Location optimization method and system in a communication network

Abstract

A method and system for optimizing location in a communication network is provided, in which an instruction is received for wireless communication to be performed by a computing device, and in response to receiving the instruction, an optimized location for performing the wireless communication is determined based on a location of the computing device and an optimized location list, and the optimized location is communicated to the computing device performing the wireless communication.

Description

[Technical Field]

[0001] The present invention relates generally to the field of communication networks, and more particularly to optimizing location for signal quality in communication networks. [Background technology]

[0002] A communication network in which the last link is wireless is also known as a cellular or mobile network. The network, and specifically the last wireless link, spans a physical area within a cell. Each cell is served by at least one fixed-location transceiver (i.e., a cell tower). Each transceiver may be for one provider or multiple providers. A network enables wireless communication by devices, including but not limited to cell phones, tablets, laptops, pagers, etc., as long as they have a portable transceiver contained within or attached (physically or wirelessly) to the device. Summary of the Invention

[0003]

[0009] Embodiments of the present invention disclose a computer-implemented method, computer program product, and system for wireless communication. In one embodiment, instructions are received. The instructions are for wireless communication to be conducted by a computing device. In response to receiving the instructions, an optimized location for conducting the wireless communication is determined based on a location of the computing device and an optimized location list. The optimized location is communicated to the computing device conducting the wireless communication. [Brief explanation of the drawings]

[0004] [Figure 1] 1 is a functional block diagram of a network computing environment, generally designated 100, suitable for operation of a central optimization program 112, in accordance with at least one embodiment of the present invention. [Figure 2] FIG. 1 is a flowchart diagram illustrating the operational steps of a central optimizer 112 for determining an optimization location, in accordance with at least one embodiment of the present invention. [Figure 3] FIG. 10 is a flowchart diagram illustrating the operational steps of the local optimizer 122 for applying optimized locations, in accordance with at least one embodiment of the present invention. [Figure 4] FIG. 4 is a block diagram illustrating components of a computer, generally designated 400, suitable for running the central optimizer 112 and the local optimizer 122, in accordance with at least one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0005] The present invention provides a method, computer program product, and computer system for determining an optimized location for communications in a network and providing the determined optimized location to a computing device. Embodiments of the present invention recognize that when a user uses a computing device to transmit data, including but not limited to text messages, voice calls, video calls, etc., the user may experience poor service from the network due to the physical location of the computing device used to transmit the data. Embodiments of the present invention recognize that many users may move around a physical area in an attempt to find a more optimal physical location for their computing device to have a better signal to connect to the network and, as a result, a better data connection with the network.

[0006] An embodiment of the present invention provides a program for determining an optimal location for a data transfer and then providing this optimal location to a user's computing device. An embodiment of the present invention enables the computing device to provide instructions to a user on how to physically reach the determined optimal location. An embodiment of the present invention provides a program for learning an optimal location in a telecommunications network or a wireless communication network, which may be a Wi-Fi network, to determine the optimal or best location to perform a data transfer.

[0007] Referring now more particularly to various embodiments of the present invention, Figure 1 is a functional block diagram of a network computing environment, generally designated 100, suitable for operation of central optimizer 112 and local optimizer 122 in accordance with at least one embodiment of the present invention. Figure 1 is merely provided as an example of one implementation and is not intended to imply any limitation with respect to the environments in which different embodiments may be implemented. Many modifications to the depicted environment may be made by one of ordinary skill in the art without departing from the scope of the present invention as defined by the appended claims.

[0008] Network computing environment 100 includes server device 110, computing device 120, and IoT devices 130-1 through 130-n interconnected via network 140. In embodiments of the present invention, network 140 may be a telecommunications network, a local area network (LAN), a wide area network (WAN) such as the Internet, or a combination of the three, and may include wired, wireless, or fiber optic connections. Network 140 may include one or more wired and / or wireless networks capable of receiving and transmitting data, voice, and / or video signals, including multimedia signals, including voice, data, and video signals. In general, network 140 may be any combination of connections and protocols that support communication between server device 110, computing device 120, IoT devices 130-1 through 130-n, and other computing devices (not shown) within network computing environment 100.

[0009] In one embodiment, network 140 may include cellular towers that are part of a communications network that is a wireless cellular network. A cellular network may include a "cell" that covers a physical land area with at least one fixed location transceiver, but may include three or more cellular sites and / or base transceiver stations. These fixed location transceivers and / or base transceiver stations may provide transmission of voice, data, and other types of content by connecting to the rest of the communications devices that are part of network 140.

[0010] Server device 110 is a computing device that may be a laptop computer, a tablet computer, a netbook computer, a personal computer (PC), a desktop computer, a personal digital assistant (PDA), a smartphone, a smartwatch, or any programmable electronic device capable of receiving, sending, and processing data. Generally, server device 110 represents any programmable electronic device or combination of programmable electronic devices that can execute machine-readable program instructions and communicate with other computing devices (not shown) in computing environment 100 over a network, such as network 140.

[0011] In various embodiments of the present invention, server device 110 may be a computing device that may be a standalone device, an administrative server, a web server, a media server, a mobile computing device, or any other programmable electronic device or computing system capable of receiving, sending, and processing data. In other embodiments, server device 110 represents a server computing system that utilizes multiple computers as server systems, such as in a cloud computing environment. In one embodiment, server device 110 represents a computing system that utilizes clustered computers and components (e.g., database server computers, application server computers, web servers, and media servers) that function as a single pool of seamless resources when accessed within network computing environment 100.

[0012] In one embodiment, server device 110 includes a user interface (not shown). A user interface is a program that provides an interface between a user and an application. A user interface refers to the information (such as graphics, text, and sound) that a program presents to a user and the control sequences the user uses to control the program. There are many types of user interfaces. In one embodiment, the user interface can be a graphical user interface (GUI). A GUI is a type of user interface that allows a user to interact with electronic devices such as a keyboard and mouse through graphical icons and visual indicators, such as secondary notation, as opposed to a text-based interface, typed command labels, or text navigation. In computers, GUIs were introduced in response to the perceived steep learning curve of command-line interfaces, which require commands to be typed on a keyboard. Actions in a GUI are often performed by direct manipulation of graphical elements.

[0013] In one embodiment, server device 110 includes central optimization program 112. An embodiment of the present invention provides central optimization program 112 for determining an optimization location. In one embodiment, central optimization program 112 receives one or more data. In one embodiment, central optimization program 112 determines an optimization location based on the received data. In one embodiment, central optimization program 112 determines whether a threshold has been reached. In one embodiment, if the threshold has been reached, central optimization program 112 transmits the optimization location. In one embodiment, if the threshold has not been met, central optimization program 112 receives data.

[0014] In one embodiment, server device 110 includes information repository 114. In one embodiment, information repository 114 may be managed by central optimization program 112. In alternative embodiments, information repository 114 may be managed by the operating system of server device 110, by a separate program (not shown), alone or together with central optimization program 112. Information repository 114 is a data repository that may store, collect, or analyze information, or a combination thereof. In some embodiments, information repository 114 is located external to server device 110 and accessed via a communications network, such as network 140. In some embodiments, information repository 114 is stored on server device 110. In some embodiments, information repository 114 may reside on another computing device (not shown), provided that information repository 114 is accessible by server device 110. In one embodiment, information repository 114 may include location information including, but not limited to, signal strength, season of the year, weather conditions, location type, azimuth angle, determined network congestion at a location at a given time, availability of completed calls at a location at a given time, and historical success rates at a given time. In one embodiment, information repository 114 may include a list of optimized locations, physical layout information of portions of network 140 (i.e., wireless network layout, tower layout, cell structure, etc.), and carrier information.

[0015] The information repository 114 may be implemented using any volatile or non-volatile storage medium for storing information, as known in the art. For example, the information repository 114 may be implemented with a tape library, an optical library, one or more independent hard disk drives, multiple hard disk drives in a redundant array of independent disks (RAID), a solid state drive (SSD), or random access memory (RAM). Similarly, the information repository 114 may be implemented with any suitable storage architecture known in the art, such as a relational database, an object-oriented database, or one or more tables.

[0016] Computing device 120 may be a laptop computer, a tablet computer, a netbook computer, a personal computer (PC), a desktop computer, a personal digital assistant (PDA), a smartphone, a smartwatch, or any programmable electronic device capable of receiving, sending, and processing data. Generally, computing device 120 represents any programmable electronic device or combination of programmable electronic devices capable of executing machine-readable program instructions and communicating with other computing devices (not shown) in computing environment 100 over a network, such as network 140.

[0017] In various embodiments of the present invention, computing device 120 may be a computing device that may be a standalone device, an administrative server, a web server, a media server, a mobile computing device, or any other programmable electronic device or computing system capable of receiving, sending, and processing data. In other embodiments, computing device 120 represents a server computing system that utilizes multiple computers as a server system, such as in a cloud computing environment. In one embodiment, computing device 120 represents a computing system that utilizes clustered computers and components (e.g., database server computers, application server computers, web servers, and media servers) that function as a single pool of seamless resources when accessed within network computing environment 100.

[0018] In one embodiment, computing device 120 includes a user interface (not shown). A user interface is a program that provides an interface between a user and an application. A user interface refers to the information (such as graphics, text, and sound) that a program presents to a user and the control sequences the user uses to control the program. There are many types of user interfaces. In one embodiment, the user interface can be a graphical user interface (GUI). A GUI is a type of user interface that allows a user to interact with electronic devices such as a keyboard and mouse through graphical icons and visual indicators, such as secondary notation, as opposed to a text-based interface, typed command labels, or text navigation. In computers, GUIs were introduced in response to the perceived steep learning curve of command-line interfaces, which require commands to be typed on a keyboard. Actions in a GUI are often performed by direct manipulation of graphical elements.

[0019] In one embodiment, computing device 120 includes local optimization program 122. An embodiment of the present invention provides local optimization program 122 for applying an optimization location. In one embodiment, local optimization program 122 receives instructions. In one embodiment, local optimization program 122 determines an optimization location. In one embodiment, local optimization program 122 communicates the optimization location. In one embodiment, local optimization program 122 provides data to central optimization program 112.

[0020] In one embodiment, computing device 120 includes information repository 124. In one embodiment, information repository 124 may be managed by local optimizer 122. In alternative embodiments, information repository 124 may be managed by the operating system of computing device 120, by another program (not shown), alone or together with local optimizer 122. Information repository 124 is a data repository that may store, collect, or analyze information, or a combination thereof. In some embodiments, information repository 124 is located external to computing device 120 and accessed via a communications network, such as network 140. In some embodiments, information repository 124 is stored on computing device 120. In some embodiments, information repository 124 may reside on another computing device (not shown), provided that information repository 124 is accessible by computing device 120. In one embodiment, the information repository 124 may include location information including, but not limited to, signal strength, season of the year, weather conditions, location type, azimuth angle, determined network congestion at a location at a given time, availability of completed calls at a location at a given time, and historical success rates at a given time. In one embodiment, the information repository 124 may include optimized location and carrier information.

[0021] Information repository 124 may be implemented using any volatile or non-volatile storage medium for storing information, as known in the art. For example, information repository 124 may be implemented with a tape library, an optical library, one or more independent hard disk drives, multiple hard disk drives in a redundant array of independent disks (RAID), a solid state drive (SSD), or random access memory (RAM). Similarly, information repository 124 may be implemented with any suitable storage architecture known in the art, such as a relational database, an object-oriented database, or one or more tables.

[0022] In the broadest sense, IoT devices 130-1, 130-2, and 130-n are any devices capable of connecting to network 140 and transmitting data to and from network 140. In one embodiment, IoT devices 130-n can be any number of IoT devices. In other words, for ease of discussion, only three IoT devices 130 are shown in network computing environment 100; however, there may be any number of IoT devices 130-n communicating within network computing environment 100. In one embodiment, IoT devices 130-n can be computing devices that can be laptop computers, tablet computers, netbook computers, personal computers (PCs), desktop computers, personal digital assistants (PDAs), smartphones, smartwatches, or any programmable electronic device capable of receiving, sending, and processing data. In general, computing device 120 represents any programmable electronic device or combination of programmable electronic devices capable of executing machine-readable program instructions and communicating with other computing devices (not shown) within computing environment 100 over a network, such as network 140. In one embodiment, IoT device 130-n may collect and / or transmit any number of data including, but not limited to, signal strength, season of the year, weather conditions, location type, azimuth angle, network congestion at a location at a given time, availability of completed calls at a location at a given time, and history of success rates at a given time. In one embodiment, IoT device 130-n may record packet loss for communications conducted at IoT device 130-n.

[0023] FIG. 2 is a flowchart diagram of a workflow 200 illustrating the operational steps of the central optimization program 112 for determining an optimized location, in accordance with at least one embodiment of the present invention. In alternative embodiments, the steps of workflow 200 may be performed by any other program (not shown) in conjunction with the central optimization program 112. It should be appreciated that embodiments of the present invention at least enable the determination of an optimized location. However, FIG. 2 merely provides an example of one implementation and does not imply any limitations with respect to the environments in which different embodiments may be implemented. Many modifications to the illustrated environment may be made by one of ordinary skill in the art without departing from the scope of the present invention as defined by the appended claims. In a preferred embodiment, a user may invoke workflow 200 via a user interface (not shown) when the user wishes to determine an optimized location for data (i.e., audio, video, etc.) transfer within network 140.

[0024] The central optimization program 112 receives data (step 202). In step 202, the central optimization program 112 receives data from one or more of the computing devices 120, IoT devices 130-1, IoT devices 130-2, or IoT devices 130-n, or a combination thereof. In one embodiment, the data may be received over the network 140 and stored in the information repository 114. In one embodiment, the data for each device may include, but is not limited to, signal strength, season of the year, weather conditions, location type, azimuth angle, determined network congestion at a given time at the location, availability of completed calls at a given time at the location, and historical success rates at a given time.

[0025] In one embodiment, signal strength is measured in dBm (a unit of measurement used to indicate power levels expressed in decibels relative to 1 milliwatt), with 0 dBm being no signal and more negative dBm (e.g., -50 dBm) being better signal strength. In one embodiment, signal strength can be a single signal strength at the time of sending data, a signal strength recorded at a particular location where the device was located, an average signal strength during data transfer at the device, or any combination. In one embodiment, the season of the year is selected from spring, summer, fall, and winter based on the date the data was sent. In one embodiment, weather conditions can be recorded on the device when the information is sent to the central optimizer 112. In an alternative embodiment, when the central optimizer 112 receives information about data sent over the network 140, the central optimizer 112 can coordinate with another program (i.e., a weather program) not shown to determine weather conditions at the location where the data was transferred from the computing device and / or IoT device. In one embodiment, the weather conditions include, but are not limited to, temperature, local wind storms, local lightning, local rain, and humidity. In one embodiment, the location type may include, but is not limited to, indoor or outdoor. In one embodiment, the azimuth angle may include, but is not limited to, the position, height, and horizontal orientation of a communication device (i.e., antenna) found on a computing device 120 or IoT device 130-n.

[0026] In one embodiment, the determined network congestion at a given time is based on queuing delays and packet loss within the network 140, more specifically, queuing delays and packet loss at the end nodes (i.e., cell towers) of the network 140 that are in direct communication with the device. In one embodiment, the effectiveness of completing a call at a given time can be based on natural language processing of data transfers. For example, if a user is complaining that the call was of very poor quality, or if a user cannot hear other users, they may engage in a "can you hear me" conversation. In one embodiment, the historical success rate is a measure of seamless use of the available network with no recorded packet loss / queuing delays. In one embodiment, a high number of instances of location coordinates recording a location as optimal is an indication of a good success rate.

[0027] In one embodiment, the central optimizer 112 may receive input from a user via a computing device 120 or an IoT device 130-n regarding the effectiveness and / or success of the data transfer. In one embodiment, the user input may be binary (i.e., good or bad). In an alternative embodiment, the user input may be scaled (i.e., 0-100, where 0 is bad and 100 is good).

[0028] The central optimization program 112 determines an optimization location (step 204). In step 204, the central optimization program 112 uses matrix factorization to determine an optimization location using the data received in step 202. In one embodiment, the central optimization program 112 may determine a single optimization location for all received data. In an alternative embodiment, the central optimization program 112 may determine one or more optimization locations for a physical area covered by end nodes (i.e., cell towers) of the network 140. In yet another alternative embodiment, the central optimization program 112 may determine one or more optimization locations for a physical area. In one embodiment, a physical area may be covered by one or more end nodes (i.e., cell towers) of the network 140. In one embodiment, if a large number of devices provide data to the central optimization program 112 indicating whether a location is good or bad for data transfer over the network 140, the confidence level regarding the accuracy of that physical location for data transfer will increase. In one embodiment, the determined optimization locations are in a list for each area.

[0029] The central optimization program 112 determines whether a threshold has been reached (decision step 206). In one embodiment, the threshold may be a time threshold. In other words, whether a time threshold has been met. In an alternative embodiment, the threshold may be a number of data points. In other words, whether a threshold amount of new data has been added. In yet another alternative embodiment, the threshold may be a number of changes in the determined optimized locations. In other words, whether a threshold number of the determined optimized locations have changed locations compared to the location prior to the determined optimized location. For example, whether the determined optimized location A has moved a threshold amount (i.e., 500 feet (152 meters)). In one embodiment, if the central optimization program 112 determines that the threshold has not been reached (decision step 206, no branch), processing continues to step 202. In one embodiment, if the central optimization program 112 determines that the threshold has been reached (decision step 206, yes branch), processing continues to step 208.

[0030] The central optimization program 112 transmits the optimized location (step 208). In one embodiment, the central optimization program 112 may transmit the optimized location in response to a request from a computing device 120. In one embodiment, the central optimization program 112 may transmit the optimized location to all computing devices that have opted-into receiving optimized locations from the central optimization program 112. In one embodiment, the central optimization program 112 may transmit the optimized location in response to a query from a local optimization program 122, discussed below, without necessarily reaching a threshold.

[0031] In one embodiment, the central optimization program 112 may transmit all optimized locations that it determines. In one embodiment, the central optimization program 112 may transmit the optimized location for the last end node (i.e., cell tower) of the network 140 to which the computing device 120 is connected. In one embodiment, the central optimization program 112 may transmit optimized locations within a threshold distance of the location of the computing device 120.

[0032] FIG. 3 is a flowchart diagram of a workflow 300 illustrating the operational steps of the local optimization program 122 for applying an optimized location, in accordance with at least one embodiment of the present invention. In alternative embodiments, the steps of workflow 300 may be performed by any other program (not shown) in conjunction with the local optimization program 122. It should be understood that embodiments of the present invention enable at least the application of an optimized location. However, FIG. 3 merely provides an example of one implementation and does not imply any limitations with respect to the environments in which different embodiments may be implemented. Many modifications to the illustrated environment may be made by one skilled in the art without departing from the scope of the present invention as defined in the claims. In a preferred embodiment, a user can invoke workflow 300 via a user interface (not shown) when the user wishes to determine an optimized location.

[0033] The local optimization program 122 receives instructions (step 302). In a first embodiment, a user instructs the local optimization program 122 via a user interface (not shown) of the computing device 120 to determine an optimized location for a data transfer (i.e., text message, voice call, video call, etc.). In an alternative embodiment, the local optimization program 122 receives an instruction from another program (not shown) indicating that the signal strength is below a threshold. In other words, there is a low-quality signal. In one embodiment, these instructions may occur before, during, or after the data transfer event.

[0034] The local optimization program 122 determines the optimization location (step 304). In one embodiment, the local optimization program 122 may determine the optimization location by querying the central optimization program 112 and receiving the determined optimization location via step 208. In one embodiment, the local optimization program 122 may have previously received the determined optimization location from the central optimization program 112 and stored the determined optimization location in the information repository 124.

[0035] In one embodiment, as described above, local optimization program 122 may receive all determined optimization locations from central optimization program 112 and store the determined optimization locations in information repository 124. In this embodiment, local optimization program 122 may determine a particular optimization location based on the carrier used by computing device 120, or based on the physical location of computing device 120 (i.e., which optimization location is closest to the physical location of computing device 120), or both.

[0036] The local optimization program 122 communicates the optimization location (step 306). In step 306, the local optimization program 122 communicates the optimization location to a user and / or IoT device 130-n. In one embodiment, the local optimization program 122 may communicate the coordinates of the determined optimization location to a user via a user interface. In other words, a visual or audible representation of the coordinates, or both, may be sent to the user via the user interface and / or the computing device 120. In one embodiment, the local optimization program 122 may communicate the coordinates of the determined optimization location to another program (not shown). For example, the local optimization program 122 may communicate the coordinates to a mapping program of the computing device 120 to provide directions to the determined optimization location. In one embodiment, the local optimization program 122 may determine the IoT device 130-n closest to the determined optimization location, and the IoT device 130-n may execute instructions of the determined optimization location, including, but not limited to, an audible indication, a visual indication, a holographic indication, etc. In one embodiment, the instructions may include a tag of the wireless network's service provider to indicate to the user that this location may be optimal for the user if the user is on that provider's wireless network.

[0037] The local optimizer 122 provides data (step 308). In step 308, the local optimizer 122 provides data to the central optimizer 112. In one embodiment, step 308 is a providing step of the data received in step 202. In other words, the provided data may include, but is not limited to, signal strength, season of the year, weather conditions, type of location, azimuth angle, determined network congestion at a given time at the location, and network congestion at a given time at the location. The information includes the effectiveness of completed calls at a given time, and the history of success rates at a given point in time. In one embodiment, the local optimizer 122 can receive an indication from the user via the user interface of the computing device 120 indicating whether a particular location where the data transfer occurred was good or bad for the data transfer. In one embodiment, this can be a binary decision (i.e., 1=good, 2=bad) or a scaled decision (i.e., 1-10, with 1 being best and 10 being worst). In one embodiment, the local optimizer 122 can perform natural language processing on the spoken and / or written data transfer to determine whether the user indicated whether the data transfer was positive or negative, similar to the instructions received from the user just discussed. In one embodiment, the natural language processing would be based on an opt-in system that occurs only when the user opts in to the service.

[0038] FIG. 4 is a block diagram illustrating components of a computer 400 suitable for central optimizer 112 and local optimizer 122 in accordance with at least one embodiment of the present invention. FIG. 4 illustrates computer 400, one or more processors 404 (including one or more computer processors), a communications fabric 402, memory 406 including RAM 416 and cache 418, persistent storage 408, a communications unit 412, an I / O interface 414, a display 422, and external devices 420. It should be understood that FIG. 4 is merely provided as an example of one embodiment and is not intended to imply any limitation with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environment may be made.

[0039] As shown, computer 400 operates via a communications fabric 402, which provides communications between computer processor 404, memory 406, persistent storage 408, communications unit 412, and input / output (I / O) interface 414. Communications fabric 402 may be implemented with any architecture suitable for passing data or control information between processor 404 (e.g., a microprocessor, communications processor, and network processor), memory 406, external devices 420, and any other hardware components in the system. For example, communications fabric 402 may be implemented with one or more buses.

[0040] Memory 406 and persistent storage 408 are computer-readable storage media. In the illustrated embodiment, memory 406 includes random access memory (RAM) 416 and cache 418. In general, memory 406 may include any suitable volatile or non-volatile computer-readable storage medium or media.

[0041] Program instructions for central optimizer 112 and local optimizer 122 may be stored in persistent storage 408, or more generally, any computer-readable storage medium, for execution by one or more of respective computer processors 404 via one or more memories in memory 406. Persistent storage 408 may be a magnetic hard disk drive, a solid-state disk drive, a semiconductor storage device, a read-only memory (ROM), an electronically erasable programmable read-only memory (EEPROM), a flash memory, or any other computer-readable storage medium capable of storing program instructions or digital information.

[0042] The media used by persistent storage 408 may also be removable. For example, a removable hard drive may be used for persistent storage 408. Other examples include optical and magnetic disks, thumb drives, and smart cards that are inserted into a drive for transfer to another computer-readable storage medium that is also part of persistent storage 408.

[0043] Communications unit 412, in these examples, provides for communication with other data processing systems or devices. In these examples, communications unit 412 may include one or more network interface cards. Communications unit 412 may provide for communication via the use of either or both physical and wireless communications links. In the context of some embodiments of the present invention, sources of various input information data may be physically remote from computer 400, such that input data is received and output is similarly transmitted via communications unit 412.

[0044] The I / O interface 414 enables data input and output to and from other devices capable of operating in conjunction with the computer 400. For example, the I / O interface 414 may provide a connection to an external device 420, which may be a keyboard, keypad, touch screen, or other suitable input device. The external device 420 may further include portable computer-readable storage media, such as thumb drives, portable optical or magnetic disks, and memory cards. Software and data used to practice embodiments of the present invention may be stored on such portable computer-readable storage media or loaded into persistent storage 408 via the I / O interface 414. The I / O interface 414 may also be connected to a display 422. The display 422 provides a mechanism for displaying data to a user and may be, for example, a computer monitor.

[0045] The present invention may be a system, method, or computer program product, or a combination thereof, integrated at any possible level of technical detail. The computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions for causing a processor to perform aspects of the present invention.

[0046] A computer-readable storage medium may be a tangible device capable of retaining and storing instructions for use by an instruction execution device. A computer-readable storage medium may be, for example, but 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 computer-readable storage media includes the following: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disks (DVDs), memory sticks, floppy disks, mechanically encoded devices such as punch cards or ridge-in-groove structures with instructions recorded thereon, and any suitable combination of the foregoing. As used herein, computer-readable storage media should not be construed as being ephemeral signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses passing through fiber optic cable), or electrical signals transmitted through wires.

[0047] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to each computing / processing device or to an external computer or storage device via a network, such as the Internet, a local area network, a wide area network, or a wireless network, or a combination thereof. The network may include copper transmission cables, fiber optic transmission cables, wireless transmissions, routers, firewalls, switches, gateway computers, or edge servers, or a combination thereof. A network adapter card or network interface within each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage on a computer-readable storage medium within the respective computing / processing device.

[0048] Computer-readable program instructions for carrying out the operations of the present invention can be either source or object code written in any combination of one or more programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or object code, including object-oriented programming languages ​​such as Smalltalk®, C++, and the like, and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions can execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be to an external computer (e.g., through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA) can execute computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry to perform aspects of the present invention.

[0049] 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.

[0050] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to create a machine, such that the instructions, which execute on the processor of the computer or other programmable data processing apparatus, create means for performing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams. These computer-readable program instructions may also be stored on a computer-readable storage medium that can instruct a computer, programmable data processing apparatus, or other device, or combination thereof, to function in a particular way, such that the computer-readable storage medium on which the instructions are stored constitutes an article of manufacture containing instructions that implement aspects of the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0051] The computer-readable program instructions may also be loaded into a computer, other programmable data processing apparatus, or other device to cause the computer, other programmable apparatus, or other device to perform a series of operational steps to create a computer-implemented process, such that the instructions, which execute on the computer, other programmable apparatus, or other device, perform the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0052] 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 flowcharts or block diagrams may represent a module, segment, or portion of computer program instructions, which comprise one or more executable instructions for implementing specified logical functions. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may actually be accomplished as a single step that is executed concurrently, substantially concurrently, partially, or fully overlapping in time, or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, are implemented in a dedicated hardware-based system that performs the specified functions or operations or executes a combination of dedicated hardware instructions and computer instructions.

[0053] The description of various embodiments of the present invention has been presented for illustrative purposes, but is not intended to be exhaustive or limited to the disclosed embodiments. Many changes and modifications will be apparent to those skilled in the art without departing from the scope of the described embodiments. The terms used herein have been chosen to best explain the principles of the embodiments, practical applications, or technical improvements over technologies found in the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

Claims

1. 1. A method for computer-implemented wireless communication, said method comprising: receiving, by one or more computer processors, instructions for wireless communication being performed by a computing device; In response to receiving the instruction, determining, by one or more computer processors, an optimized location for conducting the wireless communication based on a location of the computing device and an optimized location list; communicating, by one or more computer processors, the optimized location to the computing device communicating the wireless communication, wherein the communicating comprises communicating, by one or more computer processors, a location indication of the optimized location based on a location of the wireless communication to an Internet of Things device, the indication including causing the Internet of Things device to provide a notification, the notification being selected from the list consisting of audible, visual, and holographic; A method comprising:

2. communicating, by one or more computer processors, the optimized location to the computing device communicating the wireless communication; communicating, by one or more computer processors, physical coordinates of the optimized location based on the location of the wireless communication to a device communicating the wireless communication. The method of claim 1 , comprising:

3. The optimized location list comprises: receiving, by one or more computer processors, a plurality of data; determining, by one or more computer processors, the optimized location list for a plurality of locations based on the plurality of data; The method of claim 1 , wherein the ion exchange layer is produced by including:

4. 4. The method of claim 3, wherein the data belonging to the plurality of data is selected from the group consisting of signal strength of the computing device, season of the year at the location of the computing device, weather conditions at the location of the computing device, location type relative to the location of the computing device, azimuth angle of the location of the computing device, determined network congestion at the location at a given time, effectiveness of completing calls at the location at a given time, and historical success rate at a given time.

5. The method of claim 3 , wherein the data is received from an Internet of Things device.

6. determining, by one or more computer processors, whether a threshold event has occurred; receiving, by one or more computer processors, updated data in response to determining that the threshold event has not occurred; updating, by one or more computer processors, the optimized location list using the received update data; and The method of claim 3 further comprising:

7. A computer program causing one or more computer processors to carry out the method of any one of claims 1 to 6.

8. A computer-readable storage medium having the computer program of claim 7 stored thereon.

9. 1. A computer system for wireless communication, said computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the one or more computer-readable storage media for execution by at least one of the one or more computer processors; Including, The program instructions: program instructions for receiving instructions, the instructions being for wireless communication being conducted by a computing device; program instructions for, in response to receiving the instruction, determining an optimized location for conducting the wireless communication based on a location of the computing device and an optimized location list; and program instructions for communicating the optimized location to the computing device communicating the wireless communication, wherein the communicating comprises communicating a location indication of the optimized location to an Internet of Things device based on a location of the wireless communication, the instructions including causing the Internet of Things device to provide a notification, the notification being selected from the list consisting of audible, visual, and holographic. Including, Computer systems.

10. the program instructions for communicating the optimized location to the computing device communicating with the wireless communication; and communicating physical coordinates of the optimized location based on the location of the wireless communication to the device communicating the wireless communication.

10. The computer system of claim 9, comprising program instructions for:

11. The optimized location list comprises: Receive multiple data 10. The computer system of claim 9, wherein the computer system is produced by including program instructions for determining the optimized location list for a plurality of locations based on the plurality of data.

12. 12. The computer system of claim 11, wherein the data belonging to the plurality of data is selected from the group consisting of signal strength of the computing device, season of the year at the location of the computing device, weather conditions at the location of the computing device, location type relative to the location of the computing device, azimuth angle of the location of the computing device, determined network congestion at the location at a given time, effectiveness of completing calls at the location at a given time, and historical success rates at a given time.

13. The computer system of claim 11 , wherein the data is received from an Internet of Things device.

14. program instructions for determining, by one or more computer processors, whether a threshold event has occurred; program instructions for receiving, by one or more computer processors, updated data in response to determining that the threshold event has not occurred; program instructions for updating, by one or more computer processors, the optimized location list using the received update data; 12. The computer system of claim 11, further comprising:

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