SYSTEM AND METHOD FOR TRANSFORMING LEGACY DESKTOP ENVIRONMENTS TO A VIRTUALIZED DESKTOP MODEL

• US 20110131589A1
• Filed: 12/02/2009
• Published: 06/02/2011
• Est. Priority Date: 12/02/2009
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bhowmik, Rajdeep, Shaikh, Hidayatullah Habeebullah, Rhee, Junghwan, Beaty, Kirk Alan, Kochut, Andrzej
• Granted Patent: US 8,490,087 B2
• Time in Patent Office: Days
• US Class Current: 719/318
• CPC Class Codes: G06F 11/3428 Benchmarking
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2009/45562 Creating, deleting, cloning virtual machine instances
• CPC Class Codes: G06F 2009/45595 Network integration; Enabling network access in virtual machine instances
• CPC Class Codes: G06F 9/455 Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects
• CPC Class Codes: G06F 9/5077 Logical partitioning of resources; Management or configuration of virtualized resources specific details on emulation or internal functioning of virtual machines G06F9/455
• 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

A system and method for transforming a legacy device into a virtualized environment includes gathering profiling data over time to represent legacy device activities and analyzing the profiling data for system applications and user applications using a processor to determine usage frequency and resource requirements of at least one application. Captured user action events are benchmarked to simulate a user workload for the at least one application to determine how resource utilization and execution times scale from a legacy environment to a virtualized environment. One or more scaling factors are determined to produce a plan to provision for legacy services in the virtualized environment. The legacy system is transformed into the virtualized environment in accordance with the plan.

Claims

1. A method for transforming a legacy device into a virtualized environment, comprising:

gathering profiling data over time to represent legacy device activities;

analyzing the profiling data for system applications and user applications using a processor to determine usage frequency and resource requirements of at least one application;

benchmarking captured user action events to simulate a user workload for the at least one application to determine how resource utilization and execution times scale from a legacy environment to a virtualized environment;

determining one or more scaling factors to produce a plan to provision for legacy services in the virtualized environment; and

transforming the legacy system into the virtualized environment in accordance with the plan.

2. The method as recited in claim 1, wherein gathering profiling data includes determining application level resource statistics of the legacy system including at least one of characteristics of specific applications;

number, speed, type and utilization of processors;

size and utilization of memory;

size and utilization of local disks;

utilization of network interfaces;

names, user/owner, command line arguments;

utilization of computer processing unit, memory, and network for all processes.

3. The method as recited in claim 1, wherein gathering profiling data includes gathering information from a representative number of legacy devices.

4. The method as recited in claim 1, further comprising constructing plans to migrate to multiple models in the virtual environment from the legacy devices based upon the profiling data.

5. The method as recited in claim 4, wherein the multiple models include a shared services model, a virtualized desktop model, and a dedicated server model.

6. The method as recited in claim 1, further comprising disaggregating a legacy device and delivering a same set of services to a user of the legacy device by employing multiple virtualization technologies.

7. The method as recited in claim 1, wherein determining one or more scaling factors includes determining scaling factors based on performance and utilization measurements in the profiling data.

8. The method as recited in claim 7, wherein the performance and utilization measurements in the profiling data include stored artifacts of user events and times between events.

9. The method as recited in claim 1, wherein benchmarking includes recording and replaying user events to match screen buffer regions to playlists to determine when a user action has completed to proceed to a next action.

10. A computer readable storage medium comprising a computer readable program for transforming a legacy device into a virtualized environment, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:

gathering profiling data over time to represent legacy device activities;

analyzing the profiling data for system applications and user applications using a processor to determine usage frequency and resource requirements of at least one application;

benchmarking captured user action events to simulate a user workload for the at least one application to determine how resource utilization and execution times scale from a legacy environment to a virtualized environment;

determining one or more scaling factors to produce a plan to provision for legacy services in the virtualized environment; and

transforming the legacy system into the virtualized environment in accordance with the plan.

11. The computer readable storage medium as recited in claim 10, wherein gathering profiling data includes determining application level resource statistics of the legacy system including at least one of characteristics of specific applications;

number, speed, type and utilization of processors;

size and utilization of memory;

size and utilization of local disks;

utilization of network interfaces;

names, user/owner, command line arguments;

utilization of computer processing unit, memory, and network for all processes.

12. The computer readable storage medium as recited in claim 10, wherein gathering profiling data includes gathering information from a representative number of legacy devices.

13. The computer readable storage medium as recited in claim 10, further comprising constructing plans to migrate to multiple models in the virtual environment from the legacy devices based upon the profiling data.

14. The computer readable storage medium as recited in claim 13, wherein the multiple models include a shared services model, a virtualized desktop model, and a dedicated server model.

15. The computer readable storage medium as recited in claim 10, wherein determining one or more scaling factors includes determining scaling factors based on performance and utilization measurements in the profiling data.

16. The computer readable storage medium as recited in claim 15, wherein the performance and utilization measurements in the profiling data include stored artifacts of user events and times between events.

17. The computer readable storage medium as recited in claim 10, wherein benchmarking includes recording and replaying user events to match screen buffer regions to playlists to determine when a user action has completed to proceed to a next action.

18. The computer readable storage medium as recited in claim 10, further comprising disaggregating a legacy device and delivering a same set of services to a user of the legacy device by employing multiple virtualization technologies.

19. A system for planning and transforming legacy devices into a virtualized environment, comprising:

a user profiling module configured to gather profiling data over time to represent legacy device activities and analyze the profiling data for system applications and user applications to determine usage frequency and resource requirements of at least one application, the profiling module including a program application implemented from a storage medium for collecting profiling data and running on a legacy device;

a benchmarking module configured to capture user action events to simulate a user workload for the at least one application to determine how resource utilization and execution times scale from a legacy environment to a virtualized environment;

a transformation planner configured to employ scale factors from the benchmarking module to produce a plan to provision for legacy services in the virtualized environment; and

a transformation executor configured to execute the plan to provide services for the legacy system within the virtualized environment.

20. The system as recited in claim 19, wherein the user profiling module includes memory storage for application level resource statistics of the legacy system including statistics for at least one of characteristics of specific applications;

number, speed, type and utilization of processors;

size and utilization of memory;

size and utilization of local disks;

utilization of network interfaces;

names, user/owner, command line arguments;

utilization of computer processing unit, memory, and network for all processes.

21. The system as recited in claim 19, wherein profiling data includes information from a representative number of legacy devices.

22. The system as recited in claim 19, wherein the transformation planner constructs plans to migrate a legacy device to one or more of multiple models in the virtual environment based upon the profiling data, knowledge and models and benchmark information.

23. The system as recited in claim 22, wherein the multiple models include a shared services model, a virtualized desktop model, and a dedicated server model.

24. The system as recited in claim 19, wherein the benchmarking module determines scaling factors based on performance and utilization measurements in the profiling data.

25. The system as recited in claim 24, wherein the performance and utilization measurements in the profiling data include stored artifacts of user events and times between events.

26. The system as recited in claim 19, wherein the benchmarking module includes memory configured to record and replay user events to match screen buffer regions to playlists to determine when a user action has completed to proceed to a next action.