(12) United States Patent
`Loomans et al.
`
`(10) Patent N0.:
`(45) Date of Patent:
`
`US 7,873,503 B2
`Jan. 18, 2011
`
`USOO7873503B2
`
`(54) METHOD, SYSTEM, AND PRODUCT FOR
`PERFORMING SUB-CONFIGURATION OF
`ENTITIES
`
`(75) Inventors: Jeffrey William Loomans’ San
`Francisco CA
`Lisa Ann Laane
`’
`,
`’
`’
`CuPemnos CA (Us)
`
`(73) Assigneei Siebel Systems, Inc-s San Mateo, CA
`(Us)
`
`( * ) Notice:
`
`Subject to any disclaimer, the term ofthis
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 1320 days.
`
`_
`(21) Appl' NO" 10/299’215
`(22) Filed_
`NOV 18 2002
`
`.
`
`.
`
`,
`
`3/1996 Sonty et a1. ............... .. 710/104
`5,499,357 A *
`5/1996 Lynch et a1. . . . . . .
`. . . .. 703/13
`5,515,524 A *
`9/1998 Bentley et al.
`.... .. 703/4
`5,815,415 A *
`5,970,242 A * 10/1999 O’Connor et a1. .
`717/100
`6,223,342 B1: 4/2001 George ........... ..
`717/116
`6,237,139 B1
`5/2001 Hotta et a1. ......... ..
`717/126
`6,256,773 B1* 7/2001 Bowman-Amuah ..
`717/121
`6,289,382 B1 *
`9/2001 Bowman-Amuah ..
`709/226
`
`6,711,688 B1* 3/2004 H b h
`
`t l.
`
`. . . . .
`
`. . . . .. 726/7
`
`715/765
`4/2004
`6,717,595 B1 *
`463/43
`7/2004 Luciano et al.
`6,758,757 B2 *
`.... .. 713/1
`6,854,052 B2* 2/2005 Beeston et a1.
`6,996,711 B2 *
`2/2006 Patterson et a1. .......... .. 713/156
`_
`* _
`Clted by exammer
`Primary ExamineriPaul L Rodriguez
`Assistant ExamineriEunhee Kim
`(74) Attorney, Agent, or Firm4Campbell Stephenson LLP
`
`(65)
`
`Prior Publication Data
`
`(57)
`
`ABSTRACT
`
`Us 2010/0204970 A1
`
`Aug 12, 2010
`
`Related US. Application Data
`(63) Continuation of application No. 09/967,852, ?led on
`Se 28 2001 now abandoned
`p'
`’
`’
`'
`(51) Int Cl
`(2006 01)
`G081? 27/50
`(200601)
`G0 6 F 9/44
`703/13_ 717/116
`'
`52 U 5 Cl
`’
`(
`)
`_'
`'
`' """ "_' """ "_ """"""""""" "
`(58) Field of Classi?cation Search ........ ..: ...... .. 703/13,
`_
`_
`703/22’ 717/121’ 116
`See apphcanon ?le for Complete SearCh hlswry'
`References Cited
`
`(56)
`
`U.S. PATENT DOCUMENTS
`
`Techniques to performing sub-con?guration of components
`of an entity. In one method, the entity is con?gured via a
`parent model and each sub-con?gurable component is con
`?-gured Vla?one Ofa Humbler Of iub—nnkodelsdnmany a seleciq
`tron to con gure'a partrcu ar su -co gura e component 0
`the entity is received, and a sub-model for the selected com
`ponent is identi?ed. One or more values for one or more
`features of the selected component are received (e.g., from the
`parent model or via the sub-model) and form a con?guration
`for the component, Which is then validated based on the
`associated sub-model and the received values. Con?guration
`of the entity is also validated based on the parth model and
`the validated con?guration forthe selected component. Feed
`backs may be provided for each con?guration of the parent
`model and sub-models. The data for the parent model and
`sub-models may be localized or globalized.
`
`5,247,683 A *
`
`9/1993 Holmes et a1. ............ .. 709/221
`
`29 Claims, 11 Drawing Sheets
`
`Identify sub»model map
`for selected sub-model
`
`,514
`Receive seleotlon tori
`of N children sub-models
`in sub-model mapping
`set (e.g., "Storage")
`
`Receive selection for a
`sub-model map value from
`set at options (e.g., "A560
`
`:
`
`(522
`Receive selection tor a
`feature mapping set
`(e.g.. "Power Rating")
`c526
`Receive selection for a
`feature map value
`(e.g., >35“ = '40A")
`
`t
`
`|
`
`i," a.
`
`532 _________e\___________ u. e. Q
`
`' nether
`mapped feature
`Cl 117
`
`Run sub-model in context
`at all selected feature map
`“was Kain Mar Knit)
`
`Return to parent model and
`map values from sub-model
`to parent model
`____I
`
`Page 1 of 24
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`
`US. Patent
`
`Jan. 18, 2011
`
`Sheet 1 0111
`
`US 7,873,503 B2
`
`A
`f Chasis
`
`700
`
`,/
`Computer System
`
`B
`Processor
`
`C Drive Bay 1
`D Drive Bay 2
`E Drive Bay 3
`
`F Storage
`
`FIG. 1
`
`G
`Power
`Supply
`
`F
`E
`D
`C
`B
`A
`Processor Drive Bay 1 Drive Bay 2 Drive Bay 3 Storage
`Chasis
`P4 1.0GHz
`Floppy
`32xCD
`6.4 GB
`None
`short
`medium P4 1.0GHz
`Floppy
`32xCD
`6.4 GB
`None
`tail
`P4 1.0GHZ
`Floppy
`32xCD
`6.4 GB
`None
`short
`P4 1.3GHz
`Floppy
`32xCD
`6.4 GB
`None
`
`250
`V
`
`G
`Supply
`20 A
`20 A
`20 A
`20 A
`
`FIG. 23
`
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`Jan. 18, 2011
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`Sheet 2 0f 11
`
`US 7,873,503 B2
`
`A
`Chasis
`short
`medium
`tail
`903
`
`C
`Drive Bay 1
`Disk Drive
`CD-Drive
`Hard Disk
`None
`\
`210o
`
`B
`Processor
`P4 1.0GHz
`P4 1.3GHz
`P4 1.5(3Hz
`AMD 1.0GHz
`AMD 1-5GHZ
`C l 800M
`9
`HZ 210o
`Cel 1.0GHz
`
`D
`Drive Bay 2
`Disk Drive
`CD-Drive
`Hard Disk
`None
`‘\
`210d
`
`E
`Drive Bay 3
`Disk Drive
`CD-Drive
`Hard Disk
`None
`\
`2109
`
`F
`Storage
`ABC
`XYZ
`\ 210r
`
`G
`Supply
`20 A
`40 A
`
`60 A
`
`210
`80 A
`100 A f 9
`
`Disk
`Drive
`Floppy
`Zip disk
`Superdisk
`\
`210n
`
`CD-
`Drive
`32xCD
`DVD
`CD-R/W
`\
`210i
`
`Hard
`Disk
`6.4 GB HD
`12 GB HD
`18 GB HD
`24 GB HD
`2‘10]-
`
`FIG. 2A
`
`ABC
`Storage
`5 GB
`10 GB
`20 GB
`40 GB
`80 GB
`\‘
`210k
`
`XYZ
`Storage
`18 GB
`28 GB
`56 GB
`\
`2101
`
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`Jan. 18, 2011
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`She et3 0f11
`
`US 7,873,503 B2
`
`300
`“1
`
`Sub-Model
`Mapping Set
`1
`I310
`2
`:35
`_
`
`for
`Sub-Model Map 1
`r———L—'__\
`M 330m
`Sub-Model
`Sub-Model 2 330!)
`Sub-Model 1
`
`l
`
`Sub-Model
`(SM) Map 1
`
`'
`N
`
`320n
`32Gb
`320a!
`
`FIG. 3A
`
`Sub-Model 1
`
`33‘”
`
`Feature 1
`value 1 ~344a
`value 2 ~344b
`
`m Feature L
`value 1
`value 2
`
`value K1 ~344k
`5312
`
`value KL
`
`FIG. 3B
`
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`Jan. 18, 2011
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`Sheet 4 0f 11
`
`US 7,873,503 B2
`
`410
`
`r4100
`
`Feature Table
`for "Chassis"
`Short
`,412
`Medium
`Tail
`
`Sub-Model
`Mapping Set
`Chasis
`Processor
`Drive Bay 1
`Drive Bay 2
`Drive Bay 3
`Storage w
`Supply
`Sub-Model Map
`for "Storage"
`ABC
`f420
`XYZ
`
`430a
`
`Sub-Model for "ABC"
`440a\v
`440bx
`Storage Amount
`Power Rating
`20 GB ~444a
`40 A
`40 GB ~444b
`60 A
`80 GB ~444c
`80 A
`$42
`
`FIG. 4
`
`Sub-Model for "XYZ" 430D
`
`Storage Amount
`28 GB
`56 GB
`
`Power Rating
`20 A
`60 A
`
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`Jan. 18, 2011
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`Sheet 5 0f 11
`
`US 7,873,503 B2
`
`C
`
`Start
`
`)
`
`500 r/
`
`7V Run parent model in context I512
`
`Receive se|ection for 1
`of current set of all features
`of N Chndren submodels
`1 m
`in sub-model mapping
`v \N 4/ set (e.g., "Storage")
`Identify sub-model map
`[516
`(513
`.
`.
`for selected sub-model
`Receive selectlon for a
`
`1 ... \M _ _ _ _ f_\~ sub-model map value from
`
`set of options (e.g., "ABC")
`
`[522
`Receive selection for a
`feature mapping set
`(e.g., "Power Rating")
`
`YES
`
`Another
`mapped feature
`selected?
`NO
`
`Run sub-model in context
`of all selected feature map
`values (Xvalt' Xva12’
`XvalL)
`
`\ 01 00 M
`
`L..._..._ _ ~ _ _ _ _ _ _ __
`
`V
`Return to parent model and
`map values from sub-model
`to parent model
`l
`
`,542
`
`FIG. 5
`
`_ _ _ _ _ _ _ _ _ _ __
`
`V
`Identify sub-model for
`selected sub-model map value
`
`>1 "'
`v
`Identify feature map for
`selected feature mapping set
`
`L
`
`:
`[520 ' l
`|
`1
`4'4'\-'
`I
`{524 :
`|
`
`r525
`Recelve selectlon for a
`‘1 m \K 4* feature map value
`Identify selected
`,528
`(8'9" Xva" : 40A)
`feature map value
`
`.
`
`.
`
`r
`
`_________R___________ 01 A Q
`
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`Sheet 6 0f 11
`
`US 7,873,503 B2
`
`( Start
`l
`Run parent model
`
`)
`
`K500
`
`,612
`
`614
`
`Sub-model
`selected?
`
`616
`
`Selected
`sub-model previously
`con?gured?
`
`YES
`
`Pull in data for the selected
`sub-model and set up
`selections for features in
`the selected sub—model
`
`f618
`
`lk
`
`Validate each child
`sub-model of parent model
`l
`Validate parent model
`
`( Start
`FIG. 6
`
`I620
`
`,622
`
`>
`
`Page 7 of 24
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`Jan. 18, 2011
`
`Sheet 7 0f 11
`
`US 7,873,503 B2
`
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`Page 8 of 24
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`US. Patent
`
`Jan. 18, 2011
`
`Sheet 8 0f 11
`
`US 7,873,503 B2
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`Page 9 of 24
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`US. Patent
`
`Jan. 18, 2011
`
`Sheet 9 0f 11
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`US 7,873,503 B2
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`Page 10 of 24
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`US. Patent
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`Jan. 18, 2011
`
`Sheet 10 0f 11
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`US 7,873,503 B2
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`Page 11 of 24
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`Jan. 18, 2011
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`Sheet 11 of 11
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`US 7,873,503 B2
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`Page 12 of 24
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`
`US 7,873,503 B2
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`1
`METHOD, SYSTEM, AND PRODUCT FOR
`PERFORMING SUB-CONFIGURATION OF
`ENTITIES
`
`BACKGROUND OF THE INVENTION
`
`The present invention relates generally to computer pro
`cessing, and more particularly to techniques for performing
`sub-con?guration of complicated entities.
`For many applications, it is necessary to de?ne and repre
`sent complicated structures or entities. A complicated entity
`may include multiple components, each of which may be
`con?gurable and may further include sub -components . As the
`number of components and sub-components increases, the
`task of modeling such entity also (exponentially) increases
`along with the resources needed to represent the entity.
`One example of such a complicated entity may be a com
`puter system offered for sale by a vendor. The computer
`system may include a number of components (e.g., chassis,
`processor, storage, and so on) that may be customized to suit
`a buyer’s preference and requirements. Each component may
`be associated with a number of possible choices (e.g., the
`chassis may be tall, medium, or short). A buyer may then
`customize the computer system by selecting a particular
`choice for each component.
`The con?guration of a complicated entity can be challeng
`ing. For practical considerations and possibly due to system
`constraints, not all possible combinations of choices for the
`components (i.e., con?gurations) may be available or valid.
`In one conventional implementation, rules and constraints
`may be de?ned to validate con?gurations. These rules and
`constraints may be invoked once a speci?c con?guration has
`been selected, and are used to determine whether or not that
`con?guration is valid. In another conventional implementa
`tion, all valid con?gurations may be de?ned in a master table.
`Once a speci?c con?guration has been selected, the master
`table may be consulted to validate the con?guration. How
`ever, this master table may be very large for a complicated
`entity.
`Besides the complexity in representing complicated enti
`ties and valid con?gurations, other challenges may also be
`associated with the con?guration process. For example, if the
`validation of a selected con?guration is performed after all
`choices have been selected and the con?guration is then
`deemed to be invalid, then the selection process may need to
`be repeated again. Each iteration of the selection and valida
`tion processes is typically associated with a cost that should
`be minimized. Moreover, it may be desirable to provide rec
`ommendations based on choices that have already been
`selected, and this may be dif?cult to support using the con
`ventional rules/constraints or a master table.
`Thus, techniques that can be used to support con?guration
`of complicated entities are highly desirable.
`
`SUMMARY OF THE INVENTION
`
`The invention provides techniques to con?gure compli
`cated entities using sub-con?guration, which effectively par
`titions the con?guration of a complicated top-level entity into
`a set of con?gurations of smaller sub-level entities (i.e., com
`ponents of the top-level entity) in combination with a con
`?guration of a “simpli?ed” top-level entity. The top-level
`entity may be represented by and con?gured via a parent
`model, and each sub-con?gurable component may be repre
`sented by and con?gured via a child sub-model.
`Sub-con?guration simpli?es the data modeling for con?g
`uring complicated entities. (Data modeling is the process of
`
`5
`
`20
`
`25
`
`30
`
`35
`
`40
`
`45
`
`50
`
`55
`
`60
`
`65
`
`2
`encoding data and logic that represent information used to
`represent con?guration information.) With sub-con?gura
`tion, shared options for the top-level entity may be extracted
`and modeled with a single sub-model or a set of sub-models.
`Each sub-model may be referenced and instantiated as
`needed for any of the common options. The sub-models
`reduce the amount of redundancy by localizing data and logic
`needed to represent the shared options, and further simplify
`the data structure and logic for the top-level entity.
`Multiple levels of sub-con?guration may be supported. In
`this case, each child sub-model may be a parent model that
`includes one or more child sub-models. Each child sub-model
`may also be viewed as an independent model, and each sub
`con?gurable component may be con?gured and validated
`individually and independently.
`Sub-con?guration may be implemented in various man
`ners and based on various data modeling structures. In one
`implementation, data for the parent model and child sub
`models is localized, and parameter values may be bi-direc
`tionally passed between the parent model and sub-models
`such that con?guration may be achieved at both levels. In
`another implementation, data for the parent model and sub
`models is globalized, and data for each level is available to the
`other level.
`A speci?c embodiment of the invention provides a method
`for performing sub-con?guration of components of an entity.
`In the method, the entity is con?gured via a parent model and
`each sub-con?gurable component is con?gured via one of a
`number of sub-models. Initially a selection to con?gure a
`particular sub-con?gurable component of the entity is
`received, and a sub-model for the selected component is
`identi?ed. One or more values for one or more features of the
`selected component are received (e. g., from the parent model
`or via the sub-model) and form a con?guration for the com
`ponent, which is then validated based on the associated sub
`model and the received values. Con?guration of the entity is
`also validated based on the parent model and the validated
`con?guration for the selected component.
`A number of sub-con?gurable components may be con?g
`ured and validated, one component at a time, and the parent
`model may be validated after each validated con?guration of
`a sub-con?gurable component. Feedbacks relating to the
`validity of the selections may be provided for each con?gu
`ration of the parent model and sub-models. The data for the
`parent model and sub-models may be localized or globalized.
`The parent model and one or more sub-models may be dis
`played on one common user interface screen.
`The invention further provides other methods, computer
`program products, and systems capable of implementing
`various aspects, embodiments, and features of the invention,
`as described in further detail below.
`The foregoing, together with other aspects of this inven
`tion, will become more apparent when referring to the fol
`lowing speci?cation, claims, and accompanying drawings.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 shows a computer system that may be modeled and
`con?gured using the techniques of the invention;
`FIG. 2A shows a number of feature tables used to list
`available choices for top-level options of the computer sys
`tem;
`FIG. 2B shows a con?guration table used to represent all
`possible valid con?gurations of the computer system;
`FIGS. 3A and 3B show a data modeling structure that
`supports sub-con?guration using mapped features;
`
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`US 7,873,503 B2
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`FIG. 4 shows an implementation of the data modeling
`structure in FIGS. 3A and 3B for the computer system;
`FIG. 5 is a ?ow diagram of a process that supports sub
`con?guration using mapped features, in accordance with an
`embodiment of the invention;
`FIG. 6 is a ?ow diagram of a process that supports sub
`con?guration using globalized feature tables, in accordance
`with a embodiment of the invention;
`FIGS. 7A, 7B, and 7C show three screens of an example
`top-level pageset, a sub-level pageset, and a feedback pageset
`for a speci?c implementation that utilizes various aspects and
`embodiments of the invention;
`FIG. 8 is a simpli?ed diagram of an embodiment of a
`con?guration system that may be capable of implementing
`various aspects and embodiments of the invention; and
`FIG. 9 is a block diagram of a computer system.
`
`DESCRIPTION OF THE SPECIFIC
`EMBODIMENTS
`
`The techniques described herein may be used to model and
`represent any complicated entity having a number of compo
`nents. These techniques may further be used to support the
`con?guration of the components at the component level using
`sub-con?guration. For clarity, various aspects, embodiments,
`and features of the invention are described for a speci?c
`example entity, which is a computer system.
`FIG. 1 shows a computer system 100 that may be modeled
`and con?gured using the techniques of the invention. System
`100 includes a number of components (or top-level options),
`each of which may be a “selectable” option or a “sub-con?g
`urable” option. In the example shown, the options includes:
`AiChassis, BiProcessor, CiDrive Bay 1, DiDrive Bay
`2, EiDrive Bay 3, FiStorage Device (or Storage), and
`GiPower Supply (or Supply). Each selectable option may
`be associated with a respective set of choices that are speci?c
`for that option. For example, the Chassis option may be
`associated with three possible choicesiShort, Medium, and
`Tall. Each top-lever sub-con?gurable option may be associ
`ated with any number of sub -level options, each of which may
`be a selectable option or a sub-con?gurable option. Each
`top-level sub-con?gurable option may be con?gured based
`on its associated sets of sub-level options. For example, each
`of Drive Bays 1, 2, and 3 may be used to install a disk drive,
`a CD-drive, or a hard disk (i.e., three possible options), or
`nothing at all (which may be a default). The Disk Drive,
`CD-Drive, and Hard Disk options may each be further asso
`ciated with one or more sets of choices that are speci?c for
`that option.
`FIG. 2A shows a number of “feature” tables 21011 through
`210g that may be used to list the available choices for top
`level options A through G, respectively, of computer system
`100. For example, feature table 210a lists the available
`choices for the Chassis option as short, medium, and tall.
`Each remaining feature table 2101) through 210g similarly
`lists the available choices for an associated top-level option.
`The “parent” feature tables 21011 through 210g are shown
`above the dashed line, and the “child” feature tables 210k
`through 210j are shown below the dashed line.
`Each of top-level options C through E (i.e., Drive Bays 1, 2,
`and 3 of computer system 100) may be con?gured to hold one
`of three possible choices (Disk Drive, CD-Drive, and Hard
`Disk components) or nothing. Each of these three compo
`nents may further be associated with one or more sets of
`choices (only one set of choices is shown for each component
`for simplicity). Thus, FIG. 2A also shows feature tables 210k
`through 210j that list the available choices for the Disk Drive,
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`CD-Drive, and Hard Disk components, respectively. Simi
`larly, top-level choice F (i.e., Storage) may be con?gured to
`hold an “ABC” or “XYZ” storage component or nothing.
`FIG. 2A further shows features tables 210k and 210l that list
`the available choices for the ABC and XYZ storage compo
`nents, respectively.
`During the con?guration process for computer system 100,
`one of the available choices for each top-level option may be
`selected. A default value may also be assigned to each top
`level option and may be used as the initial choices or if no
`selection is received for the option. The combination of the
`default and selected choices for all top-level options com
`prises a speci?c con?guration for system 100. In a typical
`conventional implementation, once the choices for all options
`have been selected, the resultant con?guration may be vali
`dated.
`FIG. 2B shows a con?guration table 250 (which is some
`times referred to as a validation matrix) that may be used to
`represent all possible valid con?gurations for computer sys
`tem 100. Table 250 includes a number of columns, one col
`umn for each possible (top-level and sub-level) option of
`computer system 100. Each row of table 250 includes a spe
`ci?c set of values for the listed options. To validate a particu
`lar con?guration based on the con?guration table, the set of
`default/ selected choices for the con?guration may be com
`pared against the rows of table 250. If a row includes the same
`set of choices as the default/ selected choices, then that con
`?guration is deemed to be valid. As can be imagined, the
`number of entries (i.e., rows) in table 250 may be very large
`for a complicated entity with many options and choices.
`In the above example, some of the top-level options (e.g.,
`Drive Bays 1, 2, and 3) share the same common options (e. g.,
`Disk Drive, CD-Drive, and Hard Disk), each of which may be
`represented with a respective set of one or more feature tables.
`If these common options are extracted and separately mod
`eled, then the amount of data that needs to be maintained for
`valid con?gurations may be reduced.
`In many instances, constraints and rules may be applied to
`con?guration of a complicated entity (e.g., computer system
`100). As some examples, a vendor may only support a subset
`of the available processors for a short chassis, all three drive
`bays may be available only for medium and tall chasses, a
`power supply of a particular rating is required for each avail
`able model of storage device, and so on. If the relationship
`between different options can be effectively modeled, then
`the amount of data that needs to be maintained for valid
`con?gurations may also be reduced.
`The invention provides techniques to con?gure compli
`cated entities using sub-con?guration, which provides
`numerous bene?ts. Sub-con?guration effectively partitions
`the overall con?guration of a complicated top-level entity
`(e.g., computer system 100) into a set of con?gurations of
`smaller sub-level entities (e.g., Drive Bays 1, 2, and 3) in
`combination with a less complicated con?guration of a “sim
`pli?ed” top-level entity. The top-level entity may be repre
`sented by and con?gured via a parent model, and each sub
`con?gurable component (or sub-level entity) may be
`represented by and con?gured via a child sub-model.
`With sub-con?guration, a complicated entity may be more
`ef?ciently modeled, con?gured, and validated. Each sub-con
`?gurable option of the entity may be con?gured and validated
`via a respective child sub-model. Generally, suf?cient infor
`mation is made available to the child sub-model such that the
`associated option can be validly con?gured. The required
`information may be provided from the parent level, queried
`and entered at the sub-level via the child sub-model, and/or
`provided via some other mechanisms.
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`An interactive user interface (or screen) may be used to
`support sub-con?guration such that feedbacks can be pro
`vided at the sub-level. The feedbacks may be a warning of an
`invalid con?guration, a suggestion for new selections to
`obtain a valid con?guration, and so on. In this way, con?gu
`ration errors may be localized, ?agged as they occur, and
`remedied immediately. The feedback mechanism also
`reduces the likelihood of invalid choices propagating through
`the con?guration process.
`Once a sub-con?gurable option has been con?gured and
`validated, the parent model may be returned to, and any
`information from the sub-model that may be needed by the
`parent model is made available to the parent. Upon a return
`from the sub-level, or whenever directed, the parent model
`can be run (i.e., executed) in the context of all options that
`have been selected or con?gured. This allows the parent
`model to be validated with any new con?guration made at the
`sub-level.
`Sub-con?guration further simpli?es the data modeling for
`con?guring complicated entities. With sub-con?guration,
`shared options (e. g., Drive Bays 1, 2, and 3) may be extracted
`and modeled with a single sub-model or a set of sub-models.
`Each sub-model may be referenced and instantiated as
`needed by any of the common options. The sub-models
`reduce the amount of redundancy by localizing data and logic
`needed to represent the common options, and further simplify
`the data structure and logic for the top-level entity.
`In essence, sub-con?guration may be used to exploit com
`mon data patterns in a comprehensive con?guration table. In
`this way, valid con?gurations for a complicated entity may be
`represented using a set of smaller tables. In one implementa
`tion, these smaller tables may be “localized” and some of
`these smaller tables may reside at the parent model and the
`remaining smaller tables may be included in the sub-models.
`In another implementation, these smaller tables may be “glo
`balized” and shared between the parent model and sub -mod
`els. These implementations are described in further detail
`below.
`Multiple levels of sub-con?guration may be supported. In
`this case, each child sub-model may be a parent model that
`includes one or more child sub-models. In the following
`description, the parent model (or top-level) corresponds to the
`current level being con?gured, and the child sub-models (or
`sub-level) correspond to a lower level that may be con?gured
`using sub-con?guration. The current level may also be the
`sub-level of a higher level.
`Each child sub-model may also be viewed as an indepen
`dent model. In such a design, the child sub-model may rep
`resent a particular entity (i.e., a component may be viewed as
`an entity) and may be used independently of the parent model
`or other sub-models to con?gure that particular entity. Each
`sub-con?gurable option may thus be con?gured and vali
`dated individually and independently.
`Sub-con?guration may be implemented in various man
`ners and based on various data modeling structures. In one
`implementation, data for the parent model and child sub
`models is localized, and parameter values may be (bi-direc
`tionally) passed between the parent model and child sub
`models such that con?guration may be achieved at both
`levels. In an embodiment, each sub-model includes one or
`more features mapped from the parent model, and a value for
`each mapped feature that affects con?guration at the sub
`level may be passed from the parent model to the sub-model.
`Correspondingly, values needed by the parent model may be
`returned from the sub -model after con?guration of the child is
`completed.
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`In another implementation, data for the parent model and
`child sub-models is globalized. In this implementation, the
`tables used for con?guration at both the top-level and sub
`level are available to the parent model and sub-models. This
`globalized data modeling structure can provide certain advan
`tages as described below. These two sub-con?guration imple
`mentations and data modeling structures are described below.
`
`Sub-Con?guration Using Feature Mapping
`
`In one implementation for sub-con?guration, which uses
`mapped features, parameter values needed for con?guration
`and validation at the parent model and child sub-models are
`passed between these two levels. Each sub-model is provided
`with suf?cient information needed to con?gure and validate
`the option represented by that sub-model. Some of the
`required information may be obtained at the parent model and
`passed to the sub-model as mapped features. Other informa
`tion may be collected in the sub-model. Upon returning from
`the child sub-model to the parent model, values for the
`mapped features are returned from the child sub -model to the
`parent model.
`FIG. 3A shows a data modeling structure 300 that supports
`sub-con?guration using mapped features. Structure 300 sup
`ports mapping of features between the parent model and child
`sub-models to perform sub-con?guration, as described
`below. The mapped features are akin to parameters that may
`be bi-directionally passed between the parent model and child
`sub-models.
`As shown in FIG. 3A, structure 300 includes a sub-model
`mapping set 310 that includes a number of (N) elements, one
`element for each sub-con?gurable option a the top level. For
`example, sub-model mapping set 310 may include four ele
`ments for options C, D, E, and F (i.e., Drive Bays 1, 2, and 3
`and Storage) of computer system 100. Each element of map
`ping set 310 is associated with a respective sub-model map
`320. For example, option F (Storage) may be associated with
`a sub-model map that includes the two available types of
`storages devices (“ABC” and “XYZ”). Similarly, option C
`(Drive Bay 1) may be associated with a sub-model map that
`includes the three available drive types (Disk Drive, CD
`Drive, and Hard Disk). Each sub -model map 320 may further
`be associated with a set of (M) sub-models 330, where M may
`be one or greater. For example, the sub -model map for option
`F (Storage) may include a ?rst sub-model for theABC storage
`device and a second sub-model for the XYZ storage device.
`FIG. 3B shows an embodiment of a sub-model 330X,
`which may be one of several that may be used for a particular
`sub-model map 320. In general, sub-model 330X includes
`suf?cient information needed to con?gure the option repre
`sented by that sub-model. In the embodiment shown in FIG.
`3B, sub-model 330X includes a set of (L) features 340, where
`L can be one or greater. The ?rst feature 340a may include the
`available choices for the option represented by that sub
`model. Each additional feature may represent either a
`“mapped” feature from the parent model or a “local” feature
`of that sub -model. A mapped feature in the sub -model corre
`sponds to a feature in the parent model, and may be used for
`validation of the sub-model. A local feature in the sub-model
`may be used to further con?gure the option represented by the
`sub-model, and typically does not affect the con?guration at
`the parent model.
`Each feature 340 is associated with a feature mapping set
`342, which includes a set of (K) feature map values 344,
`where K can be one or greater. Feature mapping set 342
`represents the set of possible choices for that feature 340 in
`the sub-model 330X, and each feature map value 344 repre
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`sents a speci?c choice for the feature. Feature tables 340 of
`sub -model 330X may represent different types of information
`and may be used in a number of different ways, as described
`below.
`In general, if multiple levels of sub-con?guration are sup
`ported, each sub-model may be a parent model that includes
`selectable and/ or sub-con?gurable options. One local feature
`table may be provided for each selectable option in the sub
`model, and one sub-model mapping set and its associated
`sub-models may be provided for each sub-con?gurable
`option in the sub-model. Each sub-model may thus be a
`model that is independent of the parent model and other
`sub-models, and may be individually and separately con?g
`ured and validated. The dependency between the sub-model
`and parent model may be modeled and expressed via the
`mapped features and the passed parameter values, as
`described below.
`The use of sub-models for top-level sub-con?gurable