SPECULATIVE ALLOCATION OF INSTANCES

• US 20160239906A1
• Filed: 08/27/2013
• Published: 08/18/2016
• Est. Priority Date: 08/27/2013
• Status: Abandoned Application

• Current Assignee: Empire Technology Development LLC (Allied Inventors Management, LLC)
• Original Assignee: Empire Technology Development LLC (Allied Inventors Management, LLC)
• Inventors: Kruglick, Ezekiel
• Application Number:
  US14/380,571
• Publication Number:
  US 20160239906A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/08 Auctions

Abstract

In one example embodiment, operations may include predicting winning bidders in an auction for computing resources; pre-placing machine images before the auction has been completed; booting-up at least a portion of the pre-placed machine images before the auction has been completed; and assigning a booted-up virtual machine to one of the predicted auction winners.

Claims

1. A method for speculative allocation of computing resources, comprising:

tracking data, for each of one or more users of computing resources, including a respective history of auction bids and a respective history of computing resource usage;

predicting, based on the tracked data, respective probabilities that each of the one or more users will submit a qualifying bid for one or more available computing resources during a current auction;

ranking the predictions; and

preparing the available datacenter resources for allocation to at least one of the users in accordance with the ranked predictions.

2. The method of claim 1, wherein the tracked data, for each of the one or more users, includes user profile information, a history of winning auction bids, a history of losing auction bids, and bid patterns.

3. The method of claim 1, wherein the profile information for each of the one or more users includes an industry or service, a history of peak needs.

4. The method of claim 1, wherein the predicting is further based on deployment data regarding the available computing resources.

5. The method of claim 1, wherein the predicting is further based on pricing of the available computing resources.

6. The method of claim 1, wherein the preparing includes pre-positioning multiple virtual machine instances across the datacenter.

7. The method of claim 6, wherein the preparing includes booting at least a portion of the pre-positioned multiple virtual machine instances.

8. The method of claim 7, wherein the preparing further includes freezing at least one of the booted virtual machine instances if a winner in the current auction for the at least one booted virtual machine instance has not yet been determined.

9. The method of claim 7, wherein the preparing further includes shutting down at least one booted virtual machine resource that is not awarded in the current auction.

10. The method of claim 1, further comprising:

awarding a booted up datacenter resource to at least one user who has submitted a qualifying bid; and

billing the at least one user for time used to boot up the awarded datacenter resource.

11. A system for speculative allocation of computing resources, comprising:

a management module configured to store prediction variables;

a prediction module configured to predict, based on at least the prediction variables, respective probabilities that one or more users will submit a qualifying bid for one or more available computing resources during a current auction;

a hypervisor configured to prepare the available computing resources for allocation upon completion of the current auction.

12. The system of claim 11, wherein the prediction variables include user profile information, a history of winning auction bids, a history of losing auction bids, and bid patterns.

13. The system of claim 11, wherein the prediction module is configured to, at least, comparatively match one or more of the prediction variables to features of the available computing resources.

14. The system of claim 13, wherein the features of the available computing resources include statistics regarding at least one of pricing and performance.

15. The system of claim 11, wherein the hypervisor is configured to prepare one or more of the available computing resources by pre-positioning one or more virtual machine instances across the datacenter.

16. The system of claim 11, wherein the hypervisor is configured to prepare one or more of the available computing resources by booting at least a portion of the pre-positioned multiple virtual machine instances.

17. The system of claim 16, wherein the hypervisor is configured to prepare one or more of the available computing resources by freezing at least one of the booted virtual machine instances if a winner in the current auction for the at least one booted virtual machine instance has not yet been determined.

18. The system of claim 16, wherein the hypervisor is configured to prepare one or more of the available computing resources by shutting down at least one booted virtual machine resource that is not awarded in the current auction.

19. The system of claim 11, further comprising:

a manager configured to account for time required to boot up an awarded one of the available computing resources.

20. A non-transitory computer-readable medium storing instructions that, when executed, cause one or more processors to perform operations comprising:

predicting winning bidders in an auction for computing resources;

pre-placing machine images before the auction has been completed;

booting-up at least a portion of the pre-placed machine images before the auction has been completed; and

assigning a booted-up virtual machine to one of the predicted winning bidders who has submitted a winning bid.

21. The non-transitory computer-readable medium of claim 20, wherein the operations further comprise:

charging for time needed to boot-up one of the assigned virtual machines.