Patent Publication Number: US-2020278975-A1

Title: Searching data on a synchronization data stream

Description:
BACKGROUND OF THE INVENTION 
     The present invention relates generally to the field of data stream analytics, and more particularly, to maintaining a search index for searching near-real time data under a high throughput environment. 
     SUMMARY 
     Embodiments of the present invention disclose a method, a computer system, and computer program products. A search request is received. One of one or more search granularity classes based on the subject matter of the search request is assigned. A data synchronization stream of data records to generate a search index based on the one or more search granularity classes is indexed. Responsive to indexing a predefined number of data records associated with the assigned search granularity class, a search based on the received search request is performed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of a synchronization data stream searching environment, in accordance with an embodiment of the present invention; 
         FIGS. 2A and 2B  are block diagrams of synchronization data streams, in accordance with an embodiment of the present invention; 
         FIG. 3  is a block diagram of concurrent synchronization data streams, in accordance with an embodiment of the present invention; 
         FIG. 4  is a block diagram illustrating a hash map for more than one search granularity class; 
         FIG. 5  is a flowchart illustrating operational steps for creating a search index, in accordance with an embodiment of the present invention; 
         FIG. 6  is a flowchart illustrating operational steps for performing a search, in accordance with an embodiment of the present invention; 
         FIG. 7  is a block diagram of internal and external components of the computer systems of  FIG. 1 , in accordance with an embodiment of the present invention; 
         FIG. 8  depicts a cloud computing environment according to an embodiment of the present invention; and 
         FIG. 9  depicts abstraction model layers, in accordance with an embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Computer systems implemented in a cloud environment can be used to initiate, monitor, and manage a data synchronization process to access data that can be requested by a target computer system. The data synchronization process may involve synchronizing a large amount data, including legacy data and incoming data streams, from a source computer system to a target computer system. 
     During a data synchronization process, a computer system can index a synchronization data stream to generate a search index. As a search index is generated, a received search request can be analyzed by the computer system to define one or more search granularity classes associated with the received search request. For example, a computer system, such as a managed file transfer (MFT) system, may receive a search request from a target computer system, where the target computer system is requesting near-real time access to data stored in one or more computer systems of the cloud environment, as well as near-real time access to data from a synchronization data stream. The phrase, “search granularity class,” as used herein, refers to a category or class of a search request, based on a subject matter of the search request. After a search granularity class is defined, a search granularity size can be determined that is associated with the defined search granularity class, where the search granularity size indicates a number of data records to be received for the defined search granularity class to perform a search based on a received search request. 
     A search granularity status can be associated with a defined search granularity class, where the search granularity status indicates whether a received search request can be performed (i.e., perform a search based on the received search request), based on a number of data records received for the defined search granularity class. In certain instances, a computer system can receive more than one search request at a time, which may result in defining more than one search granularity class. In instances involving more than one defined search granularity class, a hash-code map can be implemented by a computer system to manage the more than one defined search granularity class. 
     In general, synchronization data stream analytics, such as searching a synchronization data stream, can be performed on a cloud environment that involves movement of structured data from a computer system. In this exemplary embodiment, an MFT system can be implemented in the cloud environment. It should be understood that, although the exemplary embodiment involves a cloud environment that implements an MFT system, other computer systems can be implemented in the cloud environment, such that data stream analytics can be performed. For example, data stream analytics can be performed on a cloud environment which involves data movement from an online transactional processing (OLTP) computer system to an online analytical processing (OLAP) computer system. 
     Embodiments of the present invention provide systems, methods, and computer program products for performing searches on data from a synchronization data stream at near-real time. Embodiments of the present invention can provide users of computer systems in a cloud environment with access to search request results in near-real time during a data synchronization process. 
       FIG. 1  is a functional block diagram of synchronization data stream searching environment  100 , in accordance with an embodiment of the present invention. Synchronization data stream searching environment  100  includes target computer system  110 , source computer system  130 , and MFT system  140 , which are connected via network  120 . As previously described, MFT system  140  can be another computer system, such as a monitoring computer system, in accordance with an embodiment of the present invention. Target computer system  110 , source computer system  130 , and MFT system  140  can be desktop computers, laptop computers, specialized computer servers, or any other computer systems known in the art, in accordance with an embodiment of the present invention. In certain embodiments, target computer system  110 , source computer system  130 , and MFT system  140  represent computer systems utilizing clustered computers and components to act as a single pool of seamless resources when accessed through network  120 . In general, target computer system  110 , source computer system  130 , and MFT system  140  are representative of any electronic devices or combination of electronic devices, capable of executing machine-readable program instructions in accordance with an embodiment of the present invention, as described in greater detail with regard to  FIG. 7 . In other embodiments, target computer system  110 , source computer system  130 , and MFT system  140  may be implemented in a cloud computing environment, as described in greater detail with regard to  FIGS. 8 and 9 . 
     Source computer system  130  represents a platform containing data that can be transmitted from source computer system  130  as a part of a synchronization data stream. For example, source computer system  130  can be a part of an on premise enterprise computing environment, such as a warehouse management center that manages existing data as well as incoming data streams. Existing data of the warehouse management center may include client records, previously executed inventory transactions, logistical procedures, risk management protocol, etc. Incoming data streams may be received by the warehouse management center, such as updates of inventory statuses, incoming purchase orders, incoming reports for forecasting inventory demand, etc. 
     Target computer system  110  represents a platform that receives information stored on source computer system  130 . In one embodiment, a user of target computer system  110  can submit a search request. In another embodiment, target computer system  110  may automatically transmit a search request based on a schedule and/or other conditions specified by an administrative user of target computer system  110 . In an exemplary embodiment, a search request can include an alert search request, a node search request, a process search request, and rule search request. An alert search request may involve a request to receive a notification, such as a message, that describes an event meeting criteria that is specified by the alert search request. A process search request may involve a request to receive a notification that describes parameters for data synchronization activity, such as moving particular files between source computer system  130  and target computer system  110 , ongoing processes, programs, and commands, monitoring and controlling processes, handling of processing errors. A rule search request may involve a request to receive a list of attributes for data that is involved in a data synchronization process, such as a file name, file type or file extension, dates, owner, a container name associated with the data, etc. A node search request may involve a request to receive monitoring information for node, such as a computer system. 
     MFT system  140  represents a platform that manages a data synchronization process. As previously described, MFT system  140  can represent any platform, service, or computer system that monitors a data synchronization process. For example, MFT system  140  can be a monitoring service that monitors a synchronization data stream, where the synchronization data stream is initiated by a separate computer system (not depicted). In one embodiment, MFT system  140  initiates a process to receive a synchronization data stream. MFT system  140  may also implement additional components to define a search granularity class based on a received search request, index data from the synchronization data stream, and perform the received search request, as described in greater detail below. In certain embodiments, MFT system  140  determines an order in which synchronization data streams are initiated, based on a weight matrix. For example, a weight matrix can be implemented to identify a synchronization data stream to initiate, based on a number of data records in the identified synchronization data stream that are associated with a defined search granularity class for a received search request. 
     Search engine  142  represents an application configured to perform received search requests that are transmitted by target computer system  110 . In this embodiment, search engine  142  defines a search granularity class for a received search request. 
     Search index  144  represents a one or more data structures referenced by search engine  142  that contains indexed data from a synchronization data stream received by MFT system  140 . For example, data can be indexed with respect to one or more defined search granularity classes. In certain embodiments, search index  144  may include a hash-code map that is configured to maintain information for multiple search granularity classes that are being processed by search engine  142  concurrently. 
     Search index creation module  146  represents a module that generates search index  144 . Search index creation module  146  can analyze synchronization data streams received by MFT system  140  and index the data from the synchronization data streams by generating search index  144 . 
     Network  120  can be, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, or a combination of the two, and include wired, wireless, or fiber optic connections. In general, network  120  can be any combination of connections and protocols that will support communications between target computer system  110 , source computer system  130 , and MFT system  140 , in accordance with a desired embodiment of the invention. 
     Embodiments of the invention are described with respect to the components and their functionality as presented in  FIG. 1 . Other embodiments of the invention may perform the invention as claimed with different functional boundaries between components. For example, the functionality of search engine  142  and components therein may be implemented as a part of a standalone component, or may be incorporated as a function of source computer system  130  and/or target computer system  110 . In another example, MFT system  140  can represent one or more computer systems that are configured to monitor a data synchronization stream in synchronization data stream searching environment  100 . 
       FIGS. 2A and 2B  are block diagrams of synchronization data stream unit  202 , in accordance with an embodiment of the present invention. In this embodiment, synchronization data stream unit  202  includes a set of data records that are a part of a data synchronization process managed by MFT system  140  from time T 0    210  to time T 2    230 . For example, search engine  142  can receive an alert search request, define an alert search granularity class from the received alert search request, and receive data records for the defined alert search granularity class that are contained in synchronization data stream unit  202  or indexed in search index  144 , until a determined search granularity size is met. In one embodiment data stream unit  202  may be initiated at time T 0    210 , responsive to search engine  142  receiving a search request. In another embodiment, a search request may be received at a time after synchronization data stream unit  202  is initiated. As previously described, a search granularity status indicates whether a received search request can be performed, based on a number of data records received for the defined search granularity class. For example, a search granularity status for a defined search granularity class can have an integrity status, pending status, or an inactive status. A search granularity integrity status indicates that a determined granularity size for a defined search granularity class has been met. A search granularity pending status indicates that a determined granularity size for a defined search granularity class has not yet been met. A search granularity inactive status indicates that no data records indexed in search index  144  or in a synchronization data stream unit, such as synchronization data stream unit  202 , can be received. In this exemplary embodiment, MFT system  140  is implemented, but it should be understood that, in other embodiments one or more computer systems can be implemented to manage synchronization data stream unit  202 , as previously described. 
     In  FIG. 2A , search engine  142  determines that a determined search granularity size for a defined search granularity class has not been met. For example, search engine  142  may analyze a defined search granularity class to determine that a search granularity size for the defined search granularity class is 500 data records. At time T 1    220 , search engine  142  may only receive  300  data records for the defined search granularity class. After time T 1    220 , search engine  142  can assign to the defined search granularity class a search granularity pending status  204 . Accordingly, search granularity pending status  204  indicates that search engine  142  should continue processing synchronization data stream unit  202  and receive data records for the defined search granularity class until a determined search granularity size is met (e.g.,  500  data records). 
     In  FIG. 2B , search engine  142  determines that a determined search granularity size for a defined search granularity class is met. For example, search engine  142  may analyze a defined search granularity class to determine that a search granularity size for the defined search granularity class is 500 data records. At time T 2    230 , search engine  142  may receive  500  data records for the defined search granularity class. After time T 2    230 , search engine  142  can assign to the defined search granularity class a search granularity integrity status  206 . Accordingly, search granularity integrity status  206  indicates that search engine  142  can perform a received search request associated with the defined search granularity class. 
       FIG. 3  is a block diagram depicting synchronization data streams that are managed concurrently and associated search granularity statuses, in accordance with an embodiment of the present invention. In this embodiment, search engine  142  receives more than one search request from time T 0    320  to time T 4    380 . Search engine  142  may define more than one search granularity class from the more than one received search request, resulting in one search granularity status for each of the more than one defined search granularity classes. In another embodiment, more than one search granularity class can be defined from one received search request by search engine  142 , resulting a search granularity status for each of the more than one defined search granularity classes. Search engine  142  can assign a search granularity status for a respective search granularity class, based on a number of data records received for the respective search granularity class associated with one of synchronization data stream units  304 - 316 . In certain embodiments, a hash-code map may be implemented by search engine  142  to help manage multiple search granularity classes, as described in greater detail with regard to  FIG. 4 . In this exemplary embodiment, MFT system  140  is implemented, but it should be understood that, in other embodiments one or more computer systems can be implemented to manage synchronization data stream units  304 - 316 , as previously described. 
     From time T 0    320  to time T 3    360 , a portion of synchronization data stream unit  304  and a portion of synchronization data stream unit  306  are processed concurrently. Synchronization data stream unit  304  as well as synchronization data stream unit  306  can be associated with two subsets of search granularity classes having search granularity integrity status  302 A, search granularity integrity status  302 B, and search granularity integrity status  308 A, search granularity integrity status  308 B, respectively. Accordingly, a received search request associated with synchronization data stream unit  304  and/or synchronization data stream unit  306  can be performed by search engine  142 . 
     At time T 4    370 , synchronization data stream unit  312  and synchronization data stream unit  316  are processed at a same time. In this embodiment, at time T 5    380 , synchronization data stream unit  312  is assigned a search granularity status of search granularity integrity status  310 , indicating that a received search request associated with synchronization data stream unit  312  can be performed. Search engine  142  may determine that a determined granularity size for a defined search granularity class associated with synchronization data stream unit  316  is not met. Accordingly, search engine  142  determines that a received search request associated with the defined search granularity class cannot be performed and is assigned a search granularity status of search granularity pending status  314 . 
       FIG. 4  is a block diagram illustrating hash-code map  400  that is implemented by search engine  142  to help manage more than one search granularity class that are being processed at a same time. In certain instances, a received search request can be associated with a number of defined search granularity classes, each having a large granularity size. Search engine  142  can manage the received search request, by generating sub-sets for each of the defined search granularity classes, and implementing hash-code map  400  to manage each of the generated sub-sets. In this embodiment, a hash function can be applied to each of search granularity class  402 , search granularity class  404  and search granularity  406  to populate a table included in hash-code map  400 . Each of respective hash code can identify an associated synchronization data stream unit that is managed by MFT system  140 . For example, hash-code map  400  may be referenced to determine that synchronization data stream unit  403 , synchronization data stream unit  405 , and synchronization data stream unit  407  are associated with search granularity class  402 , search granularity class  404 , and search granularity class  406 , respectively. In this exemplary embodiment, MFT system  140  is implemented, but it should be understood that in other embodiments, one or more computer systems can implement hash-code map  400 , as previously described. 
       FIG. 5  is a flowchart illustrating operational steps for creating search index  144 , in accordance with an embodiment of the present invention. In one embodiment, a synchronization data stream has been previously initiated by MFT system  140 . In another embodiment, prior to initiating a synchronization data stream, a weight matrix may be implemented by MFT system  140  to initiate a synchronization data stream that is identified, as previously described. In general, search index  144  is generated in real-time, as a synchronization data stream is being managed a monitoring computer system, such as MFT system  140 . 
     Search index creation module  146  receives a synchronization data stream that is initiated by MFT system  140  (step  502 ). While search index creation module  144  receives the synchronization data stream, search index creation module  146  can analyze the received synchronization data stream to index data records of the synchronization data stream with respect to defined search granularity classes (step  504 ). Accordingly search index  144  can be referenced by search engine  142  to perform a received search request, as described in greater detail with regard to  FIG. 6 . 
       FIG. 6  is a flowchart illustrating operational steps for performing a search, in accordance with an embodiment of the present invention. Search engine  142  can receive a search request from target computer system  110  (step  602 ). After receiving a search request, search engine  142  defines a search granularity class that is associated with the received search request (step  604 ). 
     After a search granularity class is defined by search engine  142 , search engine  142  determines whether a granularity size for the defined search granularity class is met (decision  608 ). If, search engine  142  determines that the granularity size for the defined search granularity class is met (decision  608 , “Yes” branch), then search engine  142  performs the received search request that is associated with the defined search granularity class (step  610 ). In this embodiment, if the granularity size for the defined search granularity class is met, then the defined search granularity class is assigned a search granularity integrity status. If, search engine  142  determines that the granularity size for the defined search granularity class is not met (decision  608 , “No” branch), then search engine  142  determines whether no data records for the defined search granularity class in a synchronization data stream or indexed in search index  144  are received (decision  612 ). If, search engine  142  determines that no data records for the defined search granularity class are received (decision  612 , “Yes” branch), then search engine  142  performs the received search request that is associated with the defined search granularity class (step  610 ). If, search engine  142  determines that data records for the defined search granularity class are received, but do not meet a search granularity size for the defined search granularity class (decision  612 , “No” branch), then search engine  142  assigns a search granularity pending status to the defined search granularity class (step  614 ). In this instance, the identified search granularity continues to be processed until search engine  142  determines that the identified search granularity class is of a search granularity integrity status, or that the received search request is ready to be performed. 
       FIG. 7  is a block diagram of internal and external components of a computer system  700 , which is representative the computer systems of  FIG. 1 , in accordance with an embodiment of the present invention. It should be appreciated that  FIG. 7  provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. In general, the components illustrated in  FIG. 6  are representative of any electronic device capable of executing machine-readable program instructions. Examples of computer systems, environments, and/or configurations that may be represented by the components illustrated in  FIG. 7  include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, laptop computer systems, tablet computer systems, cellular telephones (e.g., smart phones), multiprocessor systems, microprocessor-based systems, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices. 
     Computer system  700  includes communications fabric  702 , which provides for communications between one or more processors  704 , memory  706 , persistent storage  708 , communications unit  712 , and one or more input/output (I/O) interfaces  714 . Communications fabric  702  can be implemented with any architecture designed for passing data and/or control information between processors (such as microprocessors, communications and network processors, etc.), system memory, peripheral devices, and any other hardware components within a system. For example, communications fabric  702  can be implemented with one or more buses. 
     Memory  706  and persistent storage  708  are computer-readable storage media. In this embodiment, memory  706  includes random access memory (RAM)  716  and cache memory  718 . In general, memory  706  can include any suitable volatile or non-volatile computer-readable storage media. Software is stored in persistent storage  708  for execution and/or access by one or more of the respective processors  704  via one or more memories of memory  706 . 
     Persistent storage  708  may include, for example, a plurality of magnetic hard disk drives. Alternatively, or in addition to magnetic hard disk drives, persistent storage  708  can include one or more solid state hard drives, semiconductor storage devices, read-only memories (ROM), erasable programmable read-only memories (EPROM), flash memories, or any other computer-readable storage media that is capable of storing program instructions or digital information. 
     The media used by persistent storage  708  can also be removable. For example, a removable hard drive can be used for persistent storage  708 . Other examples include optical and magnetic disks, thumb drives, and smart cards that are inserted into a drive for transfer onto another computer-readable storage medium that is also part of persistent storage  708 . 
     Communications unit  712  provides for communications with other computer systems or devices via a network (e.g., network  120 ). In this exemplary embodiment, communications unit  712  includes network adapters or interfaces such as a TCP/IP adapter cards, wireless Wi-Fi interface cards, or 3G or 4G wireless interface cards or other wired or wireless communication links. The network can comprise, for example, copper wires, optical fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. Software and data used to practice embodiments of the present invention can be downloaded through communications unit  712  (e.g., via the Internet, a local area network or other wide area network). From communications unit  712 , the software and data can be loaded onto persistent storage  708 . 
     One or more I/O interfaces  714  allow for input and output of data with other devices that may be connected to computer system  700 . For example, I/O interface  714  can provide a connection to one or more external devices  720 , such as a keyboard, computer mouse, touch screen, virtual keyboard, touch pad, pointing device, or other human interface devices. External devices  720  can also include portable computer-readable storage media such as, for example, thumb drives, portable optical or magnetic disks, and memory cards. I/O interface  714  also connects to display  722 . 
     Display  722  provides a mechanism to display data to a user and can be, for example, a computer monitor. Display  722  can also be an incorporated display and may function as a touch screen, such as a built-in display of a tablet computer. 
     Referring now to  FIG. 8 , illustrative cloud computing environment  50  is depicted. As shown, cloud computing environment  50  comprises one or more cloud computing nodes  10  with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone  54 A, desktop computer  54 B, laptop computer  54 C, and/or automobile computer system  54 N may communicate. Nodes  10  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  50  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  54 A-N shown in  FIG. 8  are intended to be illustrative only and that cloud computing nodes  10  and cloud computing environment  50  can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). 
     Referring now to  FIG. 9 , a set of functional abstraction layers provided by cloud computing environment  50  ( FIG. 8 ) is shown. It should be understood in advance that the components, layers, and functions shown in  FIG. 9  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: 
     Hardware and software layer  60  includes hardware and software components. Examples of hardware components include: mainframes  61 ; RISC (Reduced Instruction Set Computer) architecture based servers  62 ; servers  63 ; blade servers  64 ; storage devices  65 ; and networks and networking components  66 . In some embodiments, software components include network application server software  67  and database software  68 . 
     Virtualization layer  70  provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers  71 ; virtual storage  72 ; virtual networks  73 , including virtual private networks; virtual applications and operating systems  74 ; and virtual clients  75 . 
     In one example, management layer  80  may provide the functions described below. Resource provisioning  81  provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing  82  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  83  provides access to the cloud computing environment for consumers and system administrators. Service level management  84  provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment  85  provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA. 
     Workloads layer  90  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  91 ; software development and lifecycle management  92 ; virtual classroom education delivery  93 ; data analytics processing  94 ; transaction processing  95 ; and synchronization data stream searching environment  96 . 
     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. 
     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. 
     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. 
     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 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. 
     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. 
     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. 
     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. 
     The flowchart and block diagrams in  FIGS. 1-9  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  FIGS. 1-9 . 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. 
     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. 
     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. 
     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. 
     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 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. 
     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. 
     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. 
     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. 
     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. 
     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. 
     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. 
     Characteristics are as follows: 
     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. 
     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). 
     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). 
     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. 
     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. 
     Service Models are as follows: 
     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 e-mail). 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. 
     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. 
     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). 
     Deployment Models are as follows: 
     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. 
     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. 
     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. 
     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). 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. 
     The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The terminology used herein was chosen to best explain the principles of the embodiment, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.