US20080228644A1 - Providing metered capacity of computer resources - Google Patents

Providing metered capacity of computer resources Download PDF

Info

Publication number
US20080228644A1
US20080228644A1 US12/131,066 US13106608A US2008228644A1 US 20080228644 A1 US20080228644 A1 US 20080228644A1 US 13106608 A US13106608 A US 13106608A US 2008228644 A1 US2008228644 A1 US 2008228644A1
Authority
US
United States
Prior art keywords
resource
logical partition
time
metered
capacity manager
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US12/131,066
Inventor
Daniel Charles Birkestrand
Randall Lane Grimm
David Otto Lewis
Terry Lyle Schardt
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
International Business Machines Corp
Original Assignee
International Business Machines Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by International Business Machines Corp filed Critical International Business Machines Corp
Priority to US12/131,066 priority Critical patent/US20080228644A1/en
Publication of US20080228644A1 publication Critical patent/US20080228644A1/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce
    • G06Q30/04Billing or invoicing
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00Payment architectures, schemes or protocols
    • G06Q20/08Payment architectures
    • G06Q20/10Payment architectures specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
    • G06Q20/102Bill distribution or payments

Definitions

  • This invention generally relates to data processing, and more specifically relates to utilization of resources in a computer system.
  • Computer systems typically include a combination of hardware (e.g., semiconductors, circuit boards, etc.) and software (e.g., computer programs).
  • hardware e.g., semiconductors, circuit boards, etc.
  • software e.g., computer programs
  • One way to provide a more flexible solution allows a computer user to buy a computer system that has some resources installed, but initially disabled.
  • the customer may enter into an arrangement with the provider of the computer system to enable certain resources for a fixed period of time. This works out particularly well for companies that have seasonal peaks.
  • the companies can purchase a computer system at a reasonable cost that has the capability of providing enhanced computing power during the peak season.
  • the concept of providing temporary capacity on demand is the subject matter of the related patent application “Method to Provide On-Demand Resource Access”, Ser. No. 10/406,652, filed on Apr. 3, 2003.
  • a flow diagram of one suitable method 200 for providing temporary capacity on demand begins by the customer requesting an enablement code from the manufacturer (step 210 ).
  • the customer receives the enablement code, which includes a specification of resource-time (step 220 ).
  • resource-time is a general term that allows specifying any resource or combination of resources for any suitable period of time.
  • resource-time is processor-days.
  • the customer enters the enablement code, which enables the resources on the computer system (step 230 ).
  • a timer is then started (step 240 ).
  • a simple example will show the usefulness of method 200 .
  • the company could purchase a computer system that has one or more additional processors that are installed but initially disabled. The company may then contract with the provider of the computer system to enable the additional processor(s) for a set period of time.
  • the computer system has two additional processors, and let's assume that the peak buying period runs for the thirty day period from November 15 th to December 14 th .
  • the customer could purchase sixty processor-days of additional capacity beginning on November 15 th . These two additional processors will then be enabled for the thirty day period (providing the sixty processor-days of additional capacity). Once the sixty processor-days have elapsed, the two additional processors are disabled.
  • One problem with method 200 is the customer pays for the resource-time even though the resources may be used only a fraction of that time. For example, if the additional processors are used primarily during the eight hour day shift, the customer ends up paying for capacity that goes mostly unused during the other two shifts. In the example above, if the customer purchases sixty processor-days, and two processors are being enabled, these two processors are enabled for exactly thirty days regardless of workload during that time. While this is a vast improvement over prior systems that do not provide temporary capacity on demand, it still has its drawbacks.
  • An apparatus and method provides the capability of metering temporary capacity on demand in a computer system.
  • a resource-time is specified, such as processor-days.
  • the actual usage of the resource is monitored, and the customer is charged for only the actual usage of the resource. In this manner a customer may purchase a specified resource-time, and is only charged for the time that the resource is actually used.
  • the preferred embodiments extend to metering temporary capacity on demand in a logically partitioned computer system. If a resource is shared, the actual usage of the resource is monitored, and the customer is only billed for actual usage that exceeds a predetermined non-zero threshold.
  • FIG. 1 is a block diagram of a computer apparatus in accordance with the preferred embodiments
  • FIG. 2 is a flow diagram of a method for providing temporary capacity on demand
  • FIG. 3 is a flow diagram of a first method in accordance with the preferred embodiments that allows a customer to be billed for metered usage of temporary resources;
  • FIG. 4 is a flow diagram of a second method in accordance with the preferred embodiments that allows a customer to prepay for metered usage of temporary resources;
  • FIG. 5 is a block diagram showing logical components in a logically partitioned computer system
  • FIG. 6 is a flow diagram of a third method in accordance with the preferred embodiments that allows a customer to be billed for metered usage of temporary resources in a logically partitioned computer system;
  • FIG. 7 is a flow diagram of a fourth method in accordance with the preferred embodiments that allows a customer to prepay for metered usage of temporary resources in a logically partitioned computer system.
  • a computer system 100 is an enhanced IBM eServer iSeries computer system, and represents one suitable type of computer system in accordance with the preferred embodiments.
  • computer system 100 comprises one or more processors 110 connected to a main memory 120 , a mass storage interface 130 , a display interface 140 , a network interface 150 , and a plurality of I/O slots 180 .
  • processors 110 connected to a main memory 120 , a mass storage interface 130 , a display interface 140 , a network interface 150 , and a plurality of I/O slots 180 .
  • Mass storage interface 130 is used to connect mass storage devices (such as a direct access storage device 155 ) to computer system 100 .
  • CD RW drive which may read data from a CD R.W. 195 .
  • mass storage interface 130 , display interface 140 , and network interface 150 may actually be implemented in adapters coupled to I/O slots 180 .
  • Main memory 120 contains data 121 , an operating system 122 , and a capacity manager 123 .
  • Data 121 is any data that may be read or written by any processor 110 or any other device that may access the main memory 120 .
  • Operating system 122 is a multitasking operating system, such as OS/400, AIX, or Linux; however, those skilled in the art will appreciate that the spirit and scope of the present invention is not limited to any one operating system. Any suitable operating system may be used.
  • Operating system 122 is a sophisticated program that contains low-level code to manage the resources of computer system 100 . Some of these resources are processor 110 , main memory 120 , mass storage interface 130 , display interface 140 , network interface 150 , system bus 160 , and I/O slots 180 .
  • Capacity manager 123 provides metered capacity on demand.
  • the capacity manager 123 includes an enablement code mechanism 124 , which is used to determine whether an enablement code 125 is valid, and to enable one or more resources when the enablement code is determined to be valid.
  • the resource allocator 126 is the mechanism that allocates resources for use. Thus, when the enablement mechanism 124 determines that an enablement code 125 is valid, the resource allocator 126 makes the corresponding resource(s) available for use.
  • Capacity manager 123 also includes an actual use meter 127 that measures usage in resource-time units 128 . In a first embodiment, the actual use meter tracks actual usage in resource-time units, and the customer is then billed for the actual usage. In a second embodiment, the actual use meter has a prepaid number of resource-time units, and the actual use is deducted from the prepaid resource-time units until the prepaid resource-time units are exhausted.
  • Computer system 100 utilizes well known virtual addressing mechanisms that allow the programs of computer system 100 to behave as if they only have access to a large, single storage entity instead of access to multiple, smaller storage entities such as main memory 120 and DASD device 155 . Therefore, data 121 , operating system 122 , and capacity manager 123 are shown to reside in main memory 120 , those skilled in the art will recognize that these items are not necessarily all completely contained in main memory 120 at the same time. It should also be noted that the term “memory” is used herein to generically refer to the entire virtual memory of computer system 100 .
  • Processor 110 may be constructed from one or more microprocessors and/or integrated circuits. Processor 110 executes program instructions stored in main memory 120 . Main memory 120 stores programs and data that processor 110 may access. When computer system 100 starts up, processor 110 initially executes the program instructions that make up the operating system 122 .
  • I/O interfaces that are used in the preferred embodiment each may include separate, fully programmed microprocessors that are used to off-load compute-intensive processing from processor 110 , as in iSeries input/output processors, or may be simple industry standard I/O adapters (IOAs).
  • IOAs industry standard I/O adapters
  • Display interface 140 is used to directly connect one or more displays 165 to computer system 100 .
  • These displays 165 which may be non-intelligent (i.e., dumb) terminals or fully programmable workstations, are used to allow system administrators and users to communicate with computer system 100 . Note, however, that while display interface 140 is provided to support communication with one or more displays 165 , computer system 100 does not necessarily require a display 165 , because all needed interaction with users and other processes may occur via network interface 150 .
  • Network interface 150 is used to connect other computer systems and/or workstations (e.g., 175 in FIG. 1 ) to computer system 100 across a network 170 .
  • the present invention applies equally no matter how computer system 100 may be connected to other computer systems and/or workstations, regardless of whether the network connection 170 is made using present-day analog and/or digital techniques or via some networking mechanism of the future.
  • many different network protocols can be used to implement a network. These protocols are specialized computer programs that allow computers to communicate across network 170 .
  • TCP/IP Transmission Control Protocol/Internet Protocol
  • a method 300 in accordance with a first embodiment bills a customer for actual use of temporary resources in a computer system.
  • the customer requests an enablement code (step 310 ).
  • the provider of the computer system sends the enablement code to the customer (step 320 ).
  • the enablement code includes a specification of resource-time.
  • the resources specified in the enablement code are then enabled (step 330 ).
  • the customer may then use the resources (step 340 ).
  • the actual usage of the resources is metered (step 350 ).
  • step 360 a record of metered resource usage is sent to the resource provider (step 370 ), and the resource provider then sends a bill to the customer for the metered resource usage (step 380 ).
  • the advantage of method 300 when compared to method 200 in FIG. 2 is the customer is only charged for the actual usage of the resources.
  • the sixty processor days will last for a total of ninety days instead of the thirty days provided by method 200 in FIG. 2 .
  • Two processors times 1 ⁇ 3 of a day usage per calendar day equals 2 ⁇ 3 of a processor day per calendar day.
  • method 300 may include the ability to bill at a higher rate for a predetermined resource-time (such as sixty processor-days), then bill at a lower rate once the predetermined resource-time has been used.
  • a predetermined resource-time such as sixty processor-days
  • the record of metered resource usage may be sent to the provider via any suitable carrier.
  • the customer queries the computer system to determine metered usage, and reports the metered usage on a form that is sent or faxed to the resource provider.
  • the capacity manager automatically sends the record of metered usage to the provider via the Internet, and the customer is then billed for the metered usage.
  • other combinations and variations are possible, all of which are within the scope of the preferred embodiments.
  • Another option is to allow the customer to prepay for a predetermined amount of resource-time, and to deduct actual usage from the prepaid amount. This is similar to a prepaid phone card that has a specified number of minutes, and deducts from the total as minutes are used.
  • One implementation of a prepaid method is shown as method 400 in FIG. 4 .
  • the customer prepays for a specified resource-time (step 410 ).
  • the customer requests an enablement code for the prepaid resource-time (step 420 ).
  • the resource supplier then provides the enablement code to the customer (step 430 ), which includes a specification of prepaid resource-time.
  • the resources are then enabled (step 440 ) and used (step 450 ).
  • a modification to method 400 in FIG. 4 within the scope of the preferred embodiments is the ability to renew the prepaid resource-time.
  • some predetermined threshold e.g. 20% of initial amount
  • the customer could be prompted to prepay for additional resource-time. If the customer does so before the prepaid resource-time is used up, the additional resource-time is added to the remaining balance, allowing the computer system to continue operating with the additional resources without interruption.
  • FIG. 5 one specific implementation of a logically partitioned computer system 500 includes N logical partitions, with each logical partition executing its own respective operating system 526 .
  • logical partitions 525 A . . . 525 N are shown executing their respective operating systems 526 A . . . 526 N.
  • the operating system 526 in each logical partition may be the same as the operating system in other partitions, or may be a completely different operating system.
  • one partition can run the OS/400 operating system, while a different partition can run another instance of OS/400, possibly a different release, or with different environment settings (e.g., time zone).
  • the operating systems in the logical partitions could even be different than OS/400, provided it is compatible with the hardware (such as AIX or Linux). In this manner the logical partitions can provide completely different computing environments on the same physical computer system.
  • partition manager 540 The logical partitions are managed by a partition manager 540 .
  • partition manager 540 One example of suitable partition manager 540 is known as a “hypervisor” in IBM terminology.
  • Partition manager 540 manages resources 550 , shown in FIG. 5 as resource 550 A through resource 550 X.
  • a “resource” in this context may be any hardware or software that may be controlled by partition manager 540 .
  • hardware resources include processors, memory, and hard disk drives.
  • software resources include a database, internal communications (such as a logical LAN), or applications (such as word processors, e-mail, etc.).
  • the partition manager 540 controls which resources 550 may be used by the logical partitions 525 .
  • FIG. 5 shows dedicated resources 580 A . . . 580 N that correspond to each logical partition 525 A . . . 525 N.
  • a method 600 in accordance with the preferred embodiments begins when a customer requests an enablement code for a temporary resource on a computer system that includes logical partitions (step 602 ).
  • the computer supplier provides the enablement code to the customer, which includes a specification of which resource to enable (step 604 ).
  • the resource is then marked as available (step 606 ). This means that the resource is placed in the pool of available resources 560 that have not yet been assigned to any logical partition. What happens next depends on whether the resource is then allocated by the partition manager as a dedicated resource to a particular partition, or whether the resource is allocated for shared use (step 610 ).
  • step 610 YES
  • a record of the metered resource usage is then sent to the resource provider (step 632 ), and the resource provider then sends a bill for the metered resource usage to the customer (step 634 ).
  • the resource is considered to be 100% in use regardless of the actual usage in the dedicated partition. Therefore, every actual minute the resource is dedicated to a partition is a resource-minute that is charged to the customer.
  • method 600 is similar to method 200 in FIG. 2 that bills the customer according to the time a resource is enabled regardless of its actual use. This type of billing makes sense for logical partitions that have dedicated use of a resource, because that resource is unavailable for other logical partitions to use.
  • step 610 NO
  • multiple logical partitions may use the shared resource (step 640 ).
  • One advantage of the present invention is the ability of a logical partition service provider being able to determine which logical partition exceeded allocations (and so was metered) so the customer using metered capacity can be billed by the service provider.
  • a method 700 in accordance with the preferred embodiments shows the case when a customer prepays for resource-time (step 710 ) in a logically partitioned computer system, rather than being billed (as shown in FIG. 6 ).
  • step 720 NO
  • the shared resources are used by the logical partitions (step 750 ).
  • step 760 YES
  • the actual usage over the threshold is metered (step 762 )
  • the metered use is compared to the prepaid resource-time.
  • method 700 could include steps that allow renewing the prepaid time so the resource metered use never arrives at the prepaid resource-time, thereby preventing the resource from being disabled.

Abstract

An apparatus and method provides the capability of metering temporary capacity on demand in a computer system. A resource-time is specified, such as processor-days. The actual usage of the resource is monitored, and the customer is charged for only the actual usage of the resource. In this manner a customer may purchase a specified resource-time, and is only charged for the time that the resource is actually used. The preferred embodiments extend to metering temporary capacity on demand in a logically partitioned computer system. If a resource is shared, the actual usage of the resource is monitored, and the customer is only billed for actual usage that exceeds a predetermined non-zero threshold.

Description

    CROSS-REFERENCE TO PARENT APPLICATION
  • This patent application is a continuation of U.S. Ser. No. 10/616,676 filed on Jul. 10, 2003, which is incorporated herein by reference.
  • BACKGROUND OF THE INVENTION
  • 1. Technical Field
  • This invention generally relates to data processing, and more specifically relates to utilization of resources in a computer system.
  • 2. Background Art
  • Since the dawn of the computer age, computer systems have evolved into extremely sophisticated devices that may be found in many different settings. Computer systems typically include a combination of hardware (e.g., semiconductors, circuit boards, etc.) and software (e.g., computer programs). As advances in semiconductor processing and computer architecture push the performance of the computer hardware higher, more sophisticated computer software has evolved to take advantage of the higher performance of the hardware, resulting in computer systems today that are much more powerful than just a few years ago.
  • One problem with computer systems today is balancing the cost of the computer hardware with fluctuating demands on computer resources. In most networked computer systems, there are times when the computing demands are relatively low, and other times when the computing demands are very high. If a company purchases a computer system that is capable of meeting peak demand, much of the capacity of the computer system will go unused during non-peak times. In addition, purchasing capacity to meet peak demand is costly. If a company purchases a computer system that is capable of meeting average demand, the cost is lower, but the performance of the computer system suffers during peak times.
  • One way to provide a more flexible solution allows a computer user to buy a computer system that has some resources installed, but initially disabled. When the customer determines that more capacity is needed, the customer may enter into an arrangement with the provider of the computer system to enable certain resources for a fixed period of time. This works out particularly well for companies that have seasonal peaks. The companies can purchase a computer system at a reasonable cost that has the capability of providing enhanced computing power during the peak season. The concept of providing temporary capacity on demand is the subject matter of the related patent application “Method to Provide On-Demand Resource Access”, Ser. No. 10/406,652, filed on Apr. 3, 2003.
  • Referring to FIG. 2, a flow diagram of one suitable method 200 for providing temporary capacity on demand begins by the customer requesting an enablement code from the manufacturer (step 210). The customer receives the enablement code, which includes a specification of resource-time (step 220). The term “resource-time” is a general term that allows specifying any resource or combination of resources for any suitable period of time. One example of resource-time is processor-days. The customer enters the enablement code, which enables the resources on the computer system (step 230). A timer is then started (step 240). The user may then use the resources (step 250) as long as the resource-time has not expired (step 260=NO). Once the resource-time expires (step 260=YES), the resources are disabled (step 270).
  • A simple example will show the usefulness of method 200. Let's assume that a company that sells goods via catalog sales experiences peak demand in November and December of each year due to holiday shopping. The company could purchase a computer system that has one or more additional processors that are installed but initially disabled. The company may then contract with the provider of the computer system to enable the additional processor(s) for a set period of time. Let's assume that the computer system has two additional processors, and let's assume that the peak buying period runs for the thirty day period from November 15th to December 14th. The customer could purchase sixty processor-days of additional capacity beginning on November 15th. These two additional processors will then be enabled for the thirty day period (providing the sixty processor-days of additional capacity). Once the sixty processor-days have elapsed, the two additional processors are disabled.
  • One problem with method 200 is the customer pays for the resource-time even though the resources may be used only a fraction of that time. For example, if the additional processors are used primarily during the eight hour day shift, the customer ends up paying for capacity that goes mostly unused during the other two shifts. In the example above, if the customer purchases sixty processor-days, and two processors are being enabled, these two processors are enabled for exactly thirty days regardless of workload during that time. While this is a vast improvement over prior systems that do not provide temporary capacity on demand, it still has its drawbacks.
  • Without a way to provide temporary capacity on demand in a way that allows customers to pay for only the actual use of temporary resources, the computer industry will not be able to meet the demands of customers who prefer to pay for temporary resources based on actual usage.
  • DISCLOSURE OF INVENTION
  • An apparatus and method provides the capability of metering temporary capacity on demand in a computer system. A resource-time is specified, such as processor-days. The actual usage of the resource is monitored, and the customer is charged for only the actual usage of the resource. In this manner a customer may purchase a specified resource-time, and is only charged for the time that the resource is actually used. The preferred embodiments extend to metering temporary capacity on demand in a logically partitioned computer system. If a resource is shared, the actual usage of the resource is monitored, and the customer is only billed for actual usage that exceeds a predetermined non-zero threshold.
  • The foregoing and other features and advantages of the invention will be apparent from the following more particular description of preferred embodiments of the invention, as illustrated in the accompanying drawings.
  • BRIEF DESCRIPTION OF DRAWINGS
  • The preferred embodiments of the present invention will hereinafter be described in conjunction with the appended drawings, where like designations denote like elements, and:
  • FIG. 1 is a block diagram of a computer apparatus in accordance with the preferred embodiments;
  • FIG. 2 is a flow diagram of a method for providing temporary capacity on demand;
  • FIG. 3 is a flow diagram of a first method in accordance with the preferred embodiments that allows a customer to be billed for metered usage of temporary resources;
  • FIG. 4 is a flow diagram of a second method in accordance with the preferred embodiments that allows a customer to prepay for metered usage of temporary resources;
  • FIG. 5 is a block diagram showing logical components in a logically partitioned computer system;
  • FIG. 6 is a flow diagram of a third method in accordance with the preferred embodiments that allows a customer to be billed for metered usage of temporary resources in a logically partitioned computer system; and
  • FIG. 7 is a flow diagram of a fourth method in accordance with the preferred embodiments that allows a customer to prepay for metered usage of temporary resources in a logically partitioned computer system.
  • BEST MODE FOR CARRYING OUT THE INVENTION
  • Referring to FIG. 1, a computer system 100 is an enhanced IBM eServer iSeries computer system, and represents one suitable type of computer system in accordance with the preferred embodiments. Those skilled in the art will appreciate that the mechanisms and apparatus of the present invention apply equally to any computer system. As shown in FIG. 1, computer system 100 comprises one or more processors 110 connected to a main memory 120, a mass storage interface 130, a display interface 140, a network interface 150, and a plurality of I/O slots 180. These system components are interconnected through the use of a system bus 160. Mass storage interface 130 is used to connect mass storage devices (such as a direct access storage device 155) to computer system 100. One specific type of direct access storage device is a CD RW drive, which may read data from a CD R.W. 195. Note that mass storage interface 130, display interface 140, and network interface 150 may actually be implemented in adapters coupled to I/O slots 180.
  • Main memory 120 contains data 121, an operating system 122, and a capacity manager 123. Data 121 is any data that may be read or written by any processor 110 or any other device that may access the main memory 120. Operating system 122 is a multitasking operating system, such as OS/400, AIX, or Linux; however, those skilled in the art will appreciate that the spirit and scope of the present invention is not limited to any one operating system. Any suitable operating system may be used. Operating system 122 is a sophisticated program that contains low-level code to manage the resources of computer system 100. Some of these resources are processor 110, main memory 120, mass storage interface 130, display interface 140, network interface 150, system bus 160, and I/O slots 180.
  • Capacity manager 123 provides metered capacity on demand. The capacity manager 123 includes an enablement code mechanism 124, which is used to determine whether an enablement code 125 is valid, and to enable one or more resources when the enablement code is determined to be valid. The resource allocator 126 is the mechanism that allocates resources for use. Thus, when the enablement mechanism 124 determines that an enablement code 125 is valid, the resource allocator 126 makes the corresponding resource(s) available for use. Capacity manager 123 also includes an actual use meter 127 that measures usage in resource-time units 128. In a first embodiment, the actual use meter tracks actual usage in resource-time units, and the customer is then billed for the actual usage. In a second embodiment, the actual use meter has a prepaid number of resource-time units, and the actual use is deducted from the prepaid resource-time units until the prepaid resource-time units are exhausted.
  • Computer system 100 utilizes well known virtual addressing mechanisms that allow the programs of computer system 100 to behave as if they only have access to a large, single storage entity instead of access to multiple, smaller storage entities such as main memory 120 and DASD device 155. Therefore, data 121, operating system 122, and capacity manager 123 are shown to reside in main memory 120, those skilled in the art will recognize that these items are not necessarily all completely contained in main memory 120 at the same time. It should also be noted that the term “memory” is used herein to generically refer to the entire virtual memory of computer system 100.
  • Processor 110 may be constructed from one or more microprocessors and/or integrated circuits. Processor 110 executes program instructions stored in main memory 120. Main memory 120 stores programs and data that processor 110 may access. When computer system 100 starts up, processor 110 initially executes the program instructions that make up the operating system 122.
  • Although computer system 100 is shown to contain only a single system bus, those skilled in the art will appreciate that the present invention may be practiced using a computer system that has multiple buses. In addition, the I/O interfaces that are used in the preferred embodiment each may include separate, fully programmed microprocessors that are used to off-load compute-intensive processing from processor 110, as in iSeries input/output processors, or may be simple industry standard I/O adapters (IOAs).
  • Display interface 140 is used to directly connect one or more displays 165 to computer system 100. These displays 165, which may be non-intelligent (i.e., dumb) terminals or fully programmable workstations, are used to allow system administrators and users to communicate with computer system 100. Note, however, that while display interface 140 is provided to support communication with one or more displays 165, computer system 100 does not necessarily require a display 165, because all needed interaction with users and other processes may occur via network interface 150.
  • Network interface 150 is used to connect other computer systems and/or workstations (e.g., 175 in FIG. 1) to computer system 100 across a network 170. The present invention applies equally no matter how computer system 100 may be connected to other computer systems and/or workstations, regardless of whether the network connection 170 is made using present-day analog and/or digital techniques or via some networking mechanism of the future. In addition, many different network protocols can be used to implement a network. These protocols are specialized computer programs that allow computers to communicate across network 170. TCP/IP (Transmission Control Protocol/Internet Protocol) is an example of a suitable network protocol.
  • At this point, it is important to note that while the present invention has been and will continue to be described in the context of a fully functional computer system, those skilled in the art will appreciate that the present invention is capable of being distributed as a program product in a variety of forms, and that the present invention applies equally regardless of the particular type of computer readable signal bearing media used to actually carry out the distribution. Examples of suitable signal bearing media include: recordable type media such as floppy disks and CD RW (e.g., 195 of FIG. 1), and transmission type media such as digital and analog communications links.
  • Referring now to FIG. 3, a method 300 in accordance with a first embodiment bills a customer for actual use of temporary resources in a computer system. First, the customer requests an enablement code (step 310). The provider of the computer system sends the enablement code to the customer (step 320). Note that the enablement code includes a specification of resource-time. The resources specified in the enablement code are then enabled (step 330). The customer may then use the resources (step 340). The actual usage of the resources is metered (step 350). The usage of resources in step 340 and metering of actual usage in step 350 continues as long as it is not time to bill (step 360=NO). Once it is time to bill (step 360=YES), a record of metered resource usage is sent to the resource provider (step 370), and the resource provider then sends a bill to the customer for the metered resource usage (step 380). The advantage of method 300 when compared to method 200 in FIG. 2 is the customer is only charged for the actual usage of the resources. Thus, if two processors are enabled for sixty processor-days, and the two processors are used on average only eight hours of each twenty four hour day, the sixty processor days will last for a total of ninety days instead of the thirty days provided by method 200 in FIG. 2. Two processors times ⅓ of a day usage per calendar day equals ⅔ of a processor day per calendar day. Because only ⅔ of a processor day is expended per calendar day, the sixty processor days will last for ninety calendar days instead of the thirty calendar days that would result using method 200 in FIG. 2. In addition, method 300 may include the ability to bill at a higher rate for a predetermined resource-time (such as sixty processor-days), then bill at a lower rate once the predetermined resource-time has been used.
  • The record of metered resource usage may be sent to the provider via any suitable carrier. In a manual example, the customer queries the computer system to determine metered usage, and reports the metered usage on a form that is sent or faxed to the resource provider. In an automatic example, the capacity manager automatically sends the record of metered usage to the provider via the Internet, and the customer is then billed for the metered usage. Of course, other combinations and variations are possible, all of which are within the scope of the preferred embodiments.
  • Another option is to allow the customer to prepay for a predetermined amount of resource-time, and to deduct actual usage from the prepaid amount. This is similar to a prepaid phone card that has a specified number of minutes, and deducts from the total as minutes are used. One implementation of a prepaid method is shown as method 400 in FIG. 4. The customer prepays for a specified resource-time (step 410). The customer then requests an enablement code for the prepaid resource-time (step 420). The resource supplier then provides the enablement code to the customer (step 430), which includes a specification of prepaid resource-time. The resources are then enabled (step 440) and used (step 450). The actual usage of the resources is metered (step 460), and deducted from the prepaid resource-time. Steps 450 and 460 continue as long as the metered use is less than the prepaid resource-time (step 470=YES). Once the metered use is no longer less than the prepaid resource time (step 470=NO), the resources are disabled (step 480).
  • A modification to method 400 in FIG. 4 within the scope of the preferred embodiments is the ability to renew the prepaid resource-time. Thus, if the prepaid resource time gets to some predetermined threshold (e.g., 20% of initial amount), the customer could be prompted to prepay for additional resource-time. If the customer does so before the prepaid resource-time is used up, the additional resource-time is added to the remaining balance, allowing the computer system to continue operating with the additional resources without interruption.
  • While the examples discussed with reference to FIGS. 1, 3 and 4 above do not have logical partitions, the preferred embodiments also extend to a logically partitioned computer system. Referring to FIG. 5, one specific implementation of a logically partitioned computer system 500 includes N logical partitions, with each logical partition executing its own respective operating system 526. In FIG. 5, logical partitions 525A . . . 525N are shown executing their respective operating systems 526A . . . 526N. The operating system 526 in each logical partition may be the same as the operating system in other partitions, or may be a completely different operating system. Thus, one partition can run the OS/400 operating system, while a different partition can run another instance of OS/400, possibly a different release, or with different environment settings (e.g., time zone). The operating systems in the logical partitions could even be different than OS/400, provided it is compatible with the hardware (such as AIX or Linux). In this manner the logical partitions can provide completely different computing environments on the same physical computer system.
  • The logical partitions are managed by a partition manager 540. One example of suitable partition manager 540 is known as a “hypervisor” in IBM terminology. Partition manager 540 manages resources 550, shown in FIG. 5 as resource 550A through resource 550X. A “resource” in this context may be any hardware or software that may be controlled by partition manager 540. Examples of hardware resources include processors, memory, and hard disk drives. Examples of software resources include a database, internal communications (such as a logical LAN), or applications (such as word processors, e-mail, etc.). The partition manager 540 controls which resources 550 may be used by the logical partitions 525. A resource, once made available to the partition manager 540, is categorized as an available resource 560 if it has not yet been assigned to a logical partition, is categorized as a shared resource 570 if multiple logical partitions may access the resource, and is categorized as a dedicated resource 580 if it has been exclusively assigned to a logical partition. FIG. 5 shows dedicated resources 580A . . . 580N that correspond to each logical partition 525A . . . 525N.
  • Referring to FIG. 6, a method 600 in accordance with the preferred embodiments begins when a customer requests an enablement code for a temporary resource on a computer system that includes logical partitions (step 602). The computer supplier provides the enablement code to the customer, which includes a specification of which resource to enable (step 604). The resource is then marked as available (step 606). This means that the resource is placed in the pool of available resources 560 that have not yet been assigned to any logical partition. What happens next depends on whether the resource is then allocated by the partition manager as a dedicated resource to a particular partition, or whether the resource is allocated for shared use (step 610). If the resource is to be a dedicated resource to a logical partition (step 610=YES), a meter timer is started (step 620) and the resource is used (step 630). This continues (step 630=NO) until the meter timer indicates it is time to bill (step 630=YES). A record of the metered resource usage is then sent to the resource provider (step 632), and the resource provider then sends a bill for the metered resource usage to the customer (step 634). Note that when a resource is configured to a dedicated partition (step 610=YES), the resource is considered to be 100% in use regardless of the actual usage in the dedicated partition. Therefore, every actual minute the resource is dedicated to a partition is a resource-minute that is charged to the customer. This is why a meter time is started in step 620, and why the record of metered usage in step 632 is the resource multiplied by the time elapsed on the meter timer. In this sense, method 600 is similar to method 200 in FIG. 2 that bills the customer according to the time a resource is enabled regardless of its actual use. This type of billing makes sense for logical partitions that have dedicated use of a resource, because that resource is unavailable for other logical partitions to use.
  • If the resource is allocated by the partition manager as a shared resource (step 610=NO), multiple logical partitions may use the shared resource (step 640). We assume a threshold value for shared use is specified. As long as the shared use does not exceed the threshold (step 650=NO), no time is metered. Only when the shared use exceeds the specified threshold (step 650=YES) does the capacity manager meter the shared use, and then only the shared use over the threshold is metered (step 652). Once it is time to bill (step 660=YES), the record of metered resource usage is sent to the resource provider (step 662), and the resource provider sends a bill for the metered resource usage to the customer (step 664).
  • The threshold that determines when the customer is charged is preferably determined by the capacity of the system before the temporary resources were enabled. For example, if one processor is allocated to the shared pool for five shared partitions that are configured for equal access to the pool, each of the partitions can use up to 20% of the processor clock cycles. Usage is averaged over a period of time and if any partition's usage exceeds 20% of the processor cycles, work from that partition is not dispatched to the processor before work from the other partitions, permitting the other partitions' usage to climb to their configured 20%. Now, let's assume that two additional processors are made available on demand. These two processors are initially marked available (step 606), and are then allocated as shared resources (step 610=NO). When the aggregate pool usage of processor clock cycles exceeds the amount one processor provides over an average time period, the additional cycles used are metered, and accumulate until a processor-minute's worth of cycles have been used and a processor-minute is charged to the customer. Of course, any suitable resource-time increment may be used. In this manner, different logical partitions may share a resource in a logically partitioned computer system and will only be charged according to their actual respective use of the resource. One advantage of the present invention is the ability of a logical partition service provider being able to determine which logical partition exceeded allocations (and so was metered) so the customer using metered capacity can be billed by the service provider.
  • Referring now to FIG. 7, a method 700 in accordance with the preferred embodiments shows the case when a customer prepays for resource-time (step 710) in a logically partitioned computer system, rather than being billed (as shown in FIG. 6). The enablement code is requested (step 712) and received (step 714), and the resource is made available for assignment to a logical partition (step 716). If the resource is dedicated to a partition (step 720=YES), the meter timer is started (step 730), and the resource is used (step 732) until the metered use equals the prepaid resource time (step 740=NO). At this point, the resource is disabled (step 742). If the resource is shared among logical partitions (step 720=NO), the shared resources are used by the logical partitions (step 750). When the shared use exceeds the specified threshold (step 760=YES), the actual usage over the threshold is metered (step 762), and the metered use is compared to the prepaid resource-time. Once the metered use is equal to the prepaid resource-time (step 720=NO), the resource is disabled (step 772) such that no new work is dispatched to the processor. Note that method 700 could include steps that allow renewing the prepaid time so the resource metered use never arrives at the prepaid resource-time, thereby preventing the resource from being disabled.
  • The preferred embodiments provide significant advantages over the known prior art. Now temporary capacity on demand may be provided on a metered basis, where the customer is only charged for actual usage of the resource. This is analogous to a telephone bill or electric bill, where the customer pays based on actual usage of resources. The ability to meter and bill based on actual usage provides enhanced capabilities in a logically partitioned computer system, because logical partitions that share resources may now each be charged for only actual usage of the shared resources. Because actual usage may now be metered and billed, the level of granularity for charging customers is reduced. For example, instead of billing for processor-days, one could bill for processor-minutes, processor-seconds, or even processor cycles.
  • One skilled in the art will appreciate that many variations are possible within the scope of the present invention. Thus, while the invention has been particularly shown and described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that these and other changes in form and details may be made therein without departing from the spirit and scope of the invention.

Claims (16)

1. An apparatus comprising:
at least one processor;
a memory coupled to the at least one processor;
a plurality of logical partitions defined on the apparatus;
at least one resource that provides temporary capacity when requested by a user of the apparatus; and
a capacity manager residing in the memory and executed by the at least one processor, the capacity manager managing access to the at least one resource by the plurality of logical partitions, the capacity manager receiving an enablement code from a user of the apparatus wherein the enablement code includes a specified resource-time the capacity manager determining whether the enablement code is valid, and if the enablement code is valid, performing the steps of:
enabling the at least one resource for metered operation by a selected logical partition;
determining whether the enabled resource is shared, and if so, the capacity manager metering actual use of the at least one resource by each logical partition above a predetermined non-zero threshold corresponding to each logical partition that specifies allowable usage of the at least one resource by the corresponding logical partition, and billing for the actual use by each logical partition above the corresponding predetermined non-zero threshold.
2. The apparatus of claim 1 wherein the capacity manager bills for the actual use by each logical partition by generating a bill for metered resource-time for each logical partition that represents actual use of the at least one resource by the logical partition.
3. The apparatus of claim 1 wherein the capacity manager bills for the actual use by each logical partition by deducting metered resource-time for each logical partition from a prepaid resource-time for each logical partition.
4. (canceled)
5. The apparatus of claim 1 further comprising a resource allocator that enables the at least one resource before the capacity manager meters the actual use of the at least one resource.
6. The apparatus of claim 5 wherein the resource allocator disables the at least one resource when the capacity manager metered actual use of the at least one resource exceeds a specified resource-time.
7. (canceled)
8. A computer-readable program product comprising:
(A) a capacity manager that manages access to at least one resource by a plurality of logical partitions in a computer system, the capacity manager receiving an enablement code from a user of the computer system, wherein the enablement code includes a specified resource-time, the capacity manager determining whether the enablement code is valid, and if the enablement code is valid, performing the steps of:
enabling the at least one resource for metered operation by a selected logical partition;
determining whether the enabled resource is shared, and if so, the capacity manager metering actual use of the at least one resource by each logical partition above a predetermined non-zero threshold corresponding to each logical partition that specifies allowable usage of the at least one resource by the corresponding logical partition, and billing for the actual use by each logical partition above the corresponding predetermined non-zero threshold; and
(B) recordable media bearing the capacity manager.
9-10. (canceled)
11. The program product of claim 8 wherein the capacity manager bills for the actual use by each logical partition by generating a bill for metered resource-time for each logical partition that represents actual use of the at least one resource by the logical partition.
12. The program product of claim 8 wherein the capacity manager bills for the actual use by each logical partition by deducting metered resource-time for each logical partition from a prepaid resource-time for each logical partition.
13. (canceled)
14. The program product of claim 8 further comprising a resource allocator that enables the at least one resource before the capacity manager meters the actual use of the at least one resource.
15. The program product of claim 14 wherein the resource allocator disables the at least one resource when the capacity manager metered actual use of the at least one resource exceeds a specified resource-time.
16. (canceled)
17. An apparatus comprising:
at least one processor;
a memory coupled to the at least one processor;
a plurality of logical partitions defined on the apparatus;
at least one resource that provides temporary capacity when requested by a user of the apparatus; and
a capacity manager residing in the memory and executed by the at least one processor, the capacity manager managing access to the at least one resource by the plurality of logical partitions, the capacity manager performing the steps of:
requesting an enablement code from a resource provider for the computer system;
receiving the enablement code from the resource provider, wherein the enablement code includes a specified resource-time for a selected resource;
enabling the selected resource for use;
if the selected resource is dedicated to one of the plurality of logical partitions, performing the steps of:
starting a meter timer;
using the selected resource until a time to bill occurs;
sending a record of metered usage to the resource provider based on value of the meter timer;
if the selected resource is not dedicated to one of the plurality of logical partitions and is shared between first and second logical partitions, performing the steps of:
the first logical partition using the selected resource without charge until the metered use of the selected resource by the first logical partition exceeds a first predetermined non-zero threshold that specifies allowable usage of the selected resource by the first logical partition;
metering use of the selected resource by the first logical partition that exceeds the first predetermined non-zero threshold until a time to bill occurs;
sending a record of metered usage of the selected resource that exceeds the first predetermined non-zero threshold to the resource provider;
the second logical partition using the selected resource without charge until the metered use of the selected resource by the second logical partition exceeds a second predetermined non-zero threshold that specifies allowable usage of the selected resource by the second logical partition;
metering use of the selected resource by the second logical partition that exceeds the second predetermined non-zero threshold until a time to bill occurs; and
sending a record of metered usage of the selected resource that exceeds the second predetermined non-zero threshold to the resource provider.
US12/131,066 2003-07-10 2008-05-31 Providing metered capacity of computer resources Abandoned US20080228644A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US12/131,066 US20080228644A1 (en) 2003-07-10 2008-05-31 Providing metered capacity of computer resources

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US10/616,676 US7627506B2 (en) 2003-07-10 2003-07-10 Method of providing metered capacity of temporary computer resources
US12/131,066 US20080228644A1 (en) 2003-07-10 2008-05-31 Providing metered capacity of computer resources

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US10/616,676 Continuation US7627506B2 (en) 2003-04-03 2003-07-10 Method of providing metered capacity of temporary computer resources

Publications (1)

Publication Number Publication Date
US20080228644A1 true US20080228644A1 (en) 2008-09-18

Family

ID=33564818

Family Applications (2)

Application Number Title Priority Date Filing Date
US10/616,676 Expired - Fee Related US7627506B2 (en) 2003-04-03 2003-07-10 Method of providing metered capacity of temporary computer resources
US12/131,066 Abandoned US20080228644A1 (en) 2003-07-10 2008-05-31 Providing metered capacity of computer resources

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US10/616,676 Expired - Fee Related US7627506B2 (en) 2003-04-03 2003-07-10 Method of providing metered capacity of temporary computer resources

Country Status (2)

Country Link
US (2) US7627506B2 (en)
TW (1) TWI338233B (en)

Cited By (38)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060156309A1 (en) * 2005-01-13 2006-07-13 Rhine Scott A Method for controlling resource utilization and computer system
US20090125370A1 (en) * 2007-11-08 2009-05-14 Genetic Finance Holdings Limited Distributed network for performing complex algorithms
US20100274736A1 (en) * 2009-04-28 2010-10-28 Genetic Finance Holdings Limited, AMS Trustees Limited Class-based distributed evolutionary algorithm for asset management and trading
US20120011036A1 (en) * 2010-07-12 2012-01-12 International Business Machines Corporation Advanced function usage-based billing
US20120011328A1 (en) * 2010-07-12 2012-01-12 International Business Machines Corporation Advanced function monitoring on a storage controller
US20120011514A1 (en) * 2010-07-12 2012-01-12 International Business Machines Corporation Generating an advanced function usage planning report
US20120233328A1 (en) * 2011-03-07 2012-09-13 Gravitant, Inc Accurately predicting capacity requirements for information technology resources in physical, virtual and hybrid cloud environments
US8725645B1 (en) * 2013-01-04 2014-05-13 Cetrus LLC Non-invasive metering system for software licenses
US8825560B2 (en) 2007-11-08 2014-09-02 Genetic Finance (Barbados) Limited Distributed evolutionary algorithm for asset management and trading
US8909570B1 (en) 2008-11-07 2014-12-09 Genetic Finance (Barbados) Limited Data mining technique with experience-layered gene pool
US8977581B1 (en) 2011-07-15 2015-03-10 Sentient Technologies (Barbados) Limited Data mining technique with diversity promotion
US9304895B1 (en) 2011-07-15 2016-04-05 Sentient Technologies (Barbados) Limited Evolutionary technique with n-pool evolution
US9367816B1 (en) 2011-07-15 2016-06-14 Sentient Technologies (Barbados) Limited Data mining technique with induced environmental alteration
US9466023B1 (en) 2007-11-08 2016-10-11 Sentient Technologies (Barbados) Limited Data mining technique with federated evolutionary coordination
US9710764B1 (en) 2011-07-15 2017-07-18 Sentient Technologies (Barbados) Limited Data mining technique with position labeling
US10025700B1 (en) 2012-07-18 2018-07-17 Sentient Technologies (Barbados) Limited Data mining technique with n-Pool evolution
US20180250554A1 (en) * 2017-03-03 2018-09-06 Sentient Technologies (Barbados) Limited Behavior Dominated Search in Evolutionary Search Systems
US10169747B2 (en) 2010-07-12 2019-01-01 International Business Machines Corporation Advanced function usage detection
US10268953B1 (en) 2014-01-28 2019-04-23 Cognizant Technology Solutions U.S. Corporation Data mining technique with maintenance of ancestry counts
US10430429B2 (en) 2015-09-01 2019-10-01 Cognizant Technology Solutions U.S. Corporation Data mining management server
US10956823B2 (en) 2016-04-08 2021-03-23 Cognizant Technology Solutions U.S. Corporation Distributed rule-based probabilistic time-series classifier
US11003994B2 (en) 2017-12-13 2021-05-11 Cognizant Technology Solutions U.S. Corporation Evolutionary architectures for evolution of deep neural networks
US11182677B2 (en) 2017-12-13 2021-11-23 Cognizant Technology Solutions U.S. Corporation Evolving recurrent networks using genetic programming
US11250328B2 (en) 2016-10-26 2022-02-15 Cognizant Technology Solutions U.S. Corporation Cooperative evolution of deep neural network structures
US11250314B2 (en) 2017-10-27 2022-02-15 Cognizant Technology Solutions U.S. Corporation Beyond shared hierarchies: deep multitask learning through soft layer ordering
US11281977B2 (en) 2017-07-31 2022-03-22 Cognizant Technology Solutions U.S. Corporation Training and control system for evolving solutions to data-intensive problems using epigenetic enabled individuals
US11288579B2 (en) 2014-01-28 2022-03-29 Cognizant Technology Solutions U.S. Corporation Training and control system for evolving solutions to data-intensive problems using nested experience-layered individual pool
US11403532B2 (en) 2017-03-02 2022-08-02 Cognizant Technology Solutions U.S. Corporation Method and system for finding a solution to a provided problem by selecting a winner in evolutionary optimization of a genetic algorithm
US11481639B2 (en) 2019-02-26 2022-10-25 Cognizant Technology Solutions U.S. Corporation Enhanced optimization with composite objectives and novelty pulsation
US11507844B2 (en) 2017-03-07 2022-11-22 Cognizant Technology Solutions U.S. Corporation Asynchronous evaluation strategy for evolution of deep neural networks
US11527308B2 (en) 2018-02-06 2022-12-13 Cognizant Technology Solutions U.S. Corporation Enhanced optimization with composite objectives and novelty-diversity selection
US11574201B2 (en) 2018-02-06 2023-02-07 Cognizant Technology Solutions U.S. Corporation Enhancing evolutionary optimization in uncertain environments by allocating evaluations via multi-armed bandit algorithms
US11574202B1 (en) 2016-05-04 2023-02-07 Cognizant Technology Solutions U.S. Corporation Data mining technique with distributed novelty search
US11663492B2 (en) 2015-06-25 2023-05-30 Cognizant Technology Solutions Alife machine learning system and method
US11669716B2 (en) 2019-03-13 2023-06-06 Cognizant Technology Solutions U.S. Corp. System and method for implementing modular universal reparameterization for deep multi-task learning across diverse domains
US11755979B2 (en) 2018-08-17 2023-09-12 Evolv Technology Solutions, Inc. Method and system for finding a solution to a provided problem using family tree based priors in Bayesian calculations in evolution based optimization
US11775841B2 (en) 2020-06-15 2023-10-03 Cognizant Technology Solutions U.S. Corporation Process and system including explainable prescriptions through surrogate-assisted evolution
US11783195B2 (en) 2019-03-27 2023-10-10 Cognizant Technology Solutions U.S. Corporation Process and system including an optimization engine with evolutionary surrogate-assisted prescriptions

Families Citing this family (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7594231B2 (en) * 2003-07-10 2009-09-22 International Business Machines Corporation Apparatus and method for assuring recovery of temporary resources in a logically partitioned computer system
US8135795B2 (en) 2003-04-03 2012-03-13 International Business Machines Corporation Method to provide on-demand resource access
US7627506B2 (en) 2003-07-10 2009-12-01 International Business Machines Corporation Method of providing metered capacity of temporary computer resources
US7493488B2 (en) 2003-07-24 2009-02-17 International Business Machines Corporation Method to disable on/off capacity in demand
JP2005339465A (en) * 2004-05-31 2005-12-08 Fujitsu Ltd Server
US8074223B2 (en) * 2005-01-31 2011-12-06 International Business Machines Corporation Permanently activating resources based on previous temporary resource usage
US8387052B2 (en) * 2005-03-14 2013-02-26 Qnx Software Systems Limited Adaptive partitioning for operating system
US9361156B2 (en) 2005-03-14 2016-06-07 2236008 Ontario Inc. Adaptive partitioning for operating system
CA2538503C (en) * 2005-03-14 2014-05-13 Attilla Danko Process scheduler employing adaptive partitioning of process threads
US8245230B2 (en) * 2005-03-14 2012-08-14 Qnx Software Systems Limited Adaptive partitioning scheduler for multiprocessing system
US8473376B2 (en) * 2005-03-23 2013-06-25 Hewlett-Packard Development Company, L.P. System, method, and computer program product for byte-based utility computing pricing
US7539647B2 (en) 2005-08-25 2009-05-26 Microsoft Corporation Using power state to enforce software metering state
US8874477B2 (en) 2005-10-04 2014-10-28 Steven Mark Hoffberg Multifactorial optimization system and method
JP4911984B2 (en) * 2006-02-08 2012-04-04 東京エレクトロン株式会社 Gas supply apparatus, substrate processing apparatus, gas supply method, and shower head
JP4751265B2 (en) * 2006-08-01 2011-08-17 株式会社日立製作所 Resource management system and method
US8320256B2 (en) * 2006-09-13 2012-11-27 International Business Machines Corporation Method, computer program product and system for managing usage of marginal capacity of computer resources
US20080077420A1 (en) * 2006-09-27 2008-03-27 Daryl Cromer System and Method for Securely Updating Remaining Time or Subscription Data for a Rental Computer
US7634561B2 (en) * 2006-10-26 2009-12-15 International Business Machines Corporation Application usage metering management system
US20080147555A1 (en) * 2006-12-18 2008-06-19 Daryl Carvis Cromer System and Method for Using a Hypervisor to Control Access to a Rental Computer
US7996820B2 (en) * 2007-01-04 2011-08-09 International Business Machines Corporation Determining proportionate use of system resources by applications executing in a shared hosting environment
US20090094455A1 (en) * 2007-10-09 2009-04-09 Microsoft Corporation Frequency Managed Performance
US8903983B2 (en) * 2008-02-29 2014-12-02 Dell Software Inc. Method, system and apparatus for managing, modeling, predicting, allocating and utilizing resources and bottlenecks in a computer network
US8935701B2 (en) 2008-03-07 2015-01-13 Dell Software Inc. Unified management platform in a computer network
US8332861B1 (en) * 2008-10-31 2012-12-11 Hewlett-Packard Development Company, L.P. Virtualized temporary instant capacity
US20130117168A1 (en) 2011-11-04 2013-05-09 Mark Henrik Sandstrom Maximizing Throughput of Multi-user Parallel Data Processing Systems
US8789065B2 (en) 2012-06-08 2014-07-22 Throughputer, Inc. System and method for input data load adaptive parallel processing
GB2490037A (en) * 2011-04-16 2012-10-17 Mark Henrik Sandstrom System and method for data processing billing
US9448847B2 (en) 2011-07-15 2016-09-20 Throughputer, Inc. Concurrent program execution optimization
US9495222B1 (en) 2011-08-26 2016-11-15 Dell Software Inc. Systems and methods for performance indexing
US9952902B1 (en) * 2013-04-10 2018-04-24 Amazon Technologies, Inc. Determining a set of application resources
US10469564B2 (en) * 2014-01-21 2019-11-05 International Business Machines Corporation Management of unreturned system pool resources
US10243973B2 (en) 2016-04-15 2019-03-26 Tangoe Us, Inc. Cloud optimizer

Citations (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6061732A (en) * 1997-05-26 2000-05-09 U. S. Philips Corporation Data streaming system utilizing an asynchronous technique for retrieving data from a stream server
US6061504A (en) * 1995-10-27 2000-05-09 Emc Corporation Video file server using an integrated cached disk array and stream server computers
US6230200B1 (en) * 1997-09-08 2001-05-08 Emc Corporation Dynamic modeling for resource allocation in a file server
US20020013802A1 (en) * 2000-07-26 2002-01-31 Toshiaki Mori Resource allocation method and system for virtual computer system
US20020016842A1 (en) * 2000-07-21 2002-02-07 Takashi Eki Method for charging fee for use of network resources and method and system for allotting network resources
US20020156824A1 (en) * 2001-04-19 2002-10-24 International Business Machines Corporation Method and apparatus for allocating processor resources in a logically partitioned computer system
US20020161891A1 (en) * 2001-04-25 2002-10-31 Tatsuo Higuchi System and method for computer resource marketing
US20020166117A1 (en) * 2000-09-12 2002-11-07 Abrams Peter C. Method system and apparatus for providing pay-per-use distributed computing resources
US20020178206A1 (en) * 2001-05-25 2002-11-28 Siemens Medical Solutions Health Services Corporation System and method for monitoring computer application and resource utilization
US20020178387A1 (en) * 2001-05-25 2002-11-28 John Theron System and method for monitoring and managing power use of networked information devices
US20030018870A1 (en) * 2001-07-17 2003-01-23 International Business Machines Corporation Appliance server with a drive partitioning scheme that accommodates application growth in size
US20030028653A1 (en) * 2001-08-06 2003-02-06 New John C. Method and system for providing access to computer resources
US20030093528A1 (en) * 2001-11-13 2003-05-15 Jerome Rolia Method and system for enabling resource sharing in a communication network having a plurality of application environments
US6584489B1 (en) * 1995-12-07 2003-06-24 Microsoft Corporation Method and system for scheduling the use of a computer system resource using a resource planner and a resource provider
US20030135580A1 (en) * 2001-12-28 2003-07-17 Camble Peter Thomas Method for using partitioning to provide capacity on demand in data libraries
US6625750B1 (en) * 1999-11-16 2003-09-23 Emc Corporation Hardware and software failover services for a file server
US20040088412A1 (en) * 2002-07-24 2004-05-06 Ranjit John System and method for highly-scalable real-time and time-based data delivery using server clusters
US20040111308A1 (en) * 2002-12-09 2004-06-10 Brighthaul Ltd. Dynamic resource allocation platform and method for time related resources
US20040148511A1 (en) * 2003-01-23 2004-07-29 Circenis Edgar I. Codeword-based auditing of computer systems and methods therefor
US20040199632A1 (en) * 2003-03-21 2004-10-07 Romero Francisco J. Assembly and method for balancing processors in a partitioned server
US20040215748A1 (en) * 2003-04-28 2004-10-28 International Business Machines Corporation Method, system, and computer program product for on demand enablement of dormant computing resources
US20040255048A1 (en) * 2001-08-01 2004-12-16 Etai Lev Ran Virtual file-sharing network
US20050015343A1 (en) * 2002-09-11 2005-01-20 Norihiro Nagai License management device, license management method, and computer program
US20050246705A1 (en) * 2002-07-25 2005-11-03 Sphera Corporation Method for dynamically allocating and managing resources in a computerized system having multiple consumers
US20050268063A1 (en) * 2004-05-25 2005-12-01 International Business Machines Corporation Systems and methods for providing constrained optimization using adaptive regulatory control
US7039784B1 (en) * 2001-12-20 2006-05-02 Info Value Computing Inc. Video distribution system using dynamic disk load balancing with variable sub-segmenting
US20060100962A1 (en) * 2004-10-23 2006-05-11 Wooldridge James L Permitting utilization of computer system resources in accordance with their licensing
US20060190615A1 (en) * 2005-01-21 2006-08-24 Panwar Shivendra S On demand peer-to-peer video streaming with multiple description coding
US7146496B2 (en) * 2003-01-23 2006-12-05 Hewlett-Packard Development Company, L.P. Methods and apparatus for managing temporary capacity in a computer system
US7155735B1 (en) * 1999-10-08 2006-12-26 Vulcan Patents Llc System and method for the broadcast dissemination of time-ordered data
US20060294238A1 (en) * 2002-12-16 2006-12-28 Naik Vijay K Policy-based hierarchical management of shared resources in a grid environment
US7322034B2 (en) * 2002-06-14 2008-01-22 Hewlett-Packard Development Company, L.P. Method and system for dynamically allocating computer system resources

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US115917A (en) * 1871-06-13 Improvement in hose-couplings
DE69228039T2 (en) * 1991-05-08 1999-08-05 Digital Equipment Corp LICENSE MANAGEMENT SYSTEM
US5956505A (en) * 1991-12-24 1999-09-21 Pitney Bowes Inc. Remote activation of software features in a data processing device
US6058423A (en) * 1996-12-23 2000-05-02 International Business Machines Corporation System and method for locating resources in a distributed network
US6301616B1 (en) * 1997-04-11 2001-10-09 Microsoft Corporation Pledge-based resource allocation system
US6385638B1 (en) 1997-09-04 2002-05-07 Equator Technologies, Inc. Processor resource distributor and method
US6460082B1 (en) * 1999-06-17 2002-10-01 International Business Machines Corporation Management of service-oriented resources across heterogeneous media servers using homogenous service units and service signatures to configure the media servers
JP2001331333A (en) 2000-05-18 2001-11-30 Hitachi Ltd Computer system and method for controlling computer system
JP4292693B2 (en) 2000-07-07 2009-07-08 株式会社日立製作所 Computer resource dividing apparatus and resource dividing method
US20020124168A1 (en) 2000-07-17 2002-09-05 Mccown Steven H. Method and system for upgrading a user environment
US7143413B2 (en) * 2002-05-15 2006-11-28 Hewlett-Packard Development Company, L.P. Method and system for allocating system resources among applications using weights
US7627506B2 (en) 2003-07-10 2009-12-01 International Business Machines Corporation Method of providing metered capacity of temporary computer resources

Patent Citations (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6061504A (en) * 1995-10-27 2000-05-09 Emc Corporation Video file server using an integrated cached disk array and stream server computers
US6584489B1 (en) * 1995-12-07 2003-06-24 Microsoft Corporation Method and system for scheduling the use of a computer system resource using a resource planner and a resource provider
US6061732A (en) * 1997-05-26 2000-05-09 U. S. Philips Corporation Data streaming system utilizing an asynchronous technique for retrieving data from a stream server
US6230200B1 (en) * 1997-09-08 2001-05-08 Emc Corporation Dynamic modeling for resource allocation in a file server
US7155735B1 (en) * 1999-10-08 2006-12-26 Vulcan Patents Llc System and method for the broadcast dissemination of time-ordered data
US6625750B1 (en) * 1999-11-16 2003-09-23 Emc Corporation Hardware and software failover services for a file server
US20020016842A1 (en) * 2000-07-21 2002-02-07 Takashi Eki Method for charging fee for use of network resources and method and system for allotting network resources
US20020013802A1 (en) * 2000-07-26 2002-01-31 Toshiaki Mori Resource allocation method and system for virtual computer system
US20020166117A1 (en) * 2000-09-12 2002-11-07 Abrams Peter C. Method system and apparatus for providing pay-per-use distributed computing resources
US20020156824A1 (en) * 2001-04-19 2002-10-24 International Business Machines Corporation Method and apparatus for allocating processor resources in a logically partitioned computer system
US20020161891A1 (en) * 2001-04-25 2002-10-31 Tatsuo Higuchi System and method for computer resource marketing
US20020178387A1 (en) * 2001-05-25 2002-11-28 John Theron System and method for monitoring and managing power use of networked information devices
US20020178206A1 (en) * 2001-05-25 2002-11-28 Siemens Medical Solutions Health Services Corporation System and method for monitoring computer application and resource utilization
US20030018870A1 (en) * 2001-07-17 2003-01-23 International Business Machines Corporation Appliance server with a drive partitioning scheme that accommodates application growth in size
US20040255048A1 (en) * 2001-08-01 2004-12-16 Etai Lev Ran Virtual file-sharing network
US20030028653A1 (en) * 2001-08-06 2003-02-06 New John C. Method and system for providing access to computer resources
US20030093528A1 (en) * 2001-11-13 2003-05-15 Jerome Rolia Method and system for enabling resource sharing in a communication network having a plurality of application environments
US7039784B1 (en) * 2001-12-20 2006-05-02 Info Value Computing Inc. Video distribution system using dynamic disk load balancing with variable sub-segmenting
US20030135580A1 (en) * 2001-12-28 2003-07-17 Camble Peter Thomas Method for using partitioning to provide capacity on demand in data libraries
US7322034B2 (en) * 2002-06-14 2008-01-22 Hewlett-Packard Development Company, L.P. Method and system for dynamically allocating computer system resources
US20040088412A1 (en) * 2002-07-24 2004-05-06 Ranjit John System and method for highly-scalable real-time and time-based data delivery using server clusters
US20050246705A1 (en) * 2002-07-25 2005-11-03 Sphera Corporation Method for dynamically allocating and managing resources in a computerized system having multiple consumers
US20050015343A1 (en) * 2002-09-11 2005-01-20 Norihiro Nagai License management device, license management method, and computer program
US20040111308A1 (en) * 2002-12-09 2004-06-10 Brighthaul Ltd. Dynamic resource allocation platform and method for time related resources
US20060294238A1 (en) * 2002-12-16 2006-12-28 Naik Vijay K Policy-based hierarchical management of shared resources in a grid environment
US7146496B2 (en) * 2003-01-23 2006-12-05 Hewlett-Packard Development Company, L.P. Methods and apparatus for managing temporary capacity in a computer system
US20040148511A1 (en) * 2003-01-23 2004-07-29 Circenis Edgar I. Codeword-based auditing of computer systems and methods therefor
US20040199632A1 (en) * 2003-03-21 2004-10-07 Romero Francisco J. Assembly and method for balancing processors in a partitioned server
US20040215748A1 (en) * 2003-04-28 2004-10-28 International Business Machines Corporation Method, system, and computer program product for on demand enablement of dormant computing resources
US20050268063A1 (en) * 2004-05-25 2005-12-01 International Business Machines Corporation Systems and methods for providing constrained optimization using adaptive regulatory control
US20060100962A1 (en) * 2004-10-23 2006-05-11 Wooldridge James L Permitting utilization of computer system resources in accordance with their licensing
US20060190615A1 (en) * 2005-01-21 2006-08-24 Panwar Shivendra S On demand peer-to-peer video streaming with multiple description coding

Cited By (51)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060156309A1 (en) * 2005-01-13 2006-07-13 Rhine Scott A Method for controlling resource utilization and computer system
US8108871B2 (en) * 2005-01-13 2012-01-31 Hewlett-Packard Development Company, L.P. Controlling computer resource utilization
US8825560B2 (en) 2007-11-08 2014-09-02 Genetic Finance (Barbados) Limited Distributed evolutionary algorithm for asset management and trading
US20090125370A1 (en) * 2007-11-08 2009-05-14 Genetic Finance Holdings Limited Distributed network for performing complex algorithms
US9466023B1 (en) 2007-11-08 2016-10-11 Sentient Technologies (Barbados) Limited Data mining technique with federated evolutionary coordination
US8918349B2 (en) 2007-11-08 2014-12-23 Genetic Finance (Barbados) Limited Distributed network for performing complex algorithms
US9734215B2 (en) 2008-11-07 2017-08-15 Sentient Technologies (Barbados) Limited Data mining technique with experience-layered gene pool
US9684875B1 (en) 2008-11-07 2017-06-20 Sentient Technologies (Barbados) Limited Data mining technique with experience-layered gene pool
US8909570B1 (en) 2008-11-07 2014-12-09 Genetic Finance (Barbados) Limited Data mining technique with experience-layered gene pool
US20100274736A1 (en) * 2009-04-28 2010-10-28 Genetic Finance Holdings Limited, AMS Trustees Limited Class-based distributed evolutionary algorithm for asset management and trading
US8768811B2 (en) 2009-04-28 2014-07-01 Genetic Finance (Barbados) Limited Class-based distributed evolutionary algorithm for asset management and trading
US10289523B2 (en) * 2010-07-12 2019-05-14 International Business Machines Corporation Generating an advanced function usage planning report
US20120011036A1 (en) * 2010-07-12 2012-01-12 International Business Machines Corporation Advanced function usage-based billing
US20120011514A1 (en) * 2010-07-12 2012-01-12 International Business Machines Corporation Generating an advanced function usage planning report
US20120011328A1 (en) * 2010-07-12 2012-01-12 International Business Machines Corporation Advanced function monitoring on a storage controller
US10169747B2 (en) 2010-07-12 2019-01-01 International Business Machines Corporation Advanced function usage detection
US8621080B2 (en) * 2011-03-07 2013-12-31 Gravitant, Inc. Accurately predicting capacity requirements for information technology resources in physical, virtual and hybrid cloud environments
US20120233328A1 (en) * 2011-03-07 2012-09-13 Gravitant, Inc Accurately predicting capacity requirements for information technology resources in physical, virtual and hybrid cloud environments
US8977581B1 (en) 2011-07-15 2015-03-10 Sentient Technologies (Barbados) Limited Data mining technique with diversity promotion
US9304895B1 (en) 2011-07-15 2016-04-05 Sentient Technologies (Barbados) Limited Evolutionary technique with n-pool evolution
US9367816B1 (en) 2011-07-15 2016-06-14 Sentient Technologies (Barbados) Limited Data mining technique with induced environmental alteration
US9710764B1 (en) 2011-07-15 2017-07-18 Sentient Technologies (Barbados) Limited Data mining technique with position labeling
US10025700B1 (en) 2012-07-18 2018-07-17 Sentient Technologies (Barbados) Limited Data mining technique with n-Pool evolution
US8725645B1 (en) * 2013-01-04 2014-05-13 Cetrus LLC Non-invasive metering system for software licenses
US11288579B2 (en) 2014-01-28 2022-03-29 Cognizant Technology Solutions U.S. Corporation Training and control system for evolving solutions to data-intensive problems using nested experience-layered individual pool
US10268953B1 (en) 2014-01-28 2019-04-23 Cognizant Technology Solutions U.S. Corporation Data mining technique with maintenance of ancestry counts
US11663492B2 (en) 2015-06-25 2023-05-30 Cognizant Technology Solutions Alife machine learning system and method
US11151147B1 (en) 2015-09-01 2021-10-19 Cognizant Technology Solutions U.S. Corporation Data mining management server
US10430429B2 (en) 2015-09-01 2019-10-01 Cognizant Technology Solutions U.S. Corporation Data mining management server
US11281978B2 (en) 2016-04-08 2022-03-22 Cognizant Technology Solutions U.S. Corporation Distributed rule-based probabilistic time-series classifier
US10956823B2 (en) 2016-04-08 2021-03-23 Cognizant Technology Solutions U.S. Corporation Distributed rule-based probabilistic time-series classifier
US11574202B1 (en) 2016-05-04 2023-02-07 Cognizant Technology Solutions U.S. Corporation Data mining technique with distributed novelty search
US11250327B2 (en) 2016-10-26 2022-02-15 Cognizant Technology Solutions U.S. Corporation Evolution of deep neural network structures
US11250328B2 (en) 2016-10-26 2022-02-15 Cognizant Technology Solutions U.S. Corporation Cooperative evolution of deep neural network structures
US11403532B2 (en) 2017-03-02 2022-08-02 Cognizant Technology Solutions U.S. Corporation Method and system for finding a solution to a provided problem by selecting a winner in evolutionary optimization of a genetic algorithm
US20180250554A1 (en) * 2017-03-03 2018-09-06 Sentient Technologies (Barbados) Limited Behavior Dominated Search in Evolutionary Search Systems
US10744372B2 (en) * 2017-03-03 2020-08-18 Cognizant Technology Solutions U.S. Corporation Behavior dominated search in evolutionary search systems
US11247100B2 (en) * 2017-03-03 2022-02-15 Cognizant Technology Solutions U.S. Corporation Behavior dominated search in evolutionary search systems
US11507844B2 (en) 2017-03-07 2022-11-22 Cognizant Technology Solutions U.S. Corporation Asynchronous evaluation strategy for evolution of deep neural networks
US11281977B2 (en) 2017-07-31 2022-03-22 Cognizant Technology Solutions U.S. Corporation Training and control system for evolving solutions to data-intensive problems using epigenetic enabled individuals
US11250314B2 (en) 2017-10-27 2022-02-15 Cognizant Technology Solutions U.S. Corporation Beyond shared hierarchies: deep multitask learning through soft layer ordering
US11003994B2 (en) 2017-12-13 2021-05-11 Cognizant Technology Solutions U.S. Corporation Evolutionary architectures for evolution of deep neural networks
US11182677B2 (en) 2017-12-13 2021-11-23 Cognizant Technology Solutions U.S. Corporation Evolving recurrent networks using genetic programming
US11030529B2 (en) 2017-12-13 2021-06-08 Cognizant Technology Solutions U.S. Corporation Evolution of architectures for multitask neural networks
US11527308B2 (en) 2018-02-06 2022-12-13 Cognizant Technology Solutions U.S. Corporation Enhanced optimization with composite objectives and novelty-diversity selection
US11574201B2 (en) 2018-02-06 2023-02-07 Cognizant Technology Solutions U.S. Corporation Enhancing evolutionary optimization in uncertain environments by allocating evaluations via multi-armed bandit algorithms
US11755979B2 (en) 2018-08-17 2023-09-12 Evolv Technology Solutions, Inc. Method and system for finding a solution to a provided problem using family tree based priors in Bayesian calculations in evolution based optimization
US11481639B2 (en) 2019-02-26 2022-10-25 Cognizant Technology Solutions U.S. Corporation Enhanced optimization with composite objectives and novelty pulsation
US11669716B2 (en) 2019-03-13 2023-06-06 Cognizant Technology Solutions U.S. Corp. System and method for implementing modular universal reparameterization for deep multi-task learning across diverse domains
US11783195B2 (en) 2019-03-27 2023-10-10 Cognizant Technology Solutions U.S. Corporation Process and system including an optimization engine with evolutionary surrogate-assisted prescriptions
US11775841B2 (en) 2020-06-15 2023-10-03 Cognizant Technology Solutions U.S. Corporation Process and system including explainable prescriptions through surrogate-assisted evolution

Also Published As

Publication number Publication date
TWI338233B (en) 2011-03-01
US20050010502A1 (en) 2005-01-13
US7627506B2 (en) 2009-12-01
TW200519626A (en) 2005-06-16

Similar Documents

Publication Publication Date Title
US7627506B2 (en) Method of providing metered capacity of temporary computer resources
CN1784659A (en) Apparatus and method for providing metered capacity of computer resources
US8074223B2 (en) Permanently activating resources based on previous temporary resource usage
US20060173730A1 (en) Adjusting resource activation based on a manufactured date of a computer
US7877754B2 (en) Methods, systems, and media to expand resources available to a logical partition
US8074225B2 (en) Assuring recovery of temporary resources in a logically partitioned computer system
US8458011B2 (en) Dynamic pricing of a resource
CA2915996C (en) Burst mode control
US20080103861A1 (en) Fair share scheduling for mixed clusters with multiple resources
US7574507B2 (en) System for determining unreturned standby resource usage
US20120158447A1 (en) Pricing batch computing jobs at data centers
US9218038B2 (en) Determining and optimizing energy consumption of computer systems
US11416782B2 (en) Dynamic modification of interruptibility settings for network-accessible resources
US20050138422A1 (en) System and method for metering the performance of a data processing system
CN111162921B (en) Multi-account cloud service usage package sharing method and device and related equipment
WO2004088507A2 (en) Apparatus and method for providing metered capacity of computer resources
US20150012398A1 (en) Credit optimization to minimize latency
CN109903030A (en) It is a kind of for the charging method of cloud host, cloud host and storage medium
US10230664B1 (en) Strategic resource allocation in a web-based computing system
US20060155555A1 (en) Utility computing method and apparatus
US20080306847A1 (en) Providing metered accounting of computer resources
CA2534201A1 (en) Apparatus and method for assuring recovery of temporary resources in a logically partitioned computer system
US8386391B1 (en) Resource-type weighting of use rights
US20140344001A1 (en) Market for resources based on reusable usage points and usage periods

Legal Events

Date Code Title Description
STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION