Abstract:
A method and system are provided for data driven shrinkage compensation. The method includes subdividing, by a polygon subdivider, polygons in a three-dimensional file into facets. The method further includes calculating, by an axis dimension calculator, dimensions of an object from an x-directional strand disposed between two facets of a first predetermined facet pair, a y-directional strand disposed between two facets of second predetermined facet pair, and a z-directional strand disposed between two facets of a third predetermined facet pair. The object is formed from at least some of the polygons. The method also includes predicting, by a dimension change predictor, dimensional changes in the strands based on a shape shrinkage model. The method additionally includes correcting, by a dimension change compensator, x-coordinate data, y-coordinate data, and z-coordinate data of at least one facet of the predetermined facet pairs to compensate for the dimensional changes in the strands.

Description:
BACKGROUND 
       [0001]    Technical Field 
         [0002]    The present invention relates generally to information processing and, in particular, to data driven shrinkage compensation. 
         [0003]    Description of the Related Art 
         [0004]    Three-dimensional (3D) printing, also known as Additive Manufacturing, has attracted considerable interest in the past few years. In contrast to the material removal processes of traditional machining, the 3D printing adds material layer by layer to construct 3D objects. 
         [0005]    When fabricating a 3D object using a 3D printer, the process involves various disturbances that can cause dimensional errors. In order to reduce the dimensional errors, a 3D printer maker provides a guidance to modify the 3D shape uniformly, or technical experts often modify the shapes of the 3D CAD model based on their experiments and intuitions. However, the dimensional errors in the 3D printed object are not uniform. When the 3D shape is complicated, even experts are no longer able to correct the shape. 
         [0006]    Thus, there is a need for an automatic shape modification method to compensate the dimensional errors in 3D printed objects. 
       SUMMARY 
       [0007]    According to an aspect of the present principles, a method is provided for data driven shrinkage compensation. The method includes subdividing, by a polygon subdivider, polygons in a three-dimensional file into facets. The method further includes calculating, by an axis dimension calculator, dimensions of an object in the three-dimensional file from an x-directional strand disposed between two facets of a first predetermined facet pair, a y-directional strand disposed between two facets of second predetermined facet pair, and a z-directional strand disposed between two facets of a third predetermined facet pair. The object is formed from at least some of the polygons. The method also includes predicting, by a dimension change predictor, dimensional changes in the x-directional strand, the y-directional strand, and the z-directional strand based on a shape shrinkage model. The method additionally includes correcting, by a dimension change compensator, x-coordinate data, y-coordinate data, and z-coordinate data of at least one facet of the predetermined facet pairs to compensate for the dimensional changes in the x-directional strand, the y-directional strand, and the z-directional strand. 
         [0008]    According to another aspect of the present principles, a system is provided for data driven shrinkage compensation. The system includes a polygon subdivider for subdividing polygons in a three-dimensional file into facets. The system further includes an axis dimension calculator for calculating dimensions of an object in the three-dimensional file from an x-directional strand disposed between two facets of a first predetermined facet pair, a y-directional strand disposed between two facets of second predetermined facet pair, and a z-directional strand disposed between two facets of a third predetermined facet pair. The object is formed from at least some of the polygons. The system also includes a dimension change predictor for predicting dimensional changes in the x-directional strand, the y-directional strand, and the z-directional strand based on a shape shrinkage model. The system additionally includes a dimension change compensator for correcting x-coordinate data, y-coordinate data, and z-coordinate data of at least one facet of the predetermined facet pairs to compensate for the dimensional changes in the x-directional strand, the y-directional strand, and the z-directional strand. 
         [0009]    These and other features and advantages will become apparent from the following detailed description of illustrative embodiments thereof, which is to be read in connection with the accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0010]    The disclosure will provide details in the following description of preferred embodiments with reference to the following figures wherein: 
           [0011]      FIG. 1  shows an exemplary processing system  100  to which the present principles may be applied, in accordance with an embodiment of the present principles; 
           [0012]      FIG. 2  shows an exemplary system  200  for data driven shrinkage compensation, in accordance with an embodiment of the present principles; and 
           [0013]      FIG. 3  shows an exemplary method  300  for data driven shrinkage compensation, in accordance with an embodiment of the present principles; 
           [0014]      FIG. 4  shows an exemplary method  400  for building a shrinkage model, in accordance with an embodiment of the present principles; 
           [0015]      FIG. 5  further shows steps  310  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles; 
           [0016]      FIG. 6  further shows step  315  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles; 
           [0017]      FIG. 7  further shows step  325  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles; 
           [0018]      FIG. 8  further shows step  340  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles; 
           [0019]      FIG. 9  shows an exemplary cloud computing node  910 , in accordance with an embodiment of the present principles; 
           [0020]      FIG. 10  shows an exemplary cloud computing environment  1050 , in accordance with an embodiment of the present principles; and 
           [0021]      FIG. 11  shows exemplary abstraction model layers, in accordance with an embodiment of the present principles. 
       
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
       [0022]    The present principles are directed to data driven shrinkage compensation. 
         [0023]      FIG. 1  shows an exemplary processing system  100  to which the present principles may be applied, in accordance with an embodiment of the present principles. The processing system  100  includes at least one processor (CPU)  104  operatively coupled to other components via a system bus  102 . A cache  106 , a Read Only Memory (ROM)  108 , a Random Access Memory (RAM)  110 , an input/output (I/O) adapter  120 , a sound adapter  130 , a network adapter  140 , a user interface adapter  150 , and a display adapter  160 , are operatively coupled to the system bus  102 . 
         [0024]    A first storage device  122  and a second storage device  124  are operatively coupled to system bus  102  by the I/O adapter  120 . The storage devices  122  and  124  can be any of a disk storage device (e.g., a magnetic or optical disk storage device), a solid state magnetic device, and so forth. The storage devices  122  and  124  can be the same type of storage device or different types of storage devices. 
         [0025]    A speaker  132  is operatively coupled to system bus  102  by the sound adapter  130 . A transceiver  142  is operatively coupled to system bus  102  by network adapter  140 . A display device  162  is operatively coupled to system bus  102  by display adapter  160 . 
         [0026]    A first user input device  152 , a second user input device  154 , and a third user input device  156  are operatively coupled to system bus  102  by user interface adapter  150 . The user input devices  152 ,  154 , and  156  can be any of a keyboard, a mouse, a keypad, an image capture device, a motion sensing device, a microphone, a device incorporating the functionality of at least two of the preceding devices, and so forth. Of course, other types of input devices can also be used, while maintaining the spirit of the present principles. The user input devices  152 ,  154 , and  156  can be the same type of user input device or different types of user input devices. The user input devices  152 ,  154 , and  156  are used to input and output information to and from system  100 . 
         [0027]    Of course, the processing system  100  may also include other elements (not shown), as readily contemplated by one of skill in the art, as well as omit certain elements. For example, various other input devices and/or output devices can be included in processing system  100 , depending upon the particular implementation of the same, as readily understood by one of ordinary skill in the art. For example, various types of wireless and/or wired input and/or output devices can be used. Moreover, additional processors, controllers, memories, and so forth, in various configurations can also be utilized as readily appreciated by one of ordinary skill in the art. These and other variations of the processing system  100  are readily contemplated by one of ordinary skill in the art given the teachings of the present principles provided herein. 
         [0028]    Moreover, it is to be appreciated that system  200  described below with respect to  FIG. 2  is a system for implementing respective embodiments of the present principles. Part or all of processing system  100  may be implemented in one or more of the elements of system  200 . 
         [0029]    Further, it is to be appreciated that processing system  100  may perform at least part of the method described herein including, for example, at least part of method  300  of  FIG. 3  and/or at least part of method  400  of  FIG. 4 . Similarly, part or all of system  200  may be used to perform at least part of method  300  of  FIG. 3  and/or at least part of method  400  of  FIG. 4 . 
         [0030]      FIG. 2  shows an exemplary system  200  for data driven shrinkage compensation, in accordance with an embodiment of the present principles. 
         [0031]    The system  200  includes a polygon subdivider  210 , a polygon labeler  220 , a sampler  230 , a memory  240 , an axis dimension calculator  250 , a shape shrinkage model generator  260 , a dimension change predictor  270 , a dimension change compensator  280 , a three-dimensional printer  281 , and a three-dimensional scanner  282 . 
         [0032]    The polygon subdivider  210  subdivides polygons in a 3D model file to increase resolution. The 3D model can be, for example, in STereoLithography (STL) format, Additive Manufacturing File (AMF) format, and so forth. 
         [0033]    The polygon labeler  220  numbers each polygon (facet) and polygon vertices. The same number is assigned to the same coordinate of vertices. The step makes the 3D model modification more efficient. 
         [0034]    The sampler  230  sets sampling points on the polygons, and performs sampling of the polygons using the sampling points. In an embodiment, in order to set the sampling points automatically, the ray intersection algorithm or the point-in-polygon algorithm can be used. Of course, other sampling approaches can also be used, while maintaining the spirit of the present principles. 
         [0035]    The memory  240  stores the polygon number to which each sample point belongs. 
         [0036]    The axis dimension calculator  250  calculates the dimensions of the x-direction (x-strand), the y-direction (y-strand), and the z-direction (z-strand). In an embodiment, the x-direction (x-strand) is calculated from opposing sampling points with the same z-coordinate and y-coordinate, the y-direction (y-strand) is calculated from opposing sampling points with the same x-coordinate and z-coordinate, and the z-direction (z-strand) is calculated from opposing sampling points with the same x-coordinate and y-coordinate. 
         [0037]    The shape shrinkage model generator  260  generates and/or otherwise derives a shape shrinkage model from a test artifact. Preferably, the test artifact has rich shape variations. 
         [0038]    The dimension change predictor  270  predicts, using the shape shrinkage model, the length change of each strand when the object is printed with a 3D printer. 
         [0039]    The dimension change compensator  280  compensates for changes in the shape. In an embodiment, for example, the vertices of polygons are moved so that the length change of strands is compensated. While shown separate from 3D printer  281 , in an embodiment, the dimension change compensator  280  is included in the 3D printer. 
         [0040]    The three-dimensional printer  281  prints out objects that have been compensated and test artifacts used to build the shape shrinkage model. 
         [0041]    The three-dimensional scanner  282  scans objects and test artifacts. For example, a test artifact can be scanned in order to generate the shape shrinkage model from the scanned dimensions. 
         [0042]    In the embodiment shown in  FIG. 2 , the elements thereof are interconnected by a bus/network(s)  201 . However, in other embodiments, other types of connections can also be used. Moreover, in an embodiment, at least one of the elements of system  200  is processor-based. Further, while one or more elements may be shown as separate elements, in other embodiments, these elements can be combined as one element. The converse is also applicable, where while one or more elements may be part of another element, in other embodiments, the one or more elements may be implemented as standalone elements. These and other variations of the elements of system  200  are readily determined by one of ordinary skill in the art, given the teachings of the present principles provided herein, while maintaining the spirit of the present principles. 
         [0043]      FIG. 3  shows an exemplary method  300  for data driven shrinkage compensation, in accordance with an embodiment of the present principles. 
         [0044]    At step  305 , subdivide polygons in a 3D model file to increase resolution. 
         [0045]    At step  310 , number each polygon (facet) and polygon vertices. The same number is assigned to the same coordinate of vertices. The step makes the 3D model modification more efficient. 
         [0046]    At step  315 , set sampling points on the polygons. 
         [0047]    At step  320 , record the polygon number to which each sample point belongs. 
         [0048]    At step  325 , calculate the dimensions of the x-direction (x-strand) from opposing sampling points with the same z-coordinate and y-coordinate. Similarly, calculate the dimensions of the y-direction (y-strand) and the z-direction (z-strand). 
         [0049]    At step  330 , derive a shape shrinkage model from a test artifact. 
         [0050]    At step  335 , predict, using the shape shrinkage model, the length change of each strand when the object is printed with a 3D printer. 
         [0051]    At step  340 , compensate for shrinkage based on the predicted length of change (per step  335 ). For example, move the vertices of polygons so that the length change of strands are compensated. 
         [0052]    In an embodiment, the polygons which belong to both ends of the strand are identified. When it is predicted that the length of the strand shrinks Lc mm, each polygon moves Lc/2 mm so that the shrinkage of the strand is compensated. 
         [0053]    While Lc/2 was used as an example, it is to be appreciated that the present principles are not limited to the same. For example, in an embodiment, movements of (Lc/3 and 2Lc/3), and so forth can also be used in accordance with the teachings of the present principles, while maintaining the spirit of the present principles. Thus, in the preceding case, one polygon is moved LC/3 and the other polygon is moved 2LC/3. In other embodiments, other values can be used. 
         [0054]      FIG. 4  shows an exemplary method  400  for building a shrinkage model, in accordance with an embodiment of the present principles. 
         [0055]    At step  405 , prepare a 3D model file of the test artifact. 
         [0056]    At step  410 , set sampling points on the polygons of the test artifact (with the same procedure as in method  300 ). 
         [0057]    At step  415 , print out the test artifact by a 3D printer. 
         [0058]    At step  420 , acquire the dimensions of the 3D printed test artifact as point-cloud-data. In an embodiment, the dimensions are acquired using a commercially available 3D scanning system. 
         [0059]    At step  425 , find detailed errors of the 3D printed object&#39;s dimensions by matching the 3D model data with the point-cloud-date. In an embodiment, step  425  can be performed using CAT software. 
         [0060]    At step  430 , calculate strands of the 3D model of the test artifact and strands of the 3D printed test artifact as in method  300 . 
         [0061]    At step  435 , generate the shrinkage model from the change of strand length between the 3D model of the test artifact and the actual measurement of the 3D printed test artifact. 
         [0062]    In an embodiment, the shrinkage model can be built using any mathematical shrinkage prediction method including, but not limited to, kernel regression, neural network, and deep learning. The accuracy of the shrinkage model may be made more precise by adding more datasets. 
         [0063]      FIG. 5  further shows steps  310  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles. Each facet (Facet 1, Facet 2) of a polygon  500  as shown on the left side is labeled with a facet number and vertice numbers as shown on the right side. In particular, the letter “F” followed by an integer (i.e., F1, F2) denotes a facet number, and the letter “v” followed by an integer (i.e., v6, v7, v8, v9) denotes a vertice number. 
         [0064]      FIG. 6  further shows step  315  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles. 
         [0065]    The left side of  FIG. 6  shows a ray intersection method  651  for setting sampling points, and the right side of  FIG. 6  shows a point-in-polygon method  652  for setting sampling points. 
         [0066]    In the ray intersection method  651 , the origin of a ray  699  is set. A point at the intersection of the ray  699  with a polygon is recorded. Here, the ray  699  intersects polygon  601  at intersection (A) and intersects polygon  602  at intersection (B). Thus, intersection (A) and intersection (B) are used as sampling points. In the ray intersection method  651 , the origin of a ray  699  is set, and then the ray is projected in parallel to and along the x-direction, the y-direction, and the x-direction. 
         [0067]    In the point-in-polygon method  652 , sample point candidates are distributed in the 3D model. Then sample points in the polygons are chosen. 
         [0068]      FIG. 7  further shows step  325  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles. 
         [0069]    For the length of the X direction, an x-strand  701  having a same y-coordinate and z-coordinate is used. The x-strand  701  starts from a point on the left face  711  of the cube and ends on a point on the right face  712  of the cube, where both points have the same y-coordinate and z-coordinate. For the length of the Y direction, a y-strand  702  having a same x-coordinate and z-coordinate is used. The y-strand  702  starts from a point on the front face  721  of the cube and ends on a point on the back face  722  of the cube, where both points have the same x-coordinate and z-coordinate. For the length of the Z direction, a z-strand  703  having a same x-coordinate and y-coordinate is used. The x-strand  703  starts from a point on the bottom face  731  of the cube and ends on a point on the top face  732  of the cube, where both points have the same x-coordinate and y-coordinate. 
         [0070]      FIG. 8  further shows step  340  of method  300  of  FIG. 3 , in accordance with an embodiment of the present principles. The top-most pair of polygons are from the 3D model, the middle pair of polygons are from the 3D printed object, and the bottom-most pair of polygons are the shrinkage compensated polygons from the 3d model. The example of  FIG. 8  relates to the case where the polygons  801  and  802  which belong to both ends of the strand are identified, and for a prediction that the length of the strand shrinks Lc mm, each polygon  801  and  802  moves Lc/2 mm so that the shrinkage of the strand is compensated. Sampling point  891  is on polygon  801  and sampling point  892  is on polygon  802 . 
         [0071]    Again it is noted that while Lc/2 was used as an example, the present principles are not limited to the same. For example, in an embodiment, movements of Lc/3, 2Lc/3, and so forth can also be used in accordance with the teachings of the present principles, while maintaining the spirit of the present principles. 
         [0072]    It is understood in advance that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed. 
         [0073]    Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models. 
         [0074]    Characteristics are as follows: 
         [0075]    On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service&#39;s provider. 
         [0076]    Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs). 
         [0077]    Resource pooling: the provider&#39;s computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter). 
         [0078]    Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time. 
         [0079]    Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service. 
         [0080]    Service Models are as follows: 
         [0081]    Software as a Service (SaaS): the capability provided to the consumer is to use the provider&#39;s applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings. 
         [0082]    Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations. 
         [0083]    Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls). 
         [0084]    Deployment Models are as follows: 
         [0085]    Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises. 
         [0086]    Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises. 
         [0087]    Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services. 
         [0088]    Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load balancing between clouds). 
         [0089]    A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes. 
         [0090]    Referring now to  FIG. 9 , a schematic of an example of a cloud computing node  910  is shown. Cloud computing node  910  is only one example of a suitable cloud computing node and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless, cloud computing node  910  is capable of being implemented and/or performing any of the functionality set forth hereinabove. 
         [0091]    In cloud computing node  910  there is a computer system/server  912 , which is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with computer system/server  912  include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like. 
         [0092]    Computer system/server  912  may be described in the general context of computer system executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system/server  912  may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices. 
         [0093]    As shown in  FIG. 9 , computer system/server  912  in cloud computing node  910  is shown in the form of a general-purpose computing device. The components of computer system/server  912  may include, but are not limited to, one or more processors or processing units  916 , a system memory  928 , and a bus  918  that couples various system components including system memory  928  to processor  916 . 
         [0094]    Bus  918  represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus. 
         [0095]    Computer system/server  912  typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server  912 , and it includes both volatile and non-volatile media, removable and non-removable media. 
         [0096]    System memory  928  can include computer system readable media in the form of volatile memory, such as random access memory (RAM)  930  and/or cache memory  932 . Computer system/server  912  may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system  934  can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM or other optical media can be provided. In such instances, each can be connected to bus  918  by one or more data media interfaces. As will be further depicted and described below, memory  928  may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention. 
         [0097]    Program/utility  940 , having a set (at least one) of program modules  942 , may be stored in memory  928  by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment. Program modules  942  generally carry out the functions and/or methodologies of embodiments of the invention as described herein. 
         [0098]    Computer system/server  912  may also communicate with one or more external devices  914  such as a keyboard, a pointing device, a display  924 , etc.; one or more devices that enable a user to interact with computer system/server  912 ; and/or any devices (e.g., network card, modem, etc.) that enable computer system/server  912  to communicate with one or more other computing devices. Such communication can occur via Input/Output (I/O) interfaces  922 . Still yet, computer system/server  912  can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter  920 . As depicted, network adapter  920  communicates with the other components of computer system/server  912  via bus  918 . It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer system/server  912 . Examples, include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data archival storage systems, etc. 
         [0099]    Referring now to  FIG. 10 , illustrative cloud computing environment  1050  is depicted. As shown, cloud computing environment  1050  comprises one or more cloud computing nodes  1010  with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone  1054 A, desktop computer  1054 B, laptop computer  1054 C, and/or automobile computer system  1054 N may communicate. Nodes  1010  may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment  1050  to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices  1054 A-N shown in  FIG. 10  are intended to be illustrative only and that computing nodes  1010  and cloud computing environment  1050  can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). 
         [0100]    Referring now to  FIG. 11 , a set of functional abstraction layers provided by cloud computing environment  1050  ( FIG. 10 ) is shown. It should be understood in advance that the components, layers, and functions shown in  FIG. 11  are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided: 
         [0101]    Hardware and software layer  1160  includes hardware and software components. Examples of hardware components include mainframes, in one example IBM® zSeries® systems; RISC (Reduced Instruction Set Computer) architecture based servers, in one example IBM pSeries® systems; IBM xSeries® systems; IBM BladeCenter® systems; storage devices; networks and networking components. Examples of software components include network application server software, in one example IBM WebSphere® application server software; and database software, in one example IBM DB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter, WebSphere, and DB2 are trademarks of International Business Machines Corporation registered in many jurisdictions worldwide). 
         [0102]    Virtualization layer  1162  provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers; virtual storage; virtual networks, including virtual private networks; virtual applications and operating systems; and virtual clients. 
         [0103]    In one example, management layer  1164  may provide the functions described below. Resource provisioning provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal provides access to the cloud computing environment for consumers and system administrators. Service level management provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA. 
         [0104]    Workloads layer  1166  provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation; software development and lifecycle management; virtual classroom education delivery; data analytics processing; transaction processing; and data driven shrinkage compensation. 
         [0105]    The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
         [0106]    The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
         [0107]    Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
         [0108]    Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
         [0109]    Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
         [0110]    These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
         [0111]    The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
         [0112]    The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
         [0113]    Reference in the specification to “one embodiment” or “an embodiment” of the present principles, as well as other variations thereof, means that a particular feature, structure, characteristic, and so forth described in connection with the embodiment is included in at least one embodiment of the present principles. Thus, the appearances of the phrase “in one embodiment” or “in an embodiment”, as well any other variations, appearing in various places throughout the specification are not necessarily all referring to the same embodiment. 
         [0114]    It is to be appreciated that the use of any of the following “/”, “and/or”, and “at least one of”, for example, in the cases of “A/B”, “A and/or B” and “at least one of A and B”, is intended to encompass the selection of the first listed option (A) only, or the selection of the second listed option (B) only, or the selection of both options (A and B). As a further example, in the cases of “A, B, and/or C” and “at least one of A, B, and C”, such phrasing is intended to encompass the selection of the first listed option (A) only, or the selection of the second listed option (B) only, or the selection of the third listed option (C) only, or the selection of the first and the second listed options (A and B) only, or the selection of the first and third listed options (A and C) only, or the selection of the second and third listed options (B and C) only, or the selection of all three options (A and B and C). This may be extended, as readily apparent by one of ordinary skill in this and related arts, for as many items listed. 
         [0115]    Having described preferred embodiments of a system and method (which are intended to be illustrative and not limiting), it is noted that modifications and variations can be made by persons skilled in the art in light of the above teachings. It is therefore to be understood that changes may be made in the particular embodiments disclosed which are within the scope of the invention as outlined by the appended claims. Having thus described aspects of the invention, with the details and particularity required by the patent laws, what is claimed and desired protected by Letters Patent is set forth in the appended claims.