US007616583B1
`
`a2) United States Patent
`US 7,616,583 B1
`(0) Patent No.:
`Nov. 10, 2009
`(45) Date of Patent:
`Poweret al.
`
`(54)
`
`(75)
`
`METHOD AND PROGRAM PRODUCT FOR
`CONSOLIDATING COMPUTER HARDWARE
`RESOURCES
`
`(56)
`
`References Cited
`U.S. PATENT DOCUMENTS
`
`Inventors: Jonathan Power, Austin, TX (US);
`Kevin Galloway, Austin, TX (US);
`Terry Harrison, Austin, TX (US)
`
`4/1998 Strothmann.............. 7105/7
`5,745,880 A *
`8/1998 Fadetal. we. 705/400
`5,793,632 A *
`6/2001 Ruffin et al.
`6,249,769 Bl
`7/2005 Walshetal. oe. 709/200
`6,920,474 B2*
`7,A67,095 B2* 12/2008 Ouimet ........ eee 7105/7
`
`(73)
`
`Assignee:
`
`International Business Machines
`Corporation, Armonk, NY (US)
`
`* cited by examiner
`
`(*)
`
`Notice:
`
`Subject to any disclaimer, the term ofthis
`patent is extended or adjusted under 35
`USS.C. 154(b) by 1273 days.
`
`Primary Examiner—Brian D Nguyen
`(74) Attorney, Agent, or Firm—Arthur J. Samodovitz
`
`(57)
`
`ABSTRACT
`
`(21)
`
`Appl. No.: 10/888,881
`
`(22)
`
`Filed:
`
`Jul. 9, 2004
`
`(60)
`
`(51)
`
`(52)
`(58)
`
`Related U.S. Application Data
`
`Provisional application No. 60/489,406, filed on Jul.
`23, 2003.
`
`Int. Cl.
`
`(2006.01)
`GO6F 9/45
`US. C1.
`ic ececceceeseeteceteeeeeneeeee 370/252; 717/148
`Field of Classification Search.
`................. 370/252,
`370/253, 254, 255, 244; 709/203, 223, 224;
`717/148
`See application file for complete search history.
`
`A computer determinesa first plurality of servers which have
`a lease set to expire within a predeterminedperiod or current
`or projected peak utilization greater than a predetermined
`percentage of their capacity. The computer determinesa sec-
`ondplurality of servers which have sufficient lease term and
`excess capacity. The computer determines and records which
`servers of thefirst plurality to consolidate on servers of the
`second plurality based on sufficient capacity, match of appli-
`cation(s) and projected life span of the application(s) of the
`second plurality, and determines a schedule for retiring the
`servers of the first plurality with the applications having
`insufficient projected lifespan, and estimates cost savings for
`the consolidation.”
`
`14 Claims, 8 Drawing Sheets
`
`101
`RECEIVE SURVEY OF
`
`HARDWARE DEVICES
`
`
`
`
`
`RECEIVE FUTURE STATE CRITERIA
`107
`
`
`ESTIMATE COST
`AVINGS
`
`NO ESTIMATE
`
`CALCULATE AND RETURN COST
`
`SAVINGS ESTIMATE
`
`105
`
`RECEIVE SURVEY OF APPLICATIONS
`©
`
`
`
`DETERMINE REPLACEMENT
`OF APPLICATIONS
`
`7 t08
`RETURN FUTURE HARDWARESTATE
`
`109
`
`RETURN REVISED APPLICATION
`
`FUTURE STATE
`
`C 110
`CALCULATE COST AND TIME
`
`
`REQUIREMENTS FOR CONSOLIDATION
`
`
`
`APPLY TOLERANCES
`
`c12
`OUTPUT FUTURE STATES AND COST AND
`(END_)
`TIME ESTIMATES FOR CONSOLIDATION
`
`
`
`VMware, Inc.
`
`Exhibit1016
`
`Page 1
`
`VMware, Inc. Exhibit 1016 Page 1
`
`

`

`U.S. Patent
`
`Nov. 10, 2009
`
`Sheet 1 of 8
`
`US 7,616,583 B1
`
`RECEIVE SURVEY OF
`HARDWAREDEVICES
`
`ea
`
`s
`
`102
`
`RECEIVE CONSOLIDATION RATIOS
`
`
`ESTIMATE COST
`SAVINGS
`
`
`
`
`
`
`NO ESTIMATE
`
`CALCULATE AND RETURN COST
`
`SAVINGS ESTIMATE
`
`105
`
`RECEIVE SURVEY OF APPLICATIONS
`<>
`
`RETURN ERRORS
`
`103
`104
`
`
`
`RECEIVE FUTURESTATECRITERIA (END)
`
`106
`
`DETERMINE REPLACEMENT
`OF APPLICATIONS
`
`107
`
`108
`
`RETURN FUTURE HARDWARESTATE
`
`109
`
`RETURN REVISED APPLICATION
`FUTURE STATE
`
`CALCULATE COST AND TIME
`REQUIREMENTS FOR CONSOLIDATION
`
`110
`
`111
`
`APPLY TOLERANCES
`
`OUTPUT FUTURE STATES AND COST AND
`TIME ESTIMATES FOR CONSOLIDATION
`
`112
`
`FIG. 1
`
`VMware, Inc.
`
`Exhibit1016
`
`Page 2
`
`VMware, Inc. Exhibit 1016 Page 2
`
`

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`Nov. 10, 2009
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`Exhibit 1016
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`Page 3
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`VMware, Inc. Exhibit 1016 Page 3
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`

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`U.S. Patent
`
`Nov. 10, 2009
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`Exhibit 1016
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`Page 4
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`VMware, Inc. Exhibit 1016 Page 4
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`

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`U.S. Patent
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`Nov. 10, 2009
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`VMware, Inc.
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`Exhibit 1016
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`Page5
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`VMware, Inc. Exhibit 1016 Page 5
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`

`

`U.S. Patent
`
`Nov. 10, 2009
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`Sheet 5 of 8
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`VMware, Inc.
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`Exhibit 1016
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`Page6
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`VMware, Inc. Exhibit 1016 Page 6
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`
`

`

`U.S. Patent
`
`Nov. 10, 2009
`
`Sheet 6 of 8
`
`US 7,616,583 B1
`
`601
`
`SORT HARDWAREDEVICES
`IDENTIFIED IN SURVEY
`
`-
`
`a
`
`602
`
`IDENTIFY NEXT SOURCE CANDIDATE
`
`
`
`APPLICATION(S) NEAR END OFLIFE
`
`SPAN ON IDENTIFIED CANDIDATE
` 604
`
`ADD SOURCE TO RETIREE LIST
`
`
`
`ADD TO MATCH
`LIST 2
`
`YES
`
`
`RETIREE LIST
`Lo
`
`NO.[RETURNFUTURESTATE
`MORE SOURCE CANDIDATES?
`RETURN FUTURE STATE
`
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`VMware, Inc.
`
`Exhibit1016
`
`Page7
`
`VMware, Inc. Exhibit 1016 Page 7
`
`

`

`U.S. Patent
`
`Nov. 10, 2009
`
`Sheet 7 of 8
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`US 7,616,583 B1
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`VMware, Inc.
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`Exhibit 1016
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`Page 8
`
`VMware, Inc. Exhibit 1016 Page 8
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`

`

`U.S. Patent
`
`Nov. 10, 2009
`
`Sheet 8 of 8
`
`US 7,616,583 B1
`
`COST AND TIME ESTIMATE
`
`FOR CONSOLIDATION
`
`Consolidation
`Estimated Cost
`Estimated Time
`
`Task
`Requirement
`
`Purchase New H/W
`
`Install New HAW
`
`Test New H/W
`
`Purchase New Apps
`
`Install New Apps
`
`Test New Apps
`
`Migrate Apps
`
`System Test
`
`Deployment
`
`TOTALS
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`Exhibit1016
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`Page9Q
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`VMware, Inc. Exhibit 1016 Page 9
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`

`

`US 7,616,583 B1
`
`1
`METHOD AND PROGRAM PRODUCT FOR
`CONSOLIDATING COMPUTER HARDWARE
`RESOURCES
`
`REFERENCE TO RELATED APPLICATIONS
`
`This application claims the benefit of U.S. Provisional
`Application Ser. No. 60/489,406, filed by Power,et al., on Jul.
`23, 2003. This application also incorporates by specitic ref-
`erence (p. 22, para. [0057]) all embodiments of the method
`described in paragraphs [0037] to [0205] and FIGS. 1-19 of
`US. patent application Ser. No. 10/807,623, entitled
`“Method and Program Product for Costing and Planning the
`Re-Hosting of Computer-Based Applications,’
`filed by
`Power, et al., with a filing date of Mar. 24, 2003.
`
`15
`
`BACKGROUND OF THE INVENTION
`
`1. Technical Field of the Invention
`
`The invention relates generally to the field of methods for
`consolidating computer hardware devices on which a plural-
`ity of computer-based applications are stored and/or oper-
`ated. The invention relates more specifically to methods for
`determining a future state for hardware resources and their
`applications and for estimating the cost and time require-
`ments for consolidating multiple hardware devices into fewer
`hardware devices.
`2. Description of Related Art
`The use of computer systems and applications greatly sim-
`plifies the storage and processing of data. Computer systems
`and applications enable businesses to reach certain econo-
`miesofscale, by streamliningthe cost, time andpracticalities
`of handling large volumes of data. As a business grows,
`however, the use of specialized systems and applications
`among its separate units can cause the overall information
`technology (IT) devices of the business to become frag-
`mented. The major result of fragmentation is the underuti-
`lization of hardware, such that each server or other hardware
`device is operated well below its capacity. Fragmentation also
`leads to otherinefficiencies, such as duplicative licensing and
`installation of operating systems and applications; excessive
`use of electrical power; excessive staffing; and inefficient
`utilization and maintenance of other devices. These wastes
`are often prolonged by the tendency of each business unit to
`become entrenchedin a particular operating system, group of
`applications, or computer hardware.
`Advances in computer hardware have enabled businesses
`to combatcertain inefficiencies. For example, new technolo-
`gies allow for many images of an application or operating
`system to be operated on a single CPU. Other technologies
`allow for single hardware devices to operate as multiple vir-
`tual machines. Nonetheless, the costs of change often exceed
`simple purchase or licensing fees. By the time a significant
`advancementis made, each unit of a business may be mired
`within its use of antiquated technologies. Applications may
`need to be replaced or migrated to a different hardware envi-
`ronment, and then configured to interact with particular oper-
`ating systemsor other applications. This results in downtime
`for hardware devices and ramp-up periods for users. Hence,
`the cost-benefit ratio of changing hardware or other IT
`resources often forces a business to lose moneyby living with
`inefficiencies for an extended period oftime.
`If a business continues to grow, a point typically arrives
`whenthe cost of continuing inefficiencies outweighs the cost
`of consolidating or reconstituting a business’ IT resources. A
`business must be able to determine whenit reaches this con-
`
`dition, so that it need not waste money unnecessarily. While
`
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`35
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`2
`methods for updating and consolidating applicationsor hard-
`ware have grown, businesses have been unableto project the
`cost or time requirements for either solution within useful
`tolerances. Thus, businesses are prone to waste financial
`resources by significantly undershooting or overshooting the
`point when consolidation and updating becomesa cost-effec-
`tive solution. Additionally, a business undergoing consolida-
`tion and updating often suffers from an inability to plan
`precisely for the interruption ofits operations. This addsto the
`cost of consolidation and updating, forcing some businesses
`to undergo migration of applications either much sooner, or
`muchlater, than it becomescost-effective.
`U.S. Pat. No. 6,249,769, to Ruffin, et al., discloses and
`claims a method for matching the IT infrastructure needs of a
`business with a set of IT solutions, and generating a proposal
`for the solution that would most help the business. Data
`relating to the IT objectives of a business are collected via an
`interactive process and are sequentially analyzed using mod-
`eling tools. The IT infrastructure is partitioned into “islands”
`of closely-related elements. Each island is assigned a score
`that reflects the value of enhancing its elements, and the
`islands are ranked according to their scores. A solution ser-
`vice or product is then chosen for each island from a database
`of available solutions. A proposal, or “Business Solutions
`Assessment,” is then generated for the enterprise by the pro-
`vider.
`
`While providing a valuable solution to IT fragmentation,
`the Ruffin invention has some limitations. First, the IT solu-
`tion is selected from a database of pre-defined solutions. It is
`not customized to each individual enterprise. The patent
`states thatits “process is fraught with a great degree of impre-
`cision”andthat a “customer engagementmayresult in failure
`for a variety of reasons including .
`.
`. applicability of [the
`provider’s] solution portfolio ...” (col. 6, lines 45-49). Any
`customization of a solution must be identified by the custom-
`er’s technical staff, or the customer must engagethe provid-
`er’s staff to develop a customized solution (col. 6, lines
`28-42). This adds time andcostto a projectfor the enterprise
`whose IT devices are being consolidated. An automated
`means for providing customized solutions would be more
`advantageous.
`Additionally, while the Ruffin invention provides a general
`cost estimate for migrating applications during a server con-
`solidation process, the cost estimate has a broad margin of
`error. The reason for this is that few factors are used to adjust
`cost, and these factors are applied to a migration as a whole.
`Factors affecting migration cost rarely affect every task dur-
`ing the migration of an application from one platform to
`another. For instance, the language factor disclosed in Ruffin
`(col. 21, line 38) mayaffect actual migration and sometesting
`functions after migration, but it will not affect baselining,
`system building, data import, or data export tasks. Hence,
`adjusting the entire migration process by the language factor
`will cause the estimated cost to be significantly higher than
`the real cost. The more factors that are applied, the more the
`overestimation compounds. Migrations must be broken down
`into individual tasks to which factors are applied, in order to
`obtain a cost estimate that prevents overshooting the point
`where consolidation becomescost-effective.
`
`Finally, while Ruffin discloses a generalized method of
`cost estimation,it discloses no meansfor estimating the time
`required for a consolidation process. The time required is an
`integral portion of any solution, because downtimeandser-
`vice interruptions result in costs that only the customer can
`truly assess. It is imperative that the customer be able to
`prepare for a consolidation process that is started and ended
`within a precise timeframe. Ruffin again admits to imprecise
`VMware, Inc.
`Exhibit 1016
`Page 10
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`VMware, Inc. Exhibit 1016 Page 10
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`US 7,616,583 B1
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`3
`implementation ofa server consolidation process, stating that
`a “customer engagement mayresult in failure [due to] delays
`and misstarts in the project planning and implementation
`process.”(col. 6, line 45-50). This may be remedied with an
`accurate estimate ofthe time requiredfor the IT consolidation
`process.
`As a result, there exists a great needin the art for a method
`for determining a customized future state for an enterprise’s
`IT resources, and for accurately projecting the costs for
`updating and consolidating a plurality of applications from
`multiple server computers or other computer-based environ-
`ments onto fewer server computers or other computer-based
`environments. The method mustprovide precise estimates for
`costs and should also accurately estimate time requirements
`for consolidation. Despite its production of customized solu-
`tions, the method must be automated andreplicable, to ensure
`that it provides more consistently valuable assessments than
`non-automated, ad hoc plans and estimating methods.
`
`SUMMARYOF THE INVENTION
`
`The current invention provides a computer-implemented
`methodfor costing and planning the consolidation ofmultiple
`source server computers or other source computer hardware
`devices to fewer target server computersor other target hard-
`ware devices. The method provides steps for determining a
`customized future state for IT resources, and for estimating
`the costs and time requirements for implementing the cus-
`tomized solution. This includes, among the other functions
`described herein, estimating the costs and time requirements
`for replacing or relocating one or more computer-basedappli-
`cations during the consolidation process and for replacing,
`installing and configuring any new hardware devices. The
`invented method addresses the foregoing challenges and pro-
`vides further advantages, by providing an automated method
`that may be implemented in a consistent manner with pre-
`dictable and accurate outcomes.
`
`The method comprises the steps of receiving identifica-
`tions and attributes of a plurality of hardware devices; receiv-
`ing identifications of a plurality of applications operated on
`the hardware devices; receiving at least one futurestate cri-
`terion; and determining a customized future hardwarestate.
`The future hardware state comprises a future IT configura-
`tion, wherein theattributesofall hardware devices meet every
`future state criterion, andall of the applications are replaced
`or operated on hardware devices meeting every future state
`criterion.
`
`The method mayalso comprise steps ofreceiving attributes
`of the applications; comparingthe attributes of each applica-
`tion with at least one replacementcriterion; and determining
`a future application state, wherein applications not meeting
`any replacementcriterion are operated on hardware devices
`meeting every future state criterion, each application meeting
`a replacementcriterion is retired, and a new or updated ver-
`sion of each retired application is operated on a hardware
`device meeting every future state criterion. The invented
`method may also comprise outputting the future hardware
`state, future application state, or both.
`Thestep of determining a customized future hardwarestate
`may be accomplished by sorting the hardware devices into
`source candidates (hardware devices not meeting every future
`state criterion) and target candidates (hardware devices meet-
`ing every future state criterion); comparing attributes of each
`source candidate with attributes of at least one target candi-
`date; comparing usage on each source candidate with capaci-
`ties of at least one target candidate; for each source candidate,
`determining a best target candidate whose attributes and
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`capacities best match the attributes and usage of the source
`candidate;
`and determining source
`candidates whose
`attributes do not match attributes of any target candidate. The
`customized future hardware state then comprises the target
`candidates and at least one new hardware device for operating
`applications on source candidates whoseattributes do not
`matchattributes ofany target candidate. The attributes ofeach
`new hardware device meet every future state criterion.
`The steps for determining a future hardware state may also
`comprise receiving a life span of each application, and deter-
`mining whetherall applications on a source candidate have a
`life span shorter than a pre-defined life span. The future
`hardwarestate further comprises, then, source candidates,all
`of whose applications have a life span shorter than the pre-
`defined life span. Alternatively, all applications having a life
`span shorter than a pre-defined life span may be migrated onto
`at least one proxy hardware device, and the future hardware
`state further comprises each proxy hardware device.
`The invented method mayalso comprise estimating at least
`one cost of implementing the future hardware state. Estimat-
`ing a cost may beachieved by receiving identifications of
`respective migration tasks; correlating base costs to respec-
`tive ones of said migration tasks; receiving identifications of
`migration attributes that affect migration cost; correlating
`cost factors to respective ones of said migration tasks, each of
`the cost factors indicating an amount by which a migration
`attribute affects the base cost of a migration task; and esti-
`mating a cost for each migration task, by applying the cost
`factors for each migration task to the base cost of the migra-
`tion task. A total cost for implementing the future hardware
`state may be estimated by summingthe estimatedcosts of all
`migration tasks.
`Thestep ofestimating at least one cost of implementing the
`future hardware state may also comprise correlating base
`time requirements to respective ones of said migration tasks;
`correlating time factors to respective ones of said migration
`tasks, each time factor indicating an amount by which a
`migration attribute changes the base time requirement for a
`migration task; and estimating a time requirement for each
`migration task, by applyingall time factors for the migration
`task to the base time requirement for the migration task. A
`total time requirement for implementing the future hardware
`state may be estimated by summing the estimated time
`requirements of all migration tasks.
`The invented method may also comprise calculating a cost
`savings for consolidating the hardware devices. The invented
`method mayalso comprise outputtingat least one cost chosen
`from a group consisting of the costs of each migration task,
`the time requirements of each migration task, the total cost
`and the total time requirement.
`Individual aspects or functionsofthe invented method may
`be embodied in computer-readable program products. Hence
`the current invention is also directed to computer-readable
`program code means for implementing and executing the
`steps of the methods disclosed, in a manner that will be
`readily knownto those skilled in theart.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 is a flow diagram illustrating steps of a method,
`wherein future states and cost and time estimates are returned
`for consolidating multiple source hardware devices to fewer
`target hardware devices, in accordance with the current inven-
`tion.
`
`FIG.2 is a table illustrating one example embodimentof a
`hardware survey, in accordance with the present invention.
`VMware, Inc.
`Exhibit1016
`Page 11
`
`VMware, Inc. Exhibit 1016 Page 11
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`

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`US 7,616,583 B1
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`5
`FIG.3 is a table illustrating a second example embodiment
`of a hardware survey, in accordance with the present inven-
`tion.
`
`FIG.4 is a table illustrating one example embodimentfor
`representing average cost by hardware category, in accor-
`dance with the present invention.
`FIG. 5 isa table illustrating one example embodimentof an
`application survey, in accordance with the present invention.
`FIG.6 is a flow diagram illustrating one embodimentof a
`method for determining a future hardware state, in accor-
`dance with the present invention.
`FIG.7 is a table illustrating an embodimentfor displaying
`or printing a future hardware state, in accordance with the
`present invention.
`FIG.8 is a table illustrating an example embodimentfor
`returning a cost andtime requirementestimate, in accordance
`with the present invention.
`
`DETAILED DESCRIPTION OF THE INVENTION
`
`Referring now to the drawings, the inventionis directed to
`a computer-implemented method for costing and planning
`the consolidation of computer hardware devices. The indi-
`vidual steps of the method are executed by at least one com-
`puter software program embodied on a computer-readable
`storage media 95 such as portable magnetic disk or semicon-
`ductor memory, or magnetic disk or semiconductor memory
`internal to a computer, without regard to the operating system
`of the computeror the language of the software programs. It
`will be appreciated by those skilledin theart that somesteps
`of the method may be performed in series, and some in
`parallel or in series. Additionally, the order ofthe steps may in
`someinstances be changed, without departing from the scope
`or advantages of by the current invention. The orderof steps
`disclosed herein is given for ease of explanation.
`FIG. 1 is a flow diagram illustrating steps of the invented
`method. In accordance with step 101, a survey of hardware
`devices is received. The hardware survey identifies the hard-
`ware devices that are to be consolidated. Hardware devices
`
`mayinclude, for example, server computer, mainframe com-
`puter, or other hardware device that is susceptible of operat-
`ing multiple applications for the benefit ofmultiple users. The
`identification of each hardware device may comprise one or
`more identifying indicia, such as a user-defined number,
`nameor character string that is assigned to each hardware
`device. The hardware survey also contains the manufacturer/
`vendor model nameandserial number, if any, of each hard-
`ware device identified in the hardware survey. The hardware
`survey also includesthe IP address of each hardware device,
`if any.
`The survey of hardware devices also includes the physical
`and logical capacities of each hardware device. Physical
`capacities may comprise, for example,
`total internal and
`external memory in each hardware device and disk or drive
`space availability and usage in each hardware device. Logical
`capacities may comprise, for example, the total and available
`numberof operating system imagesor partitions that may be
`operated on a device.
`The survey of hardware devices also includes functional
`attributes of each hardware device identified in the survey.
`Hardware functional attributes may include the primary func-
`tion of each hardware device, such as web access, online
`transaction processing, application utilization, database stor-
`age and operation,file and print, systems management,infra-
`structure or other functions. Where hardware devices in an
`enterprise are arranged in uniform layers among functional
`categories, the functional attributes of a hardware device may
`
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`be represented as two or more functional characteristics, such
`as web layerfor online services; application layer for intranet
`services; database layer for peoplesoft; or the like.
`The survey of hardware devices also includes technical
`attributes of each hardware device identified in the survey.
`Hardware technical attributes include internal components
`and capacities, such as the quantity and speedsofthe central
`processing units (CPUs) used to control each hardware device
`and the amount of random access memory (RAM) in each
`hardware device. Hardware technical attributes also include
`operating attributes of each hardware device, such as the
`types and versions of operating systems and databases used
`on each hardware device; peak and average utilization per-
`centages for each hardware device; and the network load
`among the hardware devices as a whole, or by functional
`category (described above). The hardware technicalattributes
`also include the organizational or logical affinity of each
`hardware device for applications having certain characteris-
`tics, such as particular high-level languages, or functions,
`such as calculation, production, development, or quality
`assurance. The hardware technical attributes also include
`
`transaction processing rates for each hardware device, suchas
`transactions per minute-C (tpmC)or price-per-tpmC.
`The survey of hardware devices also includes financial
`attributes, such as a description of whether the hardware
`device is purchased, leased, financed, or other indications of
`ownership. Where a hardwaredevice is leased or financed, the
`origination and expiration dates of the lease or finance agree-
`mentare received. The financial attributes also include aver-
`age costs per period for operating each hardware device on a
`quarterly, semi-annual, or yearly basis over a pre-defined or
`user-defined number of prior time periods. Average costs
`period represent all cost variables for operating hardware
`devices over a time period, including power consumption
`costs; costs from hardware leasing or financing contracts;
`costs from operating system licensing and updating; costs
`from updating components, such as processor cards, memory
`and the like; media costs for backing up, archiving or other-
`wise transferring files or programs; cost of peripherals; main-
`tenance and support costs; costs from network management;
`cost of operationsstaff; physical space costs, if any; and other
`costs associated with operating the physical hardware devices
`identified above.
`
`The average costs per period are preferably grouped into
`categories, which may be defined by ranges of hardware
`attributes. For instance, average costs per period could be
`grouped accordingto ranges in the size, capacity or number of
`processors of various hardware devices. As shownin FIG.4,
`separate average quarterly costs experienced overthe past six
`quarters may be received for server computers having one to
`twoprocessors; for server computers having three to six pro-
`cessors; and for server computers having more than six pro-
`cessors. In another example, average semi-annual costs over
`the past two years may be received for all infrastructure
`hardware; forall database hardware; for all web hardware; for
`all web payer hardware used for intranet services; and for
`other functional categories.
`The average costs received for various categories are
`accompaniedby a percentage, fraction or proportion indicat-
`ing the amountof suchcosts thatare fixed, 1.e., the costs that
`do notrise with the addition of additional units of hardware
`devices in the relevant category. Alternatively, an average
`fixed cost percentage maybe received for hardware devices as
`a whole, irrespective of category. Percentages of fixed costs
`mayalternatively be received both by category of hardware
`and overall.
`
`VMware, Inc.
`
`Exhibit1016
`
`Page 12
`
`VMware, Inc. Exhibit 1016 Page 12
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`US 7,616,583 B1
`
`7
`The hardwarefinancialattributes may also include current
`book value of each hardware device and depreciation rate by
`term, such as monthly depreciation or thelike.
`The survey of hardware devicesalso includesthe position-
`ing of each hardware device within an enterprise. Enterprise
`positioning may include physical location of each hardware
`device within the enterprise’s facilities or business units and
`the existence and/or description of any service level agree-
`ment (SLA) for users of various business units to use a par-
`ticular hardware device. The survey of hardware devices may
`also include the installation date ofeach hardware device. The
`survey of hardware devices may also include the backup
`methods used for each hardware device.
`
`The hardwaredevice survey maytake the form ofa table, or
`series of tables, as represented in FIGS. 2 and 3.
`A user may elect to calculate a cost savings that will be
`realized from consolidating the hardware devices, according
`to steps 102-104. If a cost savings estimate is to be returned,
`then at least one consolidation ratio is received, in accordance
`with step 102. A physical consolidation ratio comparing the
`numberof current hardware devices to the target number of
`hardware devices after consolidation is received. A logical
`consolidation ratio comparing the numberof current operat-
`ing system (OS) images operating on current hardware
`devices to the target number of OS imagesto be operated on
`target hardware devices after consolidation is also received.
`The target consolidation ratios may also include separate
`ratios for user-defined categories of physical hardware
`devices and OS images. For example, the overall physical
`consolidation ratio may be received along with separate ratios
`for physical consolidation of database hardware devices;
`application hardware devices; web hardware devices; file and
`print hardware devices; systems management hardware
`devices; and infrastructure hardware devices. Likewise, the
`overall logical consolidation ratio may be received along with
`separate ratios for consolidating OS images operating on
`database hardware devices; application hardware devices;
`web hardware devices; file and print hardware devices; sys-
`tems managementhardware devices; and infrastructure hard-
`ware devices. Any target consolidation ratio may be received
`as arange, which extends from the most conservative accept-
`able consolidation ratio to the most aggressive acceptable
`consolidation ratio. For example, a target consolidation ratio
`for web hardware devices maybe receivedin the form 4:1-6:1
`or 4-6:1, wherein the consolidation ratio represents a target
`consolidation from between four and six hardware devices to
`one hardware device.
`
`In accordance with step 103, errors may be returnedforthe
`target consolidation ratios. Errors may indicate that the target
`consolidation ratios are unrealistic, given limitations in tech-
`nology, such as memory capacity, numbersofpossible termi-
`nals or users, or other limitations of computer hardware
`devices. If errors are returned, then new target consolidation
`ratios are received and examinedfor errors.
`
`Once the target consolidation ratios are received without
`errors being returned,