprising:

means for determining resources to preload on a client before the application needs the resources;

means for preloading the client with the resources;

when the resources are located on a server, then means for downloading the resources from the server, means for storing the resources locally on the client; and

means for obtaining the resources locally when the resources are stored on the client;

wherein the application is configured to execute with a subset of the resources associated with the application.