Managing a set of wear-leveling data using a set of bus traffic

• US 10,078,457 B2
• Filed: 01/13/2016
• Issued: 09/18/2018
• Est. Priority Date: 01/13/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Jain, Chethan, Ward, Maria R.
• Primary Examiner(s): Oberly, Eric T
• Application Number:
  US14/994,934
• Publication Number:
  US 20170199681A1
• Time in Patent Office: 979 Days
• CPC Class Codes: G06F 11/008 Reliability or availability analysis
• CPC Class Codes: G06F 11/30 Monitoring
• CPC Class Codes: G06F 11/3006 where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems multiprogramming arrangements G06F9/46; allocation of resources G06F9/50
• CPC Class Codes: G06F 11/3433 for load management allocation of a server based on load conditions G06F9/505; load rebalancing G06F9/5083; redistributing the load in a network by a load balancer H04L67/1029
• CPC Class Codes: G06F 13/00 Interconnection of, or transfer of information or other signals between, memories, input/output devices or central processing units interface circuits for specific input/output devices G06F3/00 ; multiprogram control therefor G06F9/46; multiprocessor systems G06F15/16
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 3/0616 in relation to life time, e.g. increasing Mean Time Between Failures [MTBF]
• CPC Class Codes: G06F 3/0638 Organizing or formatting or addressing of data
• CPC Class Codes: G06F 3/0653 Monitoring storage devices or systems
• CPC Class Codes: G06F 3/0673 Single storage device
• CPC Class Codes: G06F 9/505 considering the load
• 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: G06F 9/5094 where the allocation takes into account power or heat criteria power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

Disclosed aspects include managing a set of wear-leveling data for a set of compute nodes. A set of bus traffic data may be monitored with respect to a bus which is connected to a computer hardware component of the set of compute nodes. In response to monitoring the set of bus traffic, the set of wear-leveling data may be determined using the set of bus traffic. The wear-leveling data determined using the set of bus traffic may then be established in a data store. The wear leveling data may be used to manage asset placement with respect to a shared pool of configurable computing resources.

Claims

1. A method comprising:

monitoring, with respect to a bus which is connected to a computer hardware component of a plurality of compute nodes, a set of bus traffic which indicates utilization of the bus;

detecting a respective set of wear-leveling data for each compute node of the plurality of compute nodes, wherein each set of wear leveling data includes a plurality of sets of component usage data respectively corresponding to individual one of different component types, wherein each set of component usage data indicates a degree of historical utilization of the respectively corresponding component type in the compute node;

ascertaining a respective set of component prioritization data for each virtual machine (VM) of a plurality of VMs, wherein each set of component prioritization data specifies one or more operational priorities respectively corresponding to ones of the different component types indicating a degree of importance of the respective component type relative to the other different component types;

determining a placement arrangement for the VMs with respect to the plurality of compute nodes, wherein the determining comprises, for each VM of the plurality of VMs;

identifying, using the set of component prioritization data for the VM, a component type with a highest degree of importance for the VM;

identifying, using the sets of wear-leveling data, a compatible node of the plurality of compute nodes which has the lowest degree of historical utilization of the identified component type compared to the other compute nodes of the plurality of compute nodes; and

storing, in the placement arrangement, an indication that the VM is matched with the identified compatible compute node; and

weighing wear-levels assigned to each of the compute nodes based on an intensity of commands requested by the set of bus traffic;

and

placing, based on the placement arrangement, each VM of the plurality of VMs on the compute node matched to the VM.

2. The method of claim 1, further comprising

collecting, in response to monitoring the set of bus traffic, a set of bus traffic data which indicates a historical utilization of the computer hardware component based on the set of bus traffic.

3. The method of claim 2, wherein determining the set of wear-leveling data comprises

analyzing the set of bus traffic data related to usage intensity which indicates an extent to which a component is taxed by a given access request.

4. The method of claim 1,

wherein the bus comprises a system bus, and

wherein the computer hardware component comprises a memory device.

5. The method of claim 1,

wherein the bus is not a system bus, and

wherein the computer hardware component comprises a peripheral device.

6. The method of claim 1, further comprising:

organizing the set of wear-leveling data based on a lesser utilized hardware factor which indicates a lesser likelihood of a hardware error event; and

determining, in response to the organizing, the placement arrangement for a set of virtual machines to indicate to place one or more virtual machines on a hardware device based on the lesser utilized hardware factor.

7. The method of claim 1, further comprising:

receiving an access request, wherein the access request includes a write-intensive request;

selecting, based on the set of wear-leveling data, a first compute module of the set of compute nodes to process the access request;

identifying that the first compute module has a first write frequency;

identifying that a second compute module has a second write frequency;

comparing the first write frequency for the first compute module with the second write frequency for the second compute module;

computing that the second write frequency for the second compute module exceeds the first write frequency for the first compute module; and

processing the access request using the first compute module.

8. The method of claim 7, wherein the access request comprises a read-intensive request, and further comprising:

identifying that the first compute module has a first read frequency;

identifying that the second compute module has a second read frequency;

comparing, to determine one or more compute modules to process the access request, the first read frequency with the second read frequency;

computing that the second read frequency exceeds the first read frequency; and

processing the access request using the first compute module.

9. The method of claim 1, wherein monitoring, with respect to the bus which is connected to the computer hardware component of the set of compute nodes, the set of bus traffic comprises:

tracking use of the bus by write requests; and

tracking use of the bus by read requests.

10. The method of claim 1, further comprising

recording the set of wear-leveling data in a data store on a remote compute node which is physically separate from the computer hardware component.

14. The method of claim 1, wherein the set of bus traffic pertains to utilization of a set of system bus connections.

15. The method of claim 7, further comprising:

comparing, without a comparison with one or more write frequencies not derived from the first and second computing modules, the first write frequency for the first compute module with the second write frequency for the second compute module.

16. The method of claim 1, further comprising:

marking with a tag which indicates the lesser utilized hardware factor which indicates a lesser likelihood of a hardware error event for a particular hardware component;

organizing, based on the tag which indicates the lesser utilized hardware factor which indicates the lesser likelihood of the hardware error event for the particular hardware component, the set of wear-leveling data; and

determining, in response to the organizing, the placement arrangement for a set of virtual machines to indicate to place one or more virtual machines on the particular hardware component based on the lesser utilized hardware factor.

17. The method of claim 2, further comprising:

weighting, based on usage intensity of the set of bus traffic, the set of bus traffic data; and

analyzing, in response to weighting the set of bus traffic data, the set of bus traffic data which is weighted to indicate an extent to which a component is taxed by a given access request.

18. The method of claim 17, further comprising:

determining, based on and in response to analyzing the set of bus traffic data, the set of wear-leveling data which is derived from the set of bus traffic data.

19. The method of claim 3, further comprising:

prioritizing, when analyzing the set of bus traffic data related to usage intensity which indicates the extent to which the component is taxed by the given access request, usage intensity with respect to usage frequency.

20. The method of claim 2, further comprising:

computing, to collect the set of bus traffic data, a number of read and write requests processed by the bus using a hardware counter.

11. A system comprising:

a memory having a set of computer readable computer instructions; and

a processor for executing the set of computer readable instructions, the set of computer readable instructions comprising

monitoring, with respect to a bus which is connected to a computer hardware component of a plurality of compute nodes, a set of bus traffic which indicates utilization of the bus;

detecting a respective set of wear-leveling data for each compute node of the plurality of compute nodes, wherein each set of wear leveling data includes a plurality of sets of component usage data respectively corresponding to individual one of different component types, wherein each set of component usage data indicates a degree of historical utilization of the respectively corresponding component type in the compute node;

ascertaining a respective set of component prioritization data for each virtual machine (VM) of a plurality of VMs, wherein each set of component prioritization data specifies one or more operational priorities respectively corresponding to ones of the different component types indicating a degree of importance of the respective component type relative to the other different component types;

determining a placement arrangement for the VMs with respect to the plurality of compute nodes, wherein the determining comprises, for each VM of the plurality of VMs;

identifying, using the set of component prioritization data for the VM, a component type with a highest degree of importance for the VM;

identifying, using the sets of wear-leveling data, a compatible node of the plurality of compute nodes which has the lowest degree of historical utilization of the identified component type compared to the other compute nodes of the plurality of compute nodes; and

storing, in the placement arrangement, an indication that the VM is matched with the identified compatible compute node; and

weighing wear-levels assigned to each of the compute nodes based on an intensity of commands requested by the set of bus traffic; and

placing, based on the placement arrangement, each VM of the plurality of VMs on the compute node matched to the VM.

12. The system of claim 11,

wherein the bus comprises a system bus, and

wherein the computer hardware component comprises a memory device, further comprising

organizing the set of wear-leveling data based on a lesser utilized hardware factor which indicates a lesser likelihood of a hardware error event, and

determining, in response to the organizing, the placement arrangement for a set of virtual machines to indicate to place one or more virtual machines on a hardware device based on the lesser utilized hardware factor which is tracked with respect to the system bus.

13. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising:

monitoring, with respect to a bus which is connected to a computer hardware component of a plurality of compute nodes, a set of bus traffic which indicates utilization of the bus;

detecting a respective set of wear-leveling data for each compute node of the plurality of compute nodes, wherein each set of wear leveling data includes a plurality of sets of component usage data respectively corresponding to individual one of different component types, wherein each set of component usage data indicates a degree of historical utilization of the respectively corresponding component type in the compute node;

ascertaining a respective set of component prioritization data for each virtual machine (VM) of a plurality of VMs, wherein each set of component prioritization data specifies one or more operational priorities respectively corresponding to ones of the different component types indicating a degree of importance of the respective component type relative to the other different component types;

determining a placement arrangement for the VMs with respect to the plurality of compute nodes, wherein the determining comprises, for each VM of the plurality of VMs;

identifying, using the set of component prioritization data for the VM, a component type with a highest degree of importance for the VM;

identifying, using the sets of wear-leveling data, a compatible node of the plurality of compute nodes which has the lowest degree of historical utilization of the identified component type compared to the other compute nodes of the plurality of compute nodes; and

storing, in the placement arrangement, an indication that the VM is matched with the identified compatible compute node; and

weighing wear-levels assigned to each of the compute nodes based on an intensity of commands requested by the set of bus traffic;

and

placing, based on the placement arrangement, each VM of the plurality of VMs on the compute node matched to the VM.