Patent Publication Number: US-10785598-B2

Title: Cognitive geofence updates

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation of U.S. patent application Ser. No. 16/598,133 filed Oct. 10, 2019, entitled “Cognitive Geofence Updates,” which is incorporated by reference herein in its entirety, and which is a continuation of U.S. patent application Ser. No. 15/982,008 filed May 17, 2018, entitled “Cognitive Geofence Updates,” which is incorporated by reference herein in its entirety, and which is a continuation of U.S. patent application Ser. No. 15/876,468, filed Jan. 22, 2018, entitled, “Cognitive Geofence Updates,” which is incorporated by reference herein in its entirety. 
    
    
     BACKGROUND 
     Location based services (LBS) are software services that use location data to control functionality of computer systems LBS information services have a number of uses, e.g. in social networking, entertainment, security, and in a plurality of additional applications. LBS services employ location services for locating mobile computer systems. Location services can incorporate a variety of different locating service technologies such as the Global Positioning System (GPS), cellular network locating technologies, and WI-FI based locating technologies, and other technologies. One example of an LBS is a location based messaging services wherein notifications and other messages to users can be in dependence on the respective locations of the users. 
     Data structures have been employed for improving operation of computer system. A data structure refers to an organization of data in a computer environment for improved computer system operation. Data structure types include containers, lists, stacks, queues, tables and graphs. Data structures have been employed for improved computer system operation e.g. in terms of algorithm efficiency, memory usage efficiency, maintainability, and reliability. 
     Artificial intelligence (AI) refers to intelligence exhibited by machines. Artificial intelligence (AI) research includes search and mathematical optimization, neural networks and probability. Artificial intelligence (AI) solutions involve features derived from research in a variety of different science and technology disciplines ranging from computer science, mathematics, psychology, linguistics, statistics, and neuroscience. 
     SUMMARY 
     Shortcomings of the prior art are overcome, and additional advantages are provided, through the provision, in one aspect, of a method. The method can include, for example: examining data of breaches of a geofence by client computer devices to determine respective positions of the breaches; establishing an updated location for the geofence using the determined respective positions of the breaches; updating a location of the geofence so that the location of the geofence is the updated location; obtaining data of a client computer breach of the geofence at the updated location; and providing one or more output in response to the obtaining data of a client computer breach of the geofence at the updated location. 
     In another aspect, a computer program product can be provided. The computer program product can include a computer readable storage medium readable by one or more processing circuit and storing instructions for execution by one or more processor for performing a method. The method can include, for example: examining data of breaches of a geofence by client computer devices to determine respective positions of the breaches; establishing an updated location for the geofence using the determined respective positions of the breaches; updating a location of the geofence so that the location of the geofence is the updated location; obtaining data of a client computer breach of the geofence at the updated location; and providing one or more output in response to the obtaining data of a client computer breach of the geofence at the updated location. 
     In a further aspect, a system can be provided. The system can include, for example a memory. In addition, the system can include one or more processor in communication with the memory. Further, the system can include program instructions executable by the one or more processor via the memory to perform a method. The method can include, for example: examining data of breaches of a geofence by client computer devices to determine respective positions of the breaches; establishing an updated location for the geofence using the determined respective positions of the breaches; updating a location of the geofence so that the location of the geofence is the updated location; obtaining data of a client computer breach of the geofence at the updated location; and providing one or more output in response to the obtaining data of a client computer breach of the geofence at the updated location. 
     Additional features are realized through the techniques set forth herein. Other embodiments and aspects, including but not limited to methods, computer program product and system, are described in detail herein and are considered a part of the claimed invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       One or more aspects of the present invention are particularly pointed out and distinctly claimed as examples in the claims at the conclusion of the specification. The foregoing and other objects, features, and advantages of the invention are apparent from the following detailed description taken in conjunction with the accompanying drawings in which: 
         FIG. 1  depicts a system having a manager system, client computer devices, and an administrator client computer device according to one embodiment; 
         FIG. 2  is a flowchart illustrating a method for performance by a manager system according to one embodiment; 
         FIG. 3  is a flowchart illustrating a method for performance by a manager system according to one embodiment; 
         FIG. 4  is a flowchart illustrating a method for performance by a manager system interoperating with other components according to one embodiment; 
         FIG. 5  depicts an administrator user interface according to one embodiment; 
         FIG. 6  depicts breach positions at different perimeter locations of a geofence over the course of different time periods according to one embodiment; 
         FIG. 7  depicts geofence breach determination data and regression analysis thereof according to one embodiment; 
         FIG. 8  depicts a geofence migrating throughout an environment according to one embodiment; 
         FIG. 9  depicts a computing node according to one embodiment; 
         FIG. 10  depicts a cloud computing environment according to one embodiment; and 
         FIG. 11  depicts abstraction model layers according to one embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     System  100  for use in supporting location based messaging services is shown in  FIG. 1 . System  100  can include manager system  110  having an associated data repository  112 , venue system  120 , administrator computer device  125 , a plurality of client computer devices  130 A- 130 Z, and social media system  140 . Manager system  110 , venue system  120 , administrator computer device  125 , a plurality of client computer devices  130 A- 130 Z, and social media system  140  can be in communication with one another via network  180 . System  100  includes numerous devices, which may be computing node based devices, connected by a network  180 . Network  180  may be a physical network and/or a virtual network. A physical network can be, for example, a physical telecommunications network connecting numerous computer nodes or systems, such as computer servers and computer clients. A virtual network can, for example, combine numerous physical networks or parts thereof into a logical virtual network. In another example, numerous virtual networks can be defined over a single physical network. 
     In one embodiment manager system  110  can be external to venue system  120  social media system  140  and to each of the one or more client computer device  130 A- 130 Z. In one embodiment manager system  110  can be co-located with venue system  120  and/or social media system  140 . In one embodiment manager system  110  can be co-located with one or more client computer device  130 A- 130 Z. 
     Referring further to  FIG. 1 , venue system  120  can be located in venue  122  that is delimited by venue geographical border  124  that specifies the geographical coordinate area occupied by venue  122 . In one embodiment, an organizational entity that operates manager system  110  can be in common with the organizational entity that operates venue system  120  and venue  122 . Venue  122  can be a retail or restaurant establishment venue in one embodiment. Venue system  120  can be disposed in venue  122  defined by geographical boundary  124 . Client computer devices  130 A- 130 Z can be mobile computer devices, moveable between locations, internal and external to venue  122 , and thus are shown in  FIG. 1  as being partially disposed within geographical boundary  124  and partially disposed external to geographical boundary  124 . Client computer devices  130 A- 130 Z can be wireless computer devices that can be connected to network  180  by alternative radio communication protocols. For example, client computer devices  130 A- 130 Z can connect to network  180  by connection nodes  156 . Connection nodes  156  can be connection nodes that facilitate connection to a cellular communication network. Client computer devices  130 A- 130 Z can also be connected to network  180  via connection nodes  126 . Connection nodes  126  can be provided by IEEE 802.11 access points of a WIFI wireless network provided by an operator of venue system  120 , in which operator can be the operator of venue  122  and manager system  110 . 
     In one embodiment, each client computer device  130 A- 130 Z can be associated to a certain user. In one embodiment, each user of system  100  is a registered user of a retail vendor that operates a plurality of venues such as venue  122 . Users having records stored data repository  112  can be registered users of manager system  110  and of an enterprise that operates venue  122  e.g. can be customer loyalty card holders of the vendor who receive customer loyalty cards in exchange for data regarding themselves. 
     Each of the different client computer devices  130 A- 130 Z can be associated to a different user. Regarding one or more client computer device  130 A- 130 Z, a computer device of one or more client computer device  130 A- 130 Z in one embodiment can be a computing node device provided by a client computer, e.g. a mobile device, e.g. a smartphone or tablet, a laptop, smartwatch or PC that runs one or more program, e.g. including a web browser for opening and viewing web pages. 
     Social media system  140  can include a collection of files, including for example, HTML files, CSS files, image files, and JavaScript files. Social media system  140  can be a social website such as FACEBOOK® (Facebook is a registered trademark of Facebook, Inc.), TWITTER® (Twitter is a registered trademark of Twitter, Inc.), LINKEDIN® (LinkedIn is a registered trademark of LinkedIn Corporation), or INSTAGRAM® (Instagram is a registered trademark of Instagram, LLC). Computer implemented social networks incorporate messaging systems that are capable of receiving and transmitting messages to client computers of participant users of the messaging systems. Messaging systems can also be incorporated in systems that that have minimal or no social network attributes. A messaging system can be provided by a short message system (SMS) text message delivery service of a mobile phone cellular network provider, or an email delivery system. Manager system  110  can include a messaging system in one embodiment. 
     Manager system  110  can run various processes including preparation and maintenance process  111 , Natural Language Processing (NLP) process  113 , geofence deployment process  114 , examining process  115 , establishing process  116 , updating process  117 , notifying process  118 , and machine learning process  119 . 
     Data repository  112  can store various data, such as location data specifying history of locations of client computer devices  130 A- 130 Z, breach occurrence data specifying occurrences of geofence breaches by client computer devices  130 A- 130 Z, decision data structures for use in providing artificial intelligence (AI) decisions, and geofence results data specifying a history of geofences deployed by system  100  and performance results associated therewith. 
     Manager system  110  can run geofence deployment process  114  to deploy a geofence. Manager system  110  running geofence deployment process  114  can deploy a geofence based on administrator user defined configuration data that can be defined using an administrator user interface. Using an administrator user interface, an administrator user can enter such configuration data as location of a geofence, timing of a geofence, size of a geofence, and shape of a geofence. In one embodiment an administrator user can specify geofence location to encompass a venue, such as venue  122 . A geofence location can be defined by a geofence perimeter. Geofence configuration data entered by an administrator user can also include geofence events, such as geofence breaches and dwells, as well as outputs associated with the geofence events. An output associated with a geofence can include, e.g. one or more notification output and/or one or more process output. A notification in one embodiment, can include e.g. a text based notification prompting a user to travel to venue  122  upon breaching a geofence encompassing venue  122 . Such notification can include, e.g. a promotion regarding a product available at venue  122 . 
     Manager system  110  running geofence deployment process  114 , in one embodiment can deploy a geofence. Manager system  110  running geofence deployment process  114  to deploy geofence can include manager system  110  sending geofence configuration data to geofence breach determination processes run by respective client computer devices  130 A- 130 Z. Thus, manager system  110  running geofence deployment process  114  can support distributed local geofence breach determination processes run locally on respective client computer devices  130 A- 130 Z. 
     Manager system  110  running examining process  115  can examine breach data respecting breaches of a geofence by client computer devices of client computer devices  130 A- 130 Z. Manager system  110  running examining process  115  can examine breach data respecting breaches of a geofence by client computer devices of client computer devices  130 A- 130 Z. Breach data can include, e.g. breach occurrence data that can specify a computer device identifier that has breached a geofence as well as a timestamp of the breach. Breach data can also include location data of a breach. For determining location data of a breach, manager system  110  can use the client computer device identifier specified within breach occurrence data to lookup location data of a client computer device specified by an identifier at the time of a breach occurrence and can use that data to determine a breach position. A breach position herein can specify position on a geofence perimeter defining a geofence that which a breach occurred. 
     Manager system  110  running examining process  115  can examine breach data for a plurality of breaches of a geofence by a plurality of client computer devices over a period of time. Manager system  110  running examining process  115  can determine breach position data for a plurality of breaches of a period of time by a plurality of client computer devices of client computer devices  130 A- 130 Z. Manager system  110  running examining process  115  can perform additional processes such as classifying breach positions of breaching client computer devices into one of a plurality of available candidate breach positions, and can also predict future breach positions of a geofence by client computer devices of client computer devices  130 A- 130 Z. 
     Manager system  110  running establishing process  116  can establish an updated location for a geofence. Manager system  110  running establishing process  116  can update a location of a deployed geofence. Manager system  110  running establishing process  116  can update a location of a deployed geofence, so that the geofence is at a location predicted to increase a number of breaches of the geofence. Manager system  110  running establishing process  116  can determine an updated location for a geofence based on a region of the geofence predicted to have the largest number of breaches. 
     Embodiments herein recognize that updating a location of a geofence to a new location in a direction from a prior location that is based on a predicted geofence perimeter region of highest number of breaches can increase the number of geofence breaches. Manager system  110  running establishing process  116  can qualify the running of examining process  115  based on one or more criterion being satisfied. The one or more criterion being satisfied can be the criterion that a geofence subject to examining is an underperforming geofence having less than a targeted number of breaches. Embodiments herein recognize that geofences sometimes underperform and produce less breaches than anticipated. Accordingly, features are provided herein so that a geofence can automatically update its location to produce an increased number of breaches so that geofence breaches can more accurately track a designed number of breaches targeted at the time of initial deployment of the geofence. 
     Manager system  110  running updating process  117  can update a location of a deployed geofence so that the deployed geofence is at an updated location established by manager system  110  running establishing process  116 . Manager system  110  running updating process  117  can send location change information to client computer devices of client computer devices  130 A- 130 Z. Manager system  110  running updating process  117  can send location change information to breach determination processes running locally on client computer devices of client computer devices  130 A- 130 Z, so that respective client computer devices of client computer devices  130 A- 130 Z can locally perform geofence breach determinations using the updated geofence location determine by manager system  110  running establishing process  116 . 
     Manager system  110  running notifying process  118  can send notifications to client computer devices of client computer devices  130 A- 130 Z that have breached a geofence. In one embodiment respective client computer devices of client computer devices  130 A- 130 Z can locally on their own respective hardware using locally distributed machine logic, determine that a geofence breach has occurred and can send a communication to manager system  110  specifying that a geofence breach has occurred. In response to receipt of a geofence breach occurrence communication, manager system  110  running notifying process  118  can send a notification to the breaching client computer device. The notification can include, e.g. a text based notification, e.g. specifying a promotion prompting a user of the client computer device to travel to a venue encompassed within a geofence, defined by a geofence perimeter. 
     Manager system  110 , running machine learning process  119  can update one or more process run by manager system  110  based on obtained data to improve and accuracy and/or reliability of the one or more process. In one embodiment, manager system  110  running establishing process  116  can use a decision data structure that maps predicted geofence breach positions to geofence location change information defining an updated geofence location. Such a decision data structure can have parameter values, such as parameter values specifying decision thresholds and/or distance units. Manager system  110  in one embodiment can run a plurality of instances of such a decision data structure, each instance for a different geofence subject to examining establishing and updating processes herein. For each instance of the decision data structure, manager system  110  can vary such threshold parameter values and distance unit parameter values within valid ranges. Manager system  110  running machine learning process  119  can update the threshold value and/or distance value parameters of the different instances of the decision data structure. Manager system  110  can monitor performance of the different geofences subject to establishing and updating using the different data structures and based on the performance monitoring can update the parameters of the decision data structures so that the parameters values over time converge toward values that are in common with geofences that are determined to be the best performing geofences according to one or more criterion. 
     Manager system  110  can run preparation and maintenance process  111  to populate and maintain data of data repository  112  for use by various processes run by manager system  110  including e.g. predicting examining process  115 . 
     Manager system  110  can run NLP process  113  to process data for preparation of records that are stored in data repository  112  and for other purposes. Manager system  110  can run a Natural Language Processing (NLP) process  113  for determining one or more NLP output parameter of a message. NLP process  113  can include one or more of a topic classification process that determines topics of messages and output one or more topic NLP output parameter, a sentiment analysis process which determines sentiment parameter for a message, e.g. polar sentiment NLP output parameters, “negative,” “positive,” and/or non-polar NLP output sentiment parameters, e.g. “anger,” “disgust,” “fear,” “joy,” and/or “sadness” or other classification process for output of one or more other NLP output parameters e.g. one of more “social tendency” NLP output parameter or one or more “writing style” NLP output parameter. 
     By running of NLP process  113  manager system  110  can perform a number of processes including one or more of (a) topic classification and output of one or more topic NLP output parameter for a received message (b) sentiment classification and output of one or more sentiment NLP output parameter for a received message or (c) other NLP classifications and output of one or more other NLP output parameter for the received message. 
     Topic analysis for topic classification and output of NLP output parameters can include topic segmentation to identify several topics within a message. Topic analysis can apply a variety of technologies e.g. one or more of Hidden Markov model (HMM), artificial chains, passage similarities using word co-occurrence, topic modeling, or clustering. Sentiment analysis for sentiment classification and output of one or more sentiment NLP parameter can determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. The attitude may be the author&#39;s judgment or evaluation, affective state (the emotional state of the author when writing), or the intended emotional communication (emotional effect the author wishes to have on the reader). In one embodiment sentiment analysis can classify the polarity of a given text at the document, sentence, or feature/aspect level—whether the expressed opinion in a document, a sentence or an entity feature/aspect is positive, negative, or neutral. Advanced sentiment classification can classify beyond a polarity of a given text. Advanced sentiment classification can classify emotional states as sentiment classifications. Sentiment classifications can include the classification of “anger,” “disgust,” “fear,” “joy,” and “sadness.” 
     Data repository  112  can include location data area  2121  which can include historical data on locations visited by users of system  100 . As users move throughout an environment their movement can be traced and logged into location data area  2121 . In one embodiment, location data area  2121  can include a table associating users within their respective locations (e.g. given in coordinates) and each location can be associated with a timestamp. Thus, manager system  110  is able to perform a variety of useful analyses, e.g. can ascertain a performance of a hypothetical geofence had a hypothetical geofence been previously deployed at a certain previous point in time. The performance of a hypothetical geofence can be ascertained in terms of events associated with a geofence, e.g. a number of breaches or a number of dwells (a user remaining within a geofence for more than a threshold period of time). For providing of location data that specifies a location of users of system  100 , system  100  can be configured to provide locating services. Locating services can be e.g. control plane based, self-reported based, local range based or a combination of the noted types. In one embodiment, locating services provided by system  100  can locate a computer device of client computer devices  130 A- 130 Z using e.g. GPS based locating services, located services based on processing of signals received by connection nodes  156  (cellular network), locating services based on processing of signals received by connection nodes  126  (LAN) or a combination of such services. 
     Data repository  112  can include breach occurrence data area  2122 . On determination that a geofence breach has occurred, respective client computer devices of client computer devices  130 A- 130 Z can send communications to manager system  110  with breach occurrence data. Breach occurrence data can include, e.g. an identifier of the breaching client computer device of client computer devices  130 A- 130 Z as well as a timestamp of the breach. Respective client computer devices of client computer devices  130 A- 130 Z can run respective breach determination programs to determine that a breach has occurred. A breach can be determined to have occurred when a client computer device enters an interior of a geofence defined by a geofence perimeter. On receipt of breach occurrence data from client computer devices of client computer devices  130 A- 130 Z manager system  110  responsively can store the breach occurrence data into breach occurrence data area  2122  of data repository  112 . 
     Data repository  112  can include decision data structures area  2123 . Within decision data structures area  2123 , data repository  112  can store decision data structures. In one embodiment, there can be stored in decision data structures area  2123 , a machine logic artificial intelligence (AI) decision data table that maps sections of a geofence perimeter predicted to have a highest number of breaches to updated geofence locations defined by location change information. 
     Data repository  112  can store in geofence results area  2124 , data respecting historical geofences deployed by manager system  110 , and results associated therewith. Results data can include, e.g. data on a number of breaches, data on the accuracy of past geofences, e.g. in terms of a geofence&#39;s ability to yield breaches according to a count that is in accordance with a predicted count of breaches. 
       FIG. 2  is a flowchart illustrating coordination of processes that can be performed by manager system  110  of  FIG. 1 , in accordance with one or more embodiments set forth herein. 
     At block  210 , manager system  110  can run preparation and maintenance process  111  to populate prepare and maintain various data of data repository  112  including data of locations areas  2121 - 2124 . Manager system  110  can run preparation and maintenance process  111  iteratively until process  111  is terminated at block  212 . 
     At block  220 , manager system  110  can run examining process  115  to determine geofence breach positions. For support of running of examining process  115  iteratively, manager system  110  can be running e.g. NLP process  113 , establishing process  116 , updating process  117 , notifying process  118 , and/or machine learning process  119  iteratively. Manager system  110  can run examining process  115  until examining process  115  is terminated at block  222 . Manager system  110  can run preparation and maintenance process  111  and examining process  115  concurrently and can run each of process  111  and process  115  iteratively. 
     A method  300  for performance by manager system  110  is illustrated with reference to  FIG. 3 . At block  310 , manager system  110  can perform examining data of breaches of a geofence by client computer devices to determine respective positions of the breaches. At block  320 , manager system  110  can perform establishing an updated location for the geofence using the determined respective positions of the breaches. At block  330 , manager system  110  can perform updating a location of the geofence so that the location of the geofence is the updated location. At block  340 , manager system  110  can perform obtaining data of a client computer breach of the geofence at the updated location. At block  350 , manager system  110  can perform providing one or more output in response to the obtaining data of a client computer breach of the geofence at the updated location. 
     A specific example of method  300  is set forth in reference to the flowchart of  FIG. 4  illustrating a specific example of method  300  from the perspective of manager system  110 , data repository  112 , administrator computer device  125 , and client computer devices  130 A- 130 Z. 
     At block  1301 , client computer devices  130 A- 130 Z can send registration request data for receipt by manager system  110  at block  1101 . Users of client computer devices  130 A- 130 Z can register their respective client computer devices  130 A- 130 Z to participate in a location based messaging services, in which messages are delivered to computer devices of client computer devices  130 A- 130 Z based on a location of the computer devices. 
     One example is a customer support service, wherein users of client computer devices  130 A- 130 Z are customers of an entity such as a retail or restaurant organization having numerous venues throughout a geographical area, may wish to better communicate with its customers by way of a location based messaging service. In one common use case, the service may recognize that a customer has reached a location in proximity with the venue. Based on such recognition the service may notify the customer of a special offer available at the venue, to entice the customer to travel to the venue. On reaching the venue of a retail or restaurant organization may send a location based message to the customer to entice the customer to travel to a specific location within the venue. An administrator user can define parameters of a location based messaging service using an administrator user interface such as administrator user interface  500  ( FIG. 5 ) as set forth herein. Administrator user interface  500  can be manually operated user interfaces displayed on a display of an administrator computer device  125 . Registration request data sent at block  1301  for receipt at block  1101  can include, e.g. name and contact information of a user of a computer device as well as other information in facilitating messaging of the user by the manager system  110 , e.g. messaging service, account information to allow messages to be received e.g. text based notifications to be received by a customer. 
     On receipt of registration request data at block  1101 , manager system  110  can register a user and can send at block  1102  location based messaging software to client computer devices  130 A- 130 Z, from which registration requests have been received. Location based messaging software, received by client computer devices  130 A- 130 Z at block  1302 , can include software that allows respective client computer devices  130 A- 130 Z to determine, locally on the respective computing nodes, that a geofence event has occurred. Geofence events can include e.g. geofence breaches, geofence area dwells, and geofence expirations. A breach can be regarded to have occurred when a client computer device  130 - 130 Z crosses a geofence perimeter when travelling along a path from an exterior of a geofence perimeter to an interior of a perimeter. A dwell can be regarded to have when a client computer device  130 A- 130 Z if it remains within a geofence area for more than a threshold period of time. With a location based messaging software installed on a computer device, a computer device is able to determine that an event has occurred. On the determining that an event has occurred, a certain computer device of client computer devices  130 A- 130 Z can send a notification to manager system  110 , which can then respond by providing one or more output, e.g. such as an output notification to the certain computer device. 
     Embodiments herein recognize that advantages can accrue by distributing breach determination software to client computer devices  130 A- 130 Z (block  1102 ) so that client computer devices  130 A- 130 Z are enabled to determine, locally on their respective hardware platforms, geofence breaches once geofence information is received (block  1304 ). In one aspect, the determination of geofence breaches locally, at client computer devices  130 A- 130 Z can reduce power consumption to increase battery life of client computer devices  130 A- 130 Z. Resource consumption associated with geofence breach determinations can be less than resource consumption levels associated with an alternative scheme in which location data is iteratively transmitted externally to manager system  110  for processing for breach determination externally from client computer devices  130 A- 130 Z. The determination of geofence breaches locally, by respective client computer devices  130 A- 130 Z can reduce wireless data traffic in an environment, thereby increasing available bandwidth, which is of increased importance in bandwidth limited 5G and Internet of Things (TOT) environment. The determination of geofence breaches locally by respective client computer devices  130 A- 130 Z can increase determination speed and reduce latency relative to latency associated with an alternative scheme in which geofence breaches are determined remotely by manager system  110 . The determination of geofence breaches locally, by client computer devices  130 A- 130 Z can also increase determination accuracy. In an alternative embodiment where geofence breach determination is performed remotely, e.g. on manager system  110  where manager system  110  is remote from client computer devices  130 A- 130 Z, a determination might be made based on a past location of a client computer device that is no longer accurate. Also, geofence determinations can be dependent on network connectivity. In some use cases, manager system  110  can send with geofence information at block  1111  to a certain computer device, textual message data, specifying content of a textual based message that can be output by the certain computer device responsive to a breach being detected. 
     Embodiments herein recognize that while advantages associated with client distributed logic for geofence event determination can be substantial, the advantages may not be yielded if a deployed geofence is not accurately deployed. Re-deployment can create risks and resource consumption that outweigh the benefits of client distributed geofence event determination logic. Embodiments herein set forth to provide updates to geofence locations wherein geofence breach determinations are made using distributed geofence breach determination logic running locally on client computer devices of client computer devices  130 A- 130 Z. Embodiments herein can update a distributed geofences using reduced bandwidth and processing resources and can perform location updates of a distributed geofences so that updates can be implemented asynchronously between computer devices of client computer devices  130 A- 130 Z. Embodiments can process and store data respecting a geofence as a logically constant geofence notwithstanding location changes of the geofence and differentiated locations of the geofence between client computer devices of client computer devices  130 A- 130 Z e.g. as a result of asynchronous updating of a geofence location between client computer devices, and various machine logic rules that impose restrictions on locations of a geofence. 
     At block  1303  client computer devices  130 A- 130 Z can send location data reporting their current location for receipt by manager system  110  at block  1103 . The sending at block  1303  can be iterative and can be ongoing concurrently with remaining processes. Manager system  110  can additionally or alternatively be iteratively receiving location data reporting the respective locations of computer devices from other data sources, e.g. sources associated with a cellular and/or LAN based locating service. On receipt of location data at block  1103  manager system  110  can send the received location data to data repository  112  for receipt by data repository  112  at block  1121  and storage by data repository  112  into location data area  2121 . Sending and receiving for storage at blocks  1104  and  1121  respectively can be performed iteratively. 
     At block  1261 , administrator computer device  125  can send configuration data for receipt by manager system  110  at block  1105 . Configuration data sent at block  1261  can include data that configures manager system  110  to output one or more location based message. The administrator user interface  500 , for use by an administrator user establishing location based messaging service configuration data as shown in  FIG. 5 . Using area  502 , an administrator can specify a start time and a stop time of a location based messaging service. 
     Using area  506 , an administrator user using administrator user interface  500  can specify a location of a geofence for deployment. A geofence location can be defined by a geofence perimeter. The geofence that is specified can include e.g. a venue external geofence or a venue internal geofence. A venue internal geofence herein can be referred to as a “zone”. 
     A geofence having a location specified can be depicted in area  600  of administrator user interface  500 . Area  600  can depict a geofence perimeter  602  defining a geofence as specified by an administrator user using administrator user interface  500 . Area  600  can also include depictions of features such as roadways as shown included in an environment of a geofence. The geofence can be specified to have a perimeter such that the perimeter  602  encompasses a location of interest  601  which location of interest  601  can specify a location of interest such as a venue  122  ( FIG. 1 ). Area  600  can also depict a center  1602  of a geofence. 
     Using area  510 , an administrator user can specify an action to be performed on the occurrence of an event. Geofences in one embodiment can specify a two-dimensional area determined by a perimeter e.g. depicted by perimeter  602 . The one or more action can include e.g. a notification and/or a process. A notification can include a text based message sent via a messaging system to a client computer device, e.g. upon an occurrence of a specified geofence event. An action can include an automated process e.g. a machine learning process in which performance of system  100  is monitored e.g. using one or more sensor such as a radio receiver for use in obtaining location data. A specified notification can be a notification to prompt a user of a computer device to travel to a location of a depicted location of interest  601  such as a venue  122  ( FIG. 1 ). The notification can include e.g. a text based promotion of a product available at venue  122  ( FIG. 1 ). 
     Using area  514 , an administrator user can specify a trigger condition. A trigger condition can be e.g. an event that triggers the providing of one or more output. A trigger condition can include e.g. a client computer device of client computer devices  130 A- 130 Z breaching a geofence and/or a dwell event wherein the client computer device remains within an area of a geofence for more than a threshold period of time. 
     For purposes of illustration, geofences herein can be symmetrical and circular. In the case of a circle shaped geofence a geofence location can be provided by a center (e.g. represented by  1602 ) and a radius which defines a perimeter (e.g. represented by perimeter  602 ) that defines a geofence. However, it will be noted that candidate geofences herein can be defined by perimeters of any shape. 
     Manager system  110  at block  1106  can determine whether configuration data has been received defining a new geofence and if no geofence defining data has been received, manager system  110  can iteratively perform the loop depicted at block  1105 - 1106  to wait for receipt of geofence defining configuration data defined by an administrator user using an administrator user interface  500 . On receipt of geofence defining configuration data at block  1106 , manager system  110  can proceed to deploy the defined geofence. Manager system  110  at block  1106  on receipt of geofence defining configuration data and to deploy an administrator defined geofence, can proceed to block  1107  to send geofence data for receipt by client computer devices of client computer devices  130 A- 130 Z at block  1304 . The geofence data sent to client computer devices  130 A- 130 Z at block  1107  for deployment of a geofence can include geofence data of the geofence configuration data received at block  1105 . Geofence data sent at block  1107  by manager system  110  can include geofence location data in the case of a circular geofence, geofence location data can be specified by a center point of the geofence and a radius of the geofence. Manager system  110  in one embodiment at block  1107 , can send to client computer devices  130 A- 130 Z geofence data including geofence location defining data provided by a geofence center point and a radius. Based on administrator user defined configuration data in one embodiment, a geofence can be specified to be at a location that encompasses venue  122  ( FIG. 1 ). 
     At block  1107  manager system  110  can send geofence data to geofence breach determination processes running on client computer devices  130 A- 130 Z so that on receipt of the geofence data at block  1304 , the respective client computer devices  130 A- 130 Z can be enabled to perform geofence breach determination based on the geofence location defined by the geofence data sent at block  1107 . 
     Referring again to the flowchart of  FIG. 4 , client computer devices  130 A- 130 Z, at block  1305  can determine if a geofence deployed locally based on data received at block  1304 , has been breached. Block  1305  is depicted in  FIG. 4  in double-lined format to indicate that block  1305  can be performed separately and contemporaneously at each computer device of client computer devices  130 A- 130 Z. On the determination that a breach has occurred, a computer device, e.g. computer device  130 A detecting that a breach has occurred, can send a breach occurrence communication at block  1306  for receipt by manager system  110  at block  1112  indicating that a breach has occurred. 
     Responsively, manager system  110  can provide one or more output at block  1109 . The one or more output can include, e.g. a notification to the computer device, e.g. computer device  130 A for receipt by computer device  130 A at block  1307 . The notification can include e.g. a promotional message prompting a user to travel to a location of interest such as location of interest  601  depicted in area  600  of administrator user interface  500  ( FIG. 5 ), e.g. a location of a venue  122  ( FIG. 1 ) within a geofence that has been breached (e.g. where the geofence is delimited by a perimeter encompassing and spaced apart from a venue). The one or more output provided at block  1109  can include one or more output other than a notification output. The output can include, e.g., a communication to activate a process e.g. a process of machine learning process  119 . 
     Manager system  110  at block  1110  can determine if there has been an expiration of a geofence time period of interest. For performing examining of geofence breach data in one embodiment, manager system  110  can divide a geofence activation period in which a geofence is active and to time periods of interest. Time periods in one embodiment can be arbitrarily selected, e.g. can include time periods of 10 minutes, 1 hour, 5 hours, or a time period in dependence on an activation period of a geofence. For example, by machine logic rule a time period of interest can be automatically selected to be a time period equal to 1/M (e.g. 1/10 or 1/100) of a total activation period for a geofence. Time periods can be established by administrator defined configuration data defined using administrator user interface  500  ( FIG. 5 ). If the time period of interest is determined not to have expired at block  1110 , manager system  110  can proceed to perform the loop indicated by blocks  1108 ,  1109 , and  1110  until the time period expiration condition is satisfied. Whereupon manager system  110  can proceed to block  1111  to perform examining of geofence breaches, as set forth herein. 
     Manager system  110  performing examining at block  1111  in one embodiment is described further in reference to illustrative  FIGS. 6 and 7 . Referring to  FIG. 6 ,  FIG. 6  depicts geofence breaches by different computer devices with respect to a deployed geofence, deployed at blocks  1107  and  1304  defined by perimeter  602 , over the course of various time periods of interest, namely, through the time periods of interest T=T 1  through T=T 7  with breaches during the time periods of interest T=T 1 , T=T 6 , and T=T 7  being depicted in  FIG. 6 . 
     Referring to  FIG. 6 , the geofence defined by perimeter  602  labeled T=T 1  depicts breaches of the geofence during a first period of interest T 1  whereas, the geofence defined by perimeter  602  labeled T=T 6  depicts breaches of the geofence during a sixth period of interest T 6  refers and the geofence defined by perimeter  602  labeled T=T 7  depicts breaches of the geofence during a seventh period of interest T 7 . 
     In the example described in reference to  FIG. 6 , manager system  110  can determine that there are eleven (11) breaches of the geofence defined by perimeter  602  during time period on interest T 1 , thirteen (13) breaches of the geofence defined by perimeter  602  during time period of interest T 6 , and fourteen (14) breaches of the geofence defined by perimeter  602  during the time period of interest T 7 . Manager system  110  can also similarly determine breaches of the geofence defined by perimeter  602 , during the intermediary periods T 2 -T 5  not depicted in  FIG. 6 . 
     As depicted in  FIG. 6 , manager system  110  can determine a position at which a client computer device of client computer devices  130 A- 130 Z breaches a geofence. That is, in reference to  FIG. 6 , there are depicted X on perimeter  602  defining a geofence. The illustrated “X” at a specific position on perimeter  602  depicts a position in physical space in which a client computer device of client computer devices  130 A- 130 Z breaches the geofence defined by perimeter  602 . Embodiments herein recognize that the specific position at which a client computer device of client computer devices  130 A- 130 Z depict a breach of geofence can be recorded and advantageously used. For determining a position at which client computer device breaches a geofence defined by a perimeter, such as perimeters  602 , manager system  110  at block  1111  can examine recorded data of data repository  112 . More specifically, manager system  110  for determining position of a geofence breach can examine breach occurrence data of breach occurrence data area  2122  in combination with location data of location data area  2121 . As set forth herein, breach occurrence data can specify a client computer device identifier together with a timestamp. Further, location data area  2121  can specify a history of timestamped locations of a computer device identified by different identifiers. For performing determining of a position of a geofence breach, manager system  110  can examine breach occurrence data that specifies a client computer device identifier in combination with location data specifying a location of that identified client computer device to determine a location of the client computer device at the time of the breach, e.g. by examining a location of location data area  2121  of a client computer device identified with an identifier specified in breach occurrence data in common with a timestamp specified in the breach occurrence data. If the timestamps do not match precisely, the timestamp of location data area  2121  for a certain client computer device that most closely matches the timestamp specified in breach occurrence data area  2122  can be used as the timestamp that specifies the location of the breaching client computer device at the time of the breach. Where a location, using location data from location data area  2121  of data repository  112  does not match a location precisely on a perimeter  602  defining a geofence, the reported location data can be adjusted to reference position on perimeter  602 , e.g. based on the closest distance to perimeter  602 . 
     In one embodiment for improving accuracy of determined geofence breach positions, client computer devices  130 A- 130 Z can be configured so that when sending a breach occurrence communication at block  1306  at current location of the breaching client computer device is sent together with an identifier of the client computer device and a timestamp of a breach. Such configuration can alleviate reliance on examining of data of location data area  2121 . In one embodiment, manager system  110  performing examining of client computer device geofence breaches at block  1111  can include examining a progression of breaches by client computer devices of client computer devices  130 A- 130 Z over time. In one embodiment, manager system  110  performing examining of client computer device geofence breaches can include classifying geofence breaches as occurring with respect to a determined section of a geofence. For example, in reference to  FIG. 6 , geofence defined by geofence perimeter  602  can be segmented into different sections. For example, sections I, II, III, and IV as specified in  FIG. 6 . Other sectional divisions are possible. For example, there can be fewer sections or a larger number of sections defined. 
       FIG. 7  illustrates a process by which manager system  110  can perform examining a progression of geofence breaches over time according to one embodiment. Referring to  FIG. 7 , manager system  110  can record geofence breaches over time with respect to a geofence perimeter  602  defining a geofence and for each of several time periods, e.g. T 1 -T 7  can specify a number of breaches occurring within each of several sections, e.g. sections I, II, III, and IV of a geofence defined by geofence perimeter  602 . On the completion of recording of geofence breach data for each of a plurality of time periods, e.g. time periods  2  in one embodiment. Manager system  110  can determine a predicted number of breaches within each section, e.g. using a regression analysis. 
     Referring to  FIG. 7 , linear regression line  702  depicts a linear regression line drawn with respect to breach data specifying breaches occurring with respect to geofence perimeter section I over the course of time periods T 1 -T 7 . Linear regression line  704  is a linear regression line drawn with respect to geofence breaches occurring with respect to geofence perimeter section II of geofence perimeter  602  over the plurality of time periods T=T 1  to T=T 7  and linear regression line  706  is a linear regression line for geofence breaches occurring with respect to both sections III and IV of geofence perimeter  602  defining a geofence over the course of the time periods T=T 1  to T=T 7 . Manager system  110  can use the linear regression lines  702 ,  704 ,  706  and  708  to predict geofence breaches occurring at the specified sections I, II, III, and IV, respectively, at future time T 8 , depicted in  FIG. 7 . According to the regression analysis depicted in  FIG. 7 , section I of the geofence defined by geofence perimeter  602  in the illustrated embodiment according to linear regression line  702  is predicted to experience about 11.2 breaches during time period T 8 , section II is predicted to experience about 2.9 breaches according to linear regression line  704  during future time period of interest T 8 , section III is predicted to experience about 0.3 breaches according to linear regression line  706  during future time period of interest T 8 , and section IV is predicted to experience about 0.5 breaches according to linear regression line  708  during future time period of interest T 8 . Manager system  110  can use the predicted number of breaches to determine an updated location defined by geofence perimeter  602 . 
     Referring further to the flowchart of  FIG. 4 , manager system  110  at block  1112  can determine whether an activation period for a geofence has expired, e.g. as specified in geofence configuration data specified by an administrator user, using administrator user interface  500  ( FIG. 5 ). Based on a determination that a geofence activation period has expired, manager system  110  at block  1112  can proceed to block  1114  to perform machine learning e.g. including activating machine learning process  119  ( FIG. 1 ), as set forth herein. If on the other hand, manager system  110  at block  1112  determines that a geofence activation period is not expired, manager system  110  can proceed to block  1113  to perform establishing of an updated location of a geofence, e.g. based on an examining of geofence breaches performed at block  1111 . At block  1113 , manager system  110  can activate establishing process  116  ( FIG. 1 ). For performing establishing at block  1113  manager system  110  at block  1111  can use a decision data structure stored in decision data structures area  2123  of data repository  112 . An exemplary decision data structure for use by manager system  110  in performing establishing of an updated location of a geofence is set forth in Table 1. 
     
       
         
           
               
               
               
             
               
                 TABLE 1 
               
               
                   
               
               
                 Geofence Section 
                   
                   
               
               
                 with Largest 
                 Amount of 
                   
               
               
                 Predicted 
                 Difference 
                   
               
               
                 of Breaches 
                 Number 
                 Decision 
               
               
                   
               
             
            
               
                 I 
                 D(I) ≥ T1 
                 Move S 1 unit 
               
               
                 I 
                 D(I) ≥ T2 
                 Move S 2 units 
               
               
                 I 
                 D(I) &lt; T1 
                 No Movement 
               
               
                 II 
                 D(II) ≥ T1 
                 Move W 1 unit 
               
               
                 II 
                 D(II) ≥ T2 
                 Move W 2 units 
               
               
                 II 
                 D(II) &lt; T1 
                 No Movement 
               
               
                 . 
                 . 
                 . 
               
               
                 . 
                 . 
                 . 
               
               
                 . 
                 . 
                 . 
               
               
                   
               
            
           
         
       
     
     Referring to Table 1, Table 1 is a decision data structure cognitively mapping values in dependence on predicted numbers breaches to updated geofence locations as defined by geofence location change information. Artificial intelligence (AI) decision table, as set forth in Table 1 includes three columns. The first column specifies the section of a geofence, e.g. section I, II, III, or IV having the largest number of predicted breaches for a future time period of interest, e.g. time period of interest T 8  as described in reference to  FIG. 7 . The second column of Table 1 is the column “amount of difference” which specifies in one embodiment the difference value D(X)=B(X)−A(X), where D is numerical value that specifies an amount of difference, X is the section having the highest number of predicted breaches, B is the predicted number of breaches in future time period of interest, and the A is an average predicted number of breaches per section in the future time period of interest. 
     In Table 1, the classifications for breach activity are (a) that D is a first threshold; (b) that D is a second threshold; or (c) that D is &lt;a first threshold. Other “amount of difference” classifications are possible. For example, with reference to Table 1, a section of a geofence having a highest predicted number of breaches can be classified into an arbitrary number of classifications, e.g. three classifications as specified in Table 1 or N classifications. In one embodiment the thresholds T 1  and T 2  as described in reference to Table 1 can be values that are determined as a percentage of a predicted average number of breaches for a geofence during a time period of interest. For example, T 1  and T 2  can be numerical values determined by calculating first and second different percentages of predicted numbers of breaches of a geofence during a future time period of interest. 
     In one illustrative embodiment T 1  can be calculated as being 30 percent of the predicted number of breaches of a geofence during a future time period of interest and T 2  can be calculated as being 40 percent of the predicted number of breaches of geofence during the future time period of interest. In the illustrative example of  FIG. 7 , T 1  can be calculated as 0.3((11.2+2.9+0.3+0.5))=4.47 and T 2 =5.96 and the predicted average number of breaches per section is 14.9/4=3.75. Accordingly in reference to the described illustrative example described in reference to Table 1 the decision conditions yielding the decision “Move South (S) two units” applies based on D(I)=11.2−3.75=7.45 so that D(I)≥T 2 . In another embodiment, the thresholds can be functions that are based on a standard deviation of breaches that are experienced by sections of a geofence as set forth herein. The third column of Table 1 is a decision column. In the decision column there can be specified location change information that defines a new location for a geofence. The location change information can specify a direction of change as well as an offset distance of change. 
     According to manager system  110  providing direction change location information using a decision data structure as set forth in Table 1, can establish updated locations of a geofence that are based on a section of a geofence having a highest number of predicted breaches. As set forth in Table 1, direction in which to move a geofence can be correlated to breach activity as follows: move the geofence South (S) based on there being a threshold exceeding number of predicted geofence breaches of the geofence section I located South of a geofence center; move the geofence West (W) based on there being a threshold exceeding number of predicted geofence breaches of the geofence section II located west of a geofence center; move the geofence North (N) based on there being a threshold exceeding number of predicted geofence breaches of the geofence section III located North of a geofence center; and move the geofence East (E) based on there being a threshold exceeding number of predicted geofence breaches of the geofence section IV located east of a geofence center. 
     Embodiments herein recognize that a number of breaches of a geofence can be expected to increase by moving of a geofence in a direction of the highest geofence activity. For example, based on an even distribution of geofence breach directions, a certain percentage of breaches can be expected to occur at an acute angle with respect to a tangent line of a geofence perimeter  602 , defining a geofence. Embodiments herein recognize that an increased number of breaches in such breaching directions can be yielded by moving of a geofence in a direction of highest breach position activity, e.g. moving South for highest South section geofence breach activity, West for highest West section geofence breach activity, North for highest North section geofence breach activity, and/or East for highest East section geofence breach activity. 
     A decision data structure according to Table 1 can be configured to provide more granular geofence updated location information. For example, rather than manager system  110  segmenting a geofence perimeter  602  into four sections (I, II, III, and IV), manager system  110  can instead segment a geofence perimeter into N sections, e.g. N=8, 16, etc., and direction decisions can be correspondingly made more granular, e.g. rather than encompass the directions South, West, North, and East, can encompass more granular directions in another embodiment, e.g., South, Southwest, West, Northwest, North, Northeast, East, and Southeast, or other directions intermediate of the described directions. Offset distance units specified in column three of Table 1, can also specify additional and more granular alternatives. 
     Embodiments herein recognize that whether or not movement of a geofence increases a number of breaches, can be in dependence on a travelling direction of client computer devices in an environment including a geofence, e.g. a geofence defined by perimeter  602  as set forth in  FIG. 6 . For example, referring to  FIG. 6  movement of the geofence defined by geofence perimeter  602  South may result in yielding of an additional breach by a client computer device travelling along path  622  running parallel to center tangent line  620  of section I, but may not result in additional breaches being yielded by the client computer device travelling along path  624  based on the client computer device travelling along path  624  (running perpendicular to center tangent line  620  of section I) breaching the geofence defined by geofence perimeter  602  in any respect without an updated location of the geofence. In some embodiments geofence breach position data subject to examining by manager system  110  is filtered based on breach direction, so that breaches in a direction that are more parallel to a geofence perimeter tangent line (e.g. as determined by a threshold), are preferentially examined relative to breach positions attributable to travel paths that are angles tending towards normal angles with respect to geofence perimeter tangent lines. 
     In one embodiment, in reference to  FIG. 7 , data recorded in the graphical data depiction of  FIG. 7  can be filtered so that only geofence breaches attributable to travel paths at angles with respect to geofence perimeter tangent lines of less than a threshold number of degrees, are recorded in the data set depicted in  FIG. 7 . Thus, manager system  110  can be configured to be more responsive to breaches at travel path directions likely to be more sensitive to geofence location updates. 
     For determining a path direction of a geofence breach, manager system  110  can examine a history of locations for a breaching client computer device using data of location data area  2121  of data repository  112 . Manager system  110  for determining a traveled direction of a breaching client computer device can in addition or alternatively examine data of social media system  140 , e.g. such as posts content which can be examined running NLP process  113  that may specify one or more locations of a user of a client computer device at one or more specified points in time and also such data as calendar data that may be included in data respecting a user within social media system  140 . In one embodiment, manager system  110  can determine a travel path and direction of a breaching client computer device using data of location data area  2121  and can use data of social media system  140  to determine confidence levels associated with determined traveling paths and directions of breaching client computer devices. 
     In one embodiment manager system  110  at block  1113  can perform the described establishing conditionally based on one or more criterion being satisfied. In one embodiment, manager system  110  can deploy a geofence at block  1107  based on configuration data received at block  1105  that specifies a target number of breaches for an activation period of a geofence. As described with reference to administrator user interface  500 , as shown in  FIG. 5 , target number of breaches can be specified in area  520 , e.g. by administrator user selection or by automated selection based on, e.g. past performance data of geofences previously used by system  100  having characteristics in common with a geofence currently being configured. 
     In one embodiment manager system  110  at block  1113  performs establishing an updated location for geofence conditionally on the condition that a current geofence is an underperforming geofence. For example, on the specifying by an administrator user using area  520 , a target number of breaches of a geofence being configured, which target number can also be automatically determined as set forth herein. Manager system  110  can determine a schedule of cumulative geofences that must have been yielded at the conclusion of each time period of interest subject to examination during a geofence activation period. The schedule can take into account for example, that geofence breach rates are not constant during the course of a day or a week. Manager system  110  at block  1113  can examine the geofence breach tracking schedule to determine whether the current geofence is on track to achieve a target number of breaches, e.g. the number of breaches specified automatically or by administrator user selection within area  520  of administrator user interface  500 . 
     Based on the current number of cumulative geofence breaches being below the target number as specified by the schedule, manager system  110  can proceed to perform the establishing of an update geofence location at block  1113  to increase a yield of geofence breaches. On the other hand, manager system  110  can restrict the performing of establishing of an updated geofence location at block  1113  based on a determining that a current geofence is on track to yield at least the target number of breaches specified by the described geofence breach tracking schedule. 
     In one embodiment, manager system  110  at block  1113  can restrict the establishing of an updated location of a geofence if the updated location is not permitted according to machine logic rules that specify restrictions on a location of a geofence. Embodiments herein recognize that deploying a geofence such as a geofence defined by a geofence perimeter  602  to encompass a venue  122  ( FIG. 1 ) can provide numerous advantages. For example, client computer devices that breach a geofence by definition will be at a location that is geographically related to the location of venue  122 . In one embodiment machine logic rules can be employed to assure that a geofence having an updated location notwithstanding being an updated location, remains a location that is related to the location of venue  122 . In one embodiment a machine logic rule can be established so that the location of geofence defined by geofence perimeter  602  while being subject to updating is restricted to be at a location so that a geofence perimeter  602  encompasses a location of interest such as location of interest  601  ( FIG. 5 ) that specifies a location of venue  122 . 
     In one embodiment, according to a machine logic rule employed by manager system  110 , the size of a geofence can be restricted to be of a constant size throughout an activation period of a geofence. For example, referring to geofence defined by geofence perimeter  602  manager system  110  can employ a machine logic rule so that the area defined by geofence perimeter  602  remains constant through an activation period of the geofence. Such restricting can assure that the geofence performs predictably and consistently throughout an activation period of the geofence and facilitates processing wherein the geofence defined by geofence perimeter  602  is processed as being a single logical geofence throughout an activation period thereof in spite of it changing position. 
     In one embodiment manager system  110  can be configured so that a deployed geofence defined by geofence perimeter  602  has characteristics as depicted in  FIG. 8  over the course of an activation period of the geofence.  FIG. 8  depicts area  600  of administrator user interface  500  as shown in  FIG. 5  over the course of a plurality of time periods of interest according to one embodiment. At a time of initial deployment (block  1107 ) the geofence defined by geofence perimeter  602  can be at depicted location “A” so that a center  1602  of a geofence defined by perimeter  602  depicted in the area  600  can be centered on location of interest  601  which can be specified by an administrator user using administrator user interface  500  to be the location of venue  122  ( FIG. 1 ). 
     In an illustrative use case, geofence breaches can be dominant at a “South” section during early time periods of interest of a geofence activation period and accordingly the geofence defined by geofence perimeter  602  can migrate South as depicted by dashed geofence perimeter  602  at location “B”. 
     During later time periods of interest of an activation period of the geofence, geofence breaches occurring at a “West” section of a geofence perimeter  602  can be dominate and accordingly the geofence defined by geofence perimeter  602  can migrate west as depicted by the dashed geofence perimeter  602  at location “C” of  FIG. 8 . Thus, the described manager system  110  can iteratively update the location of the geofence defined by geofence perimeter  602  so that the location of the geofence migrates throughout different locations of an area over time. 
     However, in one embodiment for each location update manager system  110  can enforce restrictions such as those described. According to one restriction, manager system  110  can restrict an updated location of a geofence having geofence perimeter  602  so that an updated location a geofence perimeter  602  continues to encompass region of interest  601  which can be specified to be the location of venue  122 . According to another restriction that can be enforced, manager system  110  can enforce the restriction that the geofence defined by geofence perimeter  602  remains of a constant size through the activation period of the geofence. Such restricting can facilitate processing of the defined geofence as a logically unchanged geofence through an activation period of the geofence. On the establishing of the updated location of the geofence at block  1113  manager system  110  can proceed to update a location of a geofence so that a current geofence has the location of the updated location determined by the establishing at block  1113 . 
     For updating the location of a geofence, manager system  110  at block  1107  can proceed to block  1107  to send geofence data to client computer devices  130 A- 130 Z. The geofence data sent at block  1107  can include geofence location change data. Regarding block  1107 , it will be seen that for a first iteration of block  1107  responsively to receipt of configuration data at block  1106 , geofence location data sent at block  1107  can include geofence location data for initial deployment of a geofence at an initial location. During second to Nth iterations of block  1107  geofence data sent at block  1107  responsively to performing of establishing at block  1113  can include geofence location change data that specifies a change of location of a deployed geofence. The change location data can include, e.g. one or more of a direction change of a deployed geofence or an offset distance change of a geofence. The direction change data can include such data as the directions, South, West, North, East, or in the case of a more granular configuration can include, South, Southwest, West, North, Northeast, East, and Southeast. The distance offset information can take on different forms in different embodiments in system  100 . 
     The geofence location change data as set forth herein can be determined using a decision data structure, such as the decision data structure described with reference to Table 1 according to one embodiment. Manager system  110  sending geofence location change data to client computer devices  130 A- 130 Z can include manager system  110  sending location change data to respective breach determination processes being run by respective client computer devices  130 A- 130 Z so that on receipt of the location change data by the respective client computer devices at block  1304  the respective client computer devices  130 A- 130 Z are enabled to detect geofence breaches with respect to an updated location of a deployed geofence. 
     According to one advantage of a geofence as set forth herein, the geofence can be configured to be subject to location change but can be processed as a logically constant geofence throughout the location changes. Embodiments herein recognize that restricting location changes of a geofence can facilitate processing of a geofence as a logically constant geofence, notwithstanding location changes of a geofence. Restrictions on location changes can include such restrictions as (a) that a geofence be restricted to locations that encompass region of interest, e.g. region of interest  601  as shown in  FIG. 8 , (b) that a geofence retains a constant size throughout an activation period of a geofence also as depicted in  FIG. 8 , (c) the geofence is restricted to location change in a predetermined set of directions and/or (d) a distance offset of a location change can be restricted, e.g. to one or a predetermined number or distance units, wherein the distance units can be limited, e.g. in increments of 10 meters, 50 meters, 100 meters, 500 meters, or 1 kilometer according to some examples. One or more of the above types of restrictions can be useful in providing a geofence that can be processed as a logically constant geofence throughout an activation period of the geofence. 
     Embodiments herein accordingly permit performance of geofence aided location based services (LBS) even where a geofence is currently located differently by different client computer devices  130 A- 130 Z. It is expected for example that at block  1107 , in response to performing of establishing at block  1113  some client computer devices  130 A- 130 Z may be unavailable for updating. For example, a certain number of client computer devices of client computer devices  130 A- 130 Z may be shut off (powered down) or out of range at a time of location data sending at block  1107 . Further, some client computer devices of client computer devices  130 A- 130 Z may have configured settings that permit updating of such client computer devices only at limited times. Therefore, it is expected that in some scenarios, some client computer devices  130 A- 130 Z can be performing geofence breach determinations based on a current (most recent) updated location of a geofence whereas other client computer devices of client computer devices  130 A- 130 Z may be performing breach determination based on a location of the geofence that is one or more iteration prior to the current iteration. Notwithstanding because of features set forth herein that permit a geofence to be processed as a logically common geofence throughout location changes, breach determinations based on prior locations of a geofence can be processed as valid breaches by manager system  110  on receipt of a breach occurrence communication at block  1108 . There is set forth herein a process for updating a geofence wherein the updating a location of the geofence includes sending location change information to update geofence breach determination logic locally running on a plurality of client computer devices, and wherein the method includes the plurality of client computer devices e.g. client computer devices of client computer devices  130 A- 130 Z asynchronously performing updates of their respective geofence breach determination logic based on the location change information so that during an iteration of the examining, the examining includes examining breach information of a first client computer device and a second client computer device, wherein the first client computer device uses a first location of the geofence and the second client computer device uses the second location of the geofence. 
     According to one embodiment, record data subject to examining regarding breaches of a geofence can be agnostic to the particular location of a breach at a time of a breach. For example, for providing low overhead processing, geofence breaches over time data recorded as set forth in  FIG. 7  and subject to regression analysis for performing of geofence breach predictions may but need not include a record of a location of a geofence at a time of a breach (e.g. may use a section of the beach without using a location of a geofence). Machine logic features set forth herein can be self-correcting in that the simple machine logic processing set forth herein without respect to a geofence location can optimize breach yields without retention of a record of a geofence location. 
     The exemplary decision data structure as set forth in Table 1 has specific parameter values, e.g. involving threshold parameter values and distance unit parameter values. In one embodiment, manager system  110  can run machine learning process  119 , e.g. at block  1114  and/or at block  1109 , to iteratively update the decision data structure such as the decision data structure of Table 1 by machine learning. In one embodiment, manager system  110  can monitor performance of current logic for determining geofence location updates. Performance can be monitored based on one or more criterion, e.g. the number of breaches or the correspondence between a number of breaches and predicted number of breaches. Manager system  110  running machine learning process  119  in one embodiment can iteratively examine performance of manager system  110  across a distribution of instances, wherein each instance employs differently configured decision data structure (e.g. having differentiated parameter values) for driving a geofence location update decision. 
     Manager system  110  can be running a plurality of instances of blocks  1102 - 1105  for a plurality of geofences. For each instance, manager system  110  can change parameter values as shown in Table 1 within valid ranges to facilitate searching of optimum values and manager system  110  by running machine learning process  119  can update the parameter values over the time so that the parameter values over time (as more sample data is accrued) converge on values that are optimally performing values. Based on a result of monitoring of different instances over time, manager system  110  running machine learning process  119  can bias the variety of the decision data structures employed, so that the decision data structures of decision data structures area  2123  assume the characteristics of the most successfully performing iterations. 
     At block  1115  manager system  110  can return to block  1105  to wait for configuration data defining a new geofence for deployment. 
     Certain embodiments herein may offer various technical computing advantages involving computing advantages to address problems arising in the realm of computer networks. Particularly, computer networks operating to provide location based services (LBS). Embodiments herein can include migrating geofence that can change locations which can be featured to permit processing of the geofence as a logically constant geofence throughout an activation period of the geofence, notwithstanding location changes thereof. Embodiments herein can permit a geofence to automatically migrate over time to yield additional geofence breaches based on a determination in one embodiment that the geofence is underperforming. Provided herein according to one embodiment, are processes that permit a geofence to be updated in terms of location automatically without administrator reconfiguration of a geofence, to permit target goals associated with the geofence to be satisfied with reduced processing overhead. Embodiments herein permit migration of a location of a geofence, but have features so that the geofence operates consistently and predictably notwithstanding the migrations to facilitate satisfaction of target breach goals. Embodiments herein can feature regression analysis to predict perimeter locations of future geofence breaches and to establish location changes in accordance with the predicted breaches. Embodiments herein recognize that distribution of geofence breach determination logic to client computer devices for local on-device breach determination can yield significant improvements in computer network performance, e.g., in terms of bandwidth and power conservation, speed and reliability, but that the advantages can be lost if a geofence is not accurately deployed. Accordingly, features can be provided for lightweight updating of geofence location. Embodiments herein can update a distributed geofence using reduced bandwidth and processing resources. Embodiments herein can feature a distributed geofence and provisions can be included so that updates of a geofence location can be implemented asynchronously by a set of computer devices. Embodiments can process and store data respecting a geofence as a logically constant geofence notwithstanding location changes of the geofence and differentiated locations of the geofence between client computer devices of client computer devices. Various decision data structures can be used to drive artificial intelligence (AI) decision making, such as decision data structure that cognitively maps social media interactions in relation to posted content in respect to parameters for use in better allocations that can include allocations of digital rights. Decision data structures as set forth herein can be updated by machine learning so that accuracy and reliability is iteratively improved over time without resource consuming rules intensive processing. Machine learning processes can be performed for increased accuracy and for reduction of reliance on rules based criteria and thus reduced computational overhead. For enhancement of computational accuracies, embodiments can feature computational platforms existing only in the realm of computer networks such as artificial intelligence platforms, and machine learning platforms. Embodiments herein can employ data structuring processes, e.g. processing for transforming unstructured data into a form optimized for computerized processing. Embodiments herein can examine data from diverse data sources such as data sources that process radio signals for location determination of users. Embodiments herein can include artificial intelligence processing platforms featuring improved processes to transform unstructured data into structured form permitting computer based analytics and decision making. Embodiments herein can include particular arrangements for both collecting rich data into a data repository and additional particular arrangements for updating such data and for use of that data to drive artificial intelligence decision making. 
       FIGS. 9-11  depict various aspects of computing, including a computer system and cloud computing, in accordance with one or more aspects set forth herein. 
     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. 
     Referring now to  FIG. 9 , a schematic of an example of a computing node is shown. Computing node  10  is only one example of a computing node suitable for use as a 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, computing node  10  is capable of being implemented and/or performing any of the functionality set forth hereinabove. Computing node  10  can be implemented as a cloud computing node in a cloud computing environment, or can be implemented as a computing node in a computing environment other than a cloud computing environment. 
     In computing node  10  there is a computer system  12 , 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  12  include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, hand-held 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. 
     Computer system  12  may be described in the general context of computer system-executable instructions, such as program processes, being executed by a computer system. Generally, program processes may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system  12  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 processes may be located in both local and remote computer system storage media including memory storage devices. 
     As shown in  FIG. 9 , computer system  12  in computing node  10  is shown in the form of a computing device. The components of computer system  12  may include, but are not limited to, one or more processor  16 , a system memory  28 , and a bus  18  that couples various system components including system memory  28  to processor  16 . In one embodiment, computing node  10  is a computing node of a non-cloud computing environment. In one embodiment, computing node  10  is a computing node of a cloud computing environment as set forth herein in connection with  FIGS. 10-11 . 
     Bus  18  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 Interconnects (PCI) bus. 
     Computer system  12  typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system  12 , and it includes both volatile and non-volatile media, removable and non-removable media. 
     System memory  28  can include computer system readable media in the form of volatile memory, such as random access memory (RAM)  30  and/or cache memory  32 . Computer system  12  may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage system  34  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  18  by one or more data media interfaces. As will be further depicted and described below, memory  28  may include at least one program product having a set (e.g., at least one) of program processes that are configured to carry out the functions of embodiments of the invention. 
     One or more program  40 , having a set (at least one) of program processes  42 , may be stored in memory  28  by way of example, and not limitation, as well as an operating system, one or more application programs, other program processes, and program data. One or more program  40  including program processes  42  can generally carry out the functions set forth herein. In one embodiment, manager system  110  can include one or more computing node  10  and can include one or more program  40  for performing functions described with reference to method  200  of  FIG. 2  and functions described with reference to method  300  of  FIG. 3  and functions described with reference to manager system  110  as set forth in the flowchart of  FIG. 4 . In one embodiment, one or more client computer device  130 A- 130 Z can include one or more computing node  10  and can include one or more program  40  for performing functions described with reference to one or more client computer device  130 A- 130 Z as set forth in the flowchart of  FIG. 4 . In one embodiment, administrator client computer device  125  can include one or more computing node  10  and can include one or more program  40  for performing functions described with reference to administrator client computer device  125  as set forth in the flowchart of  FIG. 4 . In one embodiment, the computing node based systems and devices depicted in  FIG. 1  can include one or more program for performing function described with reference to such computing node based systems and devices. 
     Computer system  12  may also communicate with one or more external devices  14  such as a keyboard, a pointing device, a display  24 , etc.; one or more devices that enable a user to interact with computer system  12 ; and/or any devices (e.g., network card, modem, etc.) that enable computer system  12  to communicate with one or more other computing devices. Such communication can occur via Input/Output (I/O) interfaces  22 . Still yet, computer system  12  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  20 . As depicted, network adapter  20  communicates with the other components of computer system  12  via bus  18 . It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer system  12 . Examples, include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc. In addition to or in place of having external devices  14  and display  24 , which can be configured to provide user interface functionality, computing node  10  in one embodiment can include display  25  connected to bus  18 . In one embodiment, display  25  can be configured as a touch screen display and can be configured to provide user interface functionality, e.g. can facilitate virtual keyboard functionality and input of total data. Computer system  12  in one embodiment can also include one or more sensor device  27  connected to bus  18 . One or more sensor device  27  can alternatively be connected through I/O interface(s)  22 . One or more sensor device  27  can include a Global Positioning Sensor (GPS) device in one embodiment and can be configured to provide a location of computing node  10 . In one embodiment, one or more sensor device  27  can alternatively or in addition include, e.g., one or more of a camera, a gyroscope, a temperature sensor, a humidity sensor, a pulse sensor, a blood pressure (bp) sensor or an audio input device. Computer system  12  can include one or more network adapter  20 . In  FIG. 10  computing node  10  is described as being implemented in a cloud computing environment and accordingly is referred to as a cloud computing node in the context of  FIG. 10 . 
     Referring now to  FIG. 10 , 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. 10  are intended to be illustrative only and that 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. 11 , a set of functional abstraction layers provided by cloud computing environment  50  ( 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: 
     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 processing components  96  for establishing and updating geofence locations as set forth herein. The processing components  96  can be implemented with use of one or more program  40  described in  FIG. 9 . 
     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 flowcharts 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. 
     The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprise” (and any form of comprise, such as “comprises” and “comprising”), “have” (and any form of have, such as “has” and “having”), “include” (and any form of include, such as “includes” and “including”), and “contain” (and any form of contain, such as “contains” and “containing”) are open-ended linking verbs. As a result, a method or device that “comprises,” “has,” “includes,” or “contains” one or more steps or elements possesses those one or more steps or elements, but is not limited to possessing only those one or more steps or elements. Likewise, a step of a method or an element of a device that “comprises,” “has,” “includes,” or “contains” one or more features possesses those one or more features, but is not limited to possessing only those one or more features. Forms of the term “based on” herein encompass relationships where an element is partially based on as well as relationships where an element is entirely based on. Methods, products and systems described as having a certain number of elements can be practiced with less than or greater than the certain number of elements. Furthermore, a device or structure that is configured in a certain way is configured in at least that way, but may also be configured in ways that are not listed. 
     The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below, if any, are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description set forth herein has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the form 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 disclosure. The embodiment was chosen and described in order to best explain the principles of one or more aspects set forth herein and the practical application, and to enable others of ordinary skill in the art to understand one or more aspects as described herein for various embodiments with various modifications as are suited to the particular use contemplated.