Location optimization in a communications network

Abstract

An indication is received. The indication is for wireless communication by a computing device. In response to receiving the indication, an optimized location for the wireless communication is determined based on a location of the computing device and a list of optimized locations. The optimized location is communicated to the computing device for the wireless communication.

Description

Background Technology

[0001] This invention relates generally to the field of communication networks, and more specifically to the optimization of signal quality in communication networks.

[0002] Last link wireless communication networks are also known as cell networks or mobile networks. A network (specifically, the last wireless link) extends over 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 used by one or more providers. The network allows wireless communication via devices including, but not limited to, mobile phones, tablets, laptops, pagers, etc., provided they have portable transceivers included within or (physically or wirelessly) attached to the device. Summary of the Invention

[0003] Embodiments of the present invention disclose a computer-implemented method, computer program product, and system for wireless communication. In one embodiment, an instruction is received. The instruction is for wireless communication performed by a computing device. In response to receiving the instruction, an optimal location for performing wireless communication is determined based on the location of the computing device and a list of optimal locations. The optimal location is transmitted to the computing device performing the wireless communication. Attached Figure Description

[0004] Figure 1 This is a functional block diagram of a network computing environment suitable for the operation of a central optimization program 112 according to at least one embodiment of the present invention, the network computing environment being generally designated as 100.

[0005] Figure 2 This is a flowchart depicting the operational steps of a central optimization procedure 112 for determining an optimal position according to at least one embodiment of the present invention.

[0006] Figure 3 This is a flowchart depicting the operational steps of a local optimization program 122 for applying optimized location according to at least one embodiment of the present invention.

[0007] Figure 4 It is a block diagram depicting components of a computer (generally designated 400) that executes a central optimization program 112 and a local optimization program 122 according to at least one embodiment of the present invention. Detailed Implementation

[0008] This invention provides a method, computer program product, and computer system for determining an optimal location in a network for communication and providing the determined optimal location to a computing device. Embodiments of this invention recognize that when a user transmits data (including but not limited to text messages, voice calls, video calls, etc.) on their computing device, the user may experience poor service from the network due to the physical location of the computing device used for data transmission. Embodiments of this invention recognize that many users may move around physically, attempting to find a better physical location for their computing device to connect to the network with better signal strength and thus better data connectivity.

[0009] Embodiments of the present invention provide a program for a computing device to determine optimal locations for data transmission and subsequently provide these optimal locations to a user. Embodiments of the present invention provide the computing device with directions to the user on how to physically reach the determined optimal locations. Embodiments of the present invention provide a program for understanding optimal locations within a wireless communication network to determine the best or optimal location for data transmission; the wireless communication network may be a telecommunications network or a Wi-Fi network.

[0010] Reference will now be made in more detail to the various embodiments of the invention. Figure 1 This is a functional block diagram of a network computing environment (generally designated as 100) suitable for the operation of a central optimization program 112 and a local optimization program 112, according to at least one embodiment of the present invention. Figure 1 This illustration provides only one implementation and does not imply any limitation regarding the environments in which different embodiments may be implemented. Those skilled in the art can make numerous modifications to the described environments without departing from the scope of the invention as set forth in the claims.

[0011] The network computing environment 100 includes server devices 110, computing devices 120, and IoT devices 130-1 to 130-n interconnected via a network 140. In embodiments of the 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 all 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 comprising voice, data, and video). Generally, network 140 may be any combination of connections and protocols supporting communication between server devices 110, computing devices 120, IoT devices 130-1 to 130-n, and other computing devices (not shown) within the network computing environment 100.

[0012] In one embodiment, network 140 may include cell towers as part of a communication network, which is a wireless cell network. The cell network may include "cells" covering a physical land area using at least one fixed-location transceiver, but may include three or more cell stations and / or base transceivers. These fixed-location transceivers and / or base transceivers can provide the transmission of voice, data, and other types of content by connecting to other communication devices as part of network 140.

[0013] Server device 110 is a computing device, which may be a laptop computer, tablet computer, netbook computer, personal computer (PC), desktop computer, personal digital assistant (PDA), smartphone, smartwatch, or any programmable electronic device capable of receiving, sending, and processing data. Generally, server device 110 refers to 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 via a network (e.g., network 140).

[0014] In various embodiments of the invention, server device 110 may be a computing device, which may be a standalone device, management server, web server, media server, mobile computing device, or any other programmable electronic device or computing system capable of receiving, transmitting, and processing data. In other embodiments, server device 110 represents a server computing system, such as one that utilizes multiple computers as server systems in a cloud computing environment. In embodiments, server device 110 represents a computing system utilizing clustered computers and components (e.g., database server computers, application server computers, web servers, and media servers) that act as a single, seamless resource pool when accessed within the network computing environment 100.

[0015] In this 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 the user, as well as the control sequences the user uses to control the program. Many types of user interfaces exist. In one embodiment, the user interface may be a graphical user interface (GUI). A GUI is a type of user interface that allows a user to interact with an electronic device such as a keyboard and mouse through graphical icons and visual indicators (such as secondary symbols), as opposed to text-based interfaces, typed command labels, or text navigation. In computers, GUIs were introduced as a response to the perceptually steep learning curve of command-line interfaces, which require typing commands on a keyboard. Actions in a GUI are often performed through direct manipulation of graphical elements.

[0016] In an embodiment, server device 110 includes a central optimization program 112. Embodiments of the present invention provide a central optimization program 112 for determining an optimization position. In an embodiment, the central optimization program 112 receives one or more data entries. In an embodiment, the central optimization program 112 determines the optimization position based on the received data. In an embodiment, the central optimization program 112 determines whether a threshold has been reached. In an embodiment, if the threshold has been reached, the central optimization program 112 transmits the optimization position. In an embodiment, if the threshold has not been met, the central optimization program 112 receives data.

[0017] In one embodiment, server device 110 includes an information storage repository 114. In another embodiment, the information storage repository 114 may be managed by a central optimization program 112. In an alternative embodiment, the information storage repository 114 may be managed by the operating system of server device 110, another program (not shown), either alone or in conjunction with the central optimization program 112. The information storage repository 114 is a data repository capable of storing, collecting, and / or analyzing information. In some embodiments, the information storage repository 114 is located outside server device 110 and accessed via a communication network (such as network 140). In some embodiments, the information storage repository 114 is stored on server device 110. In some embodiments, the information storage repository 114 may reside on another computing device (not shown), provided that the information storage repository 114 is accessible by server device 110. In another embodiment, the information storage repository 114 may include location information, including but not limited to signal strength, season of the year, weather conditions, location type, azimuth, network congestion at a given time point, the validity of completed calls at that location at a given time point, and historical success rate at a given time point. In an embodiment, the information storage 114 may include an optimized location list, physical layout information of various parts of the network 140 (i.e., wireless network layout, tower layout, cell structure, etc.) and carrier information.

[0018] As is known in the art, information storage 114 can be implemented using any volatile or non-volatile storage medium for storing information. For example, information storage 114 can be implemented using a tape library, an optical library, one or more individual 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 storage 114 can be implemented using any suitable storage architecture known in the art, such as a relational database, an object-oriented database, or one or more tables.

[0019] Computing device 120 can be a laptop computer, tablet computer, netbook computer, personal computer (PC), desktop computer, personal digital assistant (PDA), smartphone, smartwatch, or any programmable electronic device capable of receiving, sending, and processing data. Generally, computing device 120 means 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 via a network (such as network 140).

[0020] In various embodiments of the invention, computing device 120 may be a standalone device, management server, network server, media server, mobile computing device, or any other programmable electronic device or computing system capable of receiving, transmitting, and processing data. In other embodiments, computing device 120 represents a server computing system, such as one that utilizes multiple computers as server systems in a cloud computing environment. In one embodiment, computing device 120 represents a computing system utilizing clustered computers and components (e.g., database server computers, application server computers, web servers, and media servers) that act as a single, seamless resource pool when accessed within the network computing environment 100.

[0021] In this 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 the user, as well as the control sequences the user uses to control the program. Many types of user interfaces exist. In one embodiment, the user interface may be a graphical user interface (GUI). A GUI is a type of user interface that allows a user to interact with an electronic device such as a keyboard and mouse through graphical icons and visual indicators (such as secondary symbols), as opposed to text-based interfaces, typed command labels, or text navigation. In computers, GUIs were introduced as a response to the perceptually steep learning curve of command-line interfaces, which require typing commands on a keyboard. Actions in a GUI are often performed through direct manipulation of graphical elements.

[0022] In an embodiment, computing device 120 includes a local optimizer 122. Embodiments of the invention provide a local optimizer 122 for applying an optimized location. In an embodiment, the local optimizer 122 receives an instruction. In an embodiment, the local optimizer 122 determines an optimized location. In an embodiment, the local optimizer 122 transmits the optimized location. In an embodiment, the local optimizer 122 provides data to a central optimizer 112.

[0023] In one embodiment, computing device 120 includes an information storage repository 124. In another embodiment, the information storage repository 124 may be managed by a local optimization program 122. In an alternative embodiment, the information storage repository 124 may be managed by the operating system of computing device 120, another program (not shown), either alone or in conjunction with the local optimization program 122. The information storage repository 124 is a data repository capable of storing, collecting, and / or analyzing information. In some embodiments, the information storage repository 124 is located external to computing device 120 and accessed via a communication network (such as network 140). In some embodiments, the information storage repository 124 is stored on computing device 120. In some embodiments, the information storage repository 124 may reside on another computing device (not shown), provided that the information storage repository 124 is accessible by computing device 120. In another embodiment, the information storage repository 124 may include location information, including but not limited to signal strength, season of the year, weather conditions, location type, azimuth, network congestion at a given time point, the validity of completed calls at that location at a given time point, and historical success rate at a given time point. In one embodiment, the information storage 124 may include optimized location and operator information.

[0024] As is known in the art, the information repository 124 can be implemented using any volatile or non-volatile storage medium for storing information. For example, the information repository 124 can be implemented using 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 124 can be implemented using any suitable storage architecture known in the art, such as a relational database, an object-oriented database, or one or more tables.

[0025] 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 / from network 140. In this embodiment, IoT device 130-n can be any number of IoT devices. In other words, for ease of discussion, only three IoT devices 130 are shown in the network computing environment 100; however, any number of IoT devices 130-n communicating within the network computing environment 100 may exist. In this embodiment, IoT device 130-n can be a computing device, which may be a laptop computer, tablet computer, netbook computer, personal computer (PC), desktop computer, personal digital assistant (PDA), smartphone, smartwatch, or any programmable electronic device capable of receiving, transmitting, and processing data. Generally, computing device 120 refers to 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 via a network (such as network 140). In this embodiment, IoT device 130-n may collect and / or transmit any amount of data, including but not limited to signal strength, season of the year, weather conditions, location type, azimuth, network congestion at the location at a given time point, validity of calls completed at the location at a given time point, and historical success rate at the given time point. In this embodiment, IoT device 130-n may record packet loss for communications completed on IoT device 130-n.

[0026] Figure 2 This is a flowchart depicting the operational steps of a central optimization program 112 for determining an optimal location according to 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) while working in conjunction with the central optimization program 112. It should be understood that embodiments of the present invention provide at least the means for determining an optimal location. However, Figure 2 This is merely an illustration of one implementation and does not imply any limitation regarding the environment in which different embodiments may be implemented. Those skilled in the art will make many modifications to the described environment without departing from the scope of the invention as set forth in the claims. In a preferred embodiment, when a user wants to determine the optimal location for data (i.e., audio, video, etc.) transmission in network 140, the user can invoke workflow 200 through a user interface (not shown).

[0027] Central optimization program 112 receives data (step 202). In step 202, RDBMS 112 receives data from one or more of computing device 120, IoT device 130-1, IoT device 130-2, or IoT device 130-n. In an embodiment, data may be received via network 140 and stored in information storage 114. In an embodiment, the data for each device may include (but is not limited to) signal strength, season of the year, weather conditions, location type, azimuth, network congestion at a given point in time determining the location, validity of completed calls at the given point in time at the location, and historical success rate at the given point in time.

[0028] In this embodiment, signal strength is measured in dBm (a unit used to indicate power levels, with reference to a milliwatt level expressed in decibels), where 0 dBm represents no signal, and a larger negative dBm (e.g., -50 dBm) indicates better signal strength. In this embodiment, signal strength can be a single signal strength when data is transmitted, a signal strength recorded at certain locations where the device has been positioned, an average signal strength during data transmission on the device, or any combination thereof. In this embodiment, a season of the year is selected from spring, summer, autumn, and winter based on the date the data is transmitted. In this embodiment, weather conditions can be recorded on the device when information is sent to the central optimization program 112. In an alternative embodiment, when the central optimization program 112 receives information about data transmitted via network 140, the central optimization program 112 can work with another program (i.e., a weather program, not shown) to determine weather conditions at the location where the data is transmitted from the computing device and / or IoT device. In this embodiment, weather conditions include, but are not limited to, temperature, storms in the region, brightness changes in the region, rain in the region, and humidity. In this embodiment, location type can include, but is not limited to, indoor or outdoor. In embodiments, the azimuth angle includes, but is not limited to, the position, height, and horizontal direction of the communication device (i.e., antenna) found in the computing device 120 or IoT device 130-n.

[0029] In this embodiment, network congestion determined at a given point in time is based on queuing delays and packet loss within network 140, and more specifically, on the end nodes (i.e., cell towers) of network 140 that communicate directly with the device. In this embodiment, the validity of a call completed at a given point in time can be based on natural language processing of data transmission. For example, if a user expresses frustration with poor call quality, or if a user cannot hear other users, they are in the state "Can you hear me?" In this embodiment, historical success rate is a measure of seamless network usage without any recorded packet / queuing delay losses. In this embodiment, recording more instances of optimal location coordinates is a good factor in informing success rates.

[0030] In one embodiment, the central optimization program 112 may receive input from the user regarding the validity and / or success of data transmission via its computing device 120 or IoT device 130-n. In another embodiment, the user input may be binary (i.e., good or bad). In a different embodiment, the user input may be scaled (i.e., 0-100, where 0 is bad and 100 is good).

[0031] Central optimization procedure 112 determines an optimized location (step 204). In step 204, central optimization procedure 112 uses matrix factorization to determine the optimized location using the data received in step 202. In an embodiment, central optimization procedure 112 may determine a single optimized location for the received data. In an alternative embodiment, central optimization procedure 112 may determine one or more optimized locations for a physical area covered by the end nodes (i.e., cell towers) of network 140. In yet another alternative embodiment, central optimization procedure 112 may determine one or more optimized locations for a physical area. In an embodiment, the physical area may be covered by one or more end nodes (i.e., cell towers of network 140). In an embodiment, if a larger number of devices provide central optimization procedure 112 with data indicating whether the location is good or bad for data transmission through network 140, the confidence level regarding the accuracy of the physical location used for data transmission will increase. In an embodiment, the determined optimized locations are in a list by region.

[0032] Central optimization procedure 112 determines whether a threshold has been reached (decision step 206). In an embodiment, the threshold may be a time threshold. In other words, the time threshold has been met. In an alternative embodiment, the threshold may be the number of data points. In other words, the threshold amount of new data added. In yet another alternative embodiment, the threshold may be the number of changes to the determined optimized position. In other words, the position of the determined optimized position change relative to the previous position in the determined optimized positions, with a threshold number of changes. For example, the threshold amount of movement of optimized position A has been determined (i.e., 500 feet). In an embodiment, if central optimization procedure 112 determines that the threshold has not been reached (decision step 206, no branch), the process proceeds to step 202. In an embodiment, if central optimization procedure 112 determines that the threshold has been reached (decision step 206, yes branch), the process proceeds to step 208.

[0033] Central optimization program 112 transmits the optimized location (step 210). In an embodiment, central optimization program 112 may transmit the optimized location in response to a request from computing device 120. In an embodiment, central optimization program 112 may transmit the optimized location to all computing devices selected by central optimization program 112 to receive the optimized location. In an embodiment, central optimization program 112 may transmit the optimized location in response to a query from local optimization program 122, as discussed below, and does not necessarily have to reach a threshold.

[0034] In one embodiment, the central optimization program 112 may send all optimized central locations determined by the central optimization program 112. In another embodiment, the optimization program 112 may send the optimized location of the rearmost node (i.e., cell tower) of the network 140 to which the computing device 120 is connected. In yet another embodiment, the central optimization program 112 may send the optimized location within a threshold distance of the location of the computing device 120.

[0035] Figure 3 This is a flowchart depicting the operational steps of a local optimization program 122 for applying optimized location according to 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) while working in conjunction with the local optimization program 122. It should be understood that embodiments of the present invention provide at least for applying optimized location. However, Figure 3 This illustration is provided only to illustrate one implementation and does not imply any limitation regarding the environment in which different embodiments may be implemented. Those skilled in the art can make many modifications to the described environment without departing from the scope of the invention as set forth in the claims. In a preferred embodiment, the user can invoke workflow 300 via a user interface (not shown) when the user wants to determine the optimization location.

[0036] Local optimization program 122 receives an instruction (step 302). In a first embodiment, the user instructs local optimization program 122 via a user interface (not shown) on computing device 120 to determine an optimized location for data transmission (i.e., text messages, voice calls, video calls, etc.). In an alternative embodiment, local optimization program 122 receives an instruction from another program (not shown) indicating that the signal strength is below a threshold amount. In other words, a poor signal exists. In embodiments, this instruction may be given before, during, or after the data transmission event.

[0037] The local optimization program 122 determines the optimization location (step 304). In an embodiment, the local optimization program 122 can determine the optimization location by querying the central optimization program 112 and receive the determined optimization location via step 208. In an 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 storage 124.

[0038] In this embodiment, the local optimization program 122 may receive all determined optimization positions from the central optimization program 112 and store the determined optimization positions in the information storage 124, as described above. In this embodiment, the local optimization program 122 may determine a specific optimization position based on the carrier being used by the computing device 120 and / or based on the physical location of the computing device 120 (i.e., which optimization position is closest to the physical location of the computing device 120).

[0039] Local optimization program 122 transmits the optimized location (step 306). In step 306, local optimization program 122 transmits the optimized location to the user and / or IoT device 130-n. In an embodiment, local optimization program 122 may transmit the coordinates of the determined optimized location to the user via a user interface. In other words, a visual and / or auditory representation of the coordinates may be sent to the user via a user interface and / or computing device 120. In an embodiment, local optimization program 122 may transmit the coordinates of the determined optimized location to another program (not shown). For example, local optimization program 122 may transmit the coordinates to a mapping program on computing device 120 to provide direction to the determined optimized location. In an embodiment, local optimization program 122 may determine the IoT device 130-n closest to the determined optimized location, and IoT device 130-n may perform an instruction on the determined optimized location, including but not limited to audible instructions, visual instructions, holographic instructions, etc. In an embodiment, the instruction may include a service provider's tag for the wireless network to indicate to the user that this location may be optimal for them if they are on the provider's wireless network.

[0040] Local optimization program 122 provides data (step 308). In step 308, local optimization program 122 provides data to central optimization program 112. In an embodiment, step 308 is a step of providing data received in step 202. In other words, the data provided includes, but is not limited to, signal strength, season of the year, weather conditions, location type, azimuth, determining network congestion at a given time, validity of completed calls at a given time, and historical success rate at a given time. In an embodiment, local optimization program 122 may receive an indication from a user via a user interface on computing device 120, indicating whether a location for data transmission is good or bad for data transmission. In an embodiment, this may be a binary decision (i.e., 1 = good, 2 = bad) or a scaled decision (i.e., 1-10, 1 is best, 10 is worst). In an embodiment, local optimization program 122 may perform natural language processing on voice and / or written data transmission to determine whether the user indication of data transmission is affirmative or negative, similar to the indication just discussed from the user. In this embodiment, natural language processing will be based on an opt-in system that occurs only when a user opts in to join a service.

[0041] Figure 4 This is a block diagram depicting components of a computer 400 adapted for a central optimization program 112 and a local optimization program 122 according to at least one embodiment of the present invention. Figure 4 The system includes a computer 400, one or more processors 404 (including one or more computer processors), a communication structure 402, a memory 406 (including RAM 416 and cache 418), a permanent storage device 408, a communication unit 412, an I / O interface 414, a display 422, and external devices 420. It should be understood that... Figure 4 The illustration is provided only as an example and does not imply any limitation regarding the environment in which different embodiments may be implemented. Many modifications may be made to the depicted environment.

[0042] As depicted, computer 400 operates on communication architecture 402, which provides communication between computer processor 404, memory 406, persistent storage device 408, communication unit 412, and input / output (I / O) interface 414. Communication architecture 402 can be implemented using an architecture suitable for transferring data or control information between processor 404 (e.g., microprocessor, communication processor, and network processor), memory 406, external devices 420, and any other hardware components within the system. For example, communication architecture 402 can be implemented using one or more buses.

[0043] Memory 406 and persistent storage device 408 are computer-readable storage media. In the depicted embodiment, memory 406 includes random access memory (RAM) 416 and cache 418. Typically, memory 406 may include one or more suitable volatile or non-volatile computer-readable storage media.

[0044] Program instructions for the central optimization program 112 and the local optimization program 122 may be stored in permanent storage device 408, or more generally, in any computer-readable storage medium for execution by one or more of the respective computer processors 404 via one or more memories of memory 406. Permanent storage device 408 may be a magnetic hard disk drive, a solid-state drive, a semiconductor storage device, a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory, or any other computer-readable storage medium capable of storing program instructions or digital information.

[0045] The media used by the persistent storage device 408 can also be removable. For example, a removable hard disk drive can be used for the persistent storage device 408. Other examples include optical discs and disks, thumb drives, and smart cards, which are inserted into the drive to be transferred to another computer-readable storage medium that is also part of the persistent storage device 408.

[0046] In these examples, communication unit 412 provides communication with other data processing systems or devices. In these examples, communication unit 412 may include one or more network interface cards. Communication unit 412 can provide communication using physical and / or wireless communication links. In some embodiments of the invention, sources of different input data may be physically located away from computer 400, allowing input data to be received and output similarly transmitted via communication unit 412.

[0047] I / O interface 414 allows for data input and output with other devices that can be operated in conjunction with computer 400. For example, I / O interface 414 can provide a connection to external device 420, which may be a keyboard, keypad, touchscreen, or other suitable input device. External device 420 may also include portable computer-readable storage media, such as thumb drives, portable optical discs or disks, and memory cards. Software and data used to implement embodiments of the invention can be stored on such portable computer-readable storage media and loaded onto permanent storage device 508 via I / O interface 414. I / O interface 414 can similarly be connected to display 422. Display 422 provides a mechanism for displaying data to a user and may be, for example, a computer monitor.

[0048] This invention can be a system, method, and / or computer program product with any possible level of technical detail integration. The computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to execute aspects of the invention.

[0049] Computer-readable storage media can be tangible devices capable of retaining and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes: portable computer disks, 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 universal disk (DVD), memory sticks, floppy disks, mechanical encoding devices such as punched cards, or protrusions in slots having instructions recorded thereon, and any suitable combination of the foregoing. As used herein, computer-readable storage media should not be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

[0050] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a suitable computing / processing device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network), or to an external computer or external storage device. The network may include copper cables, optical fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to a computer-readable storage medium within the suitable computing / processing device.

[0051] Computer-readable program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​(such as Smalltalk, C++, etc.) and conventional procedural programming languages ​​(such as the "C" programming language or similar programming languages). The computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as a standalone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)) or may be connected to an external computer (e.g., via the Internet through an Internet service provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) may execute computer-readable program instructions by utilizing state information from the computer-readable program instructions to personalize the electronic circuitry in order to perform aspects of this invention.

[0052] The present invention will now be described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0053] 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 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 / actions specified in one or more blocks of a flowchart and / or block diagram. These computer-readable program instructions may also be stored in a readable storage medium that can instruct a computer, programmable data processing apparatus, and / or other device to operate in a particular manner, such that the computer-readable storage medium having the instructions stored therein comprises an article of manufacture including instructions for implementing aspects of the functions / actions specified in one or more blocks of a flowchart and / or block diagram.

[0054] 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 computer-implemented processing, such that the instructions executed on the computer, other programmable apparatus, or other device perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0055] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of computer program instructions, including one or more executable instructions for implementing a specified logical function. In some alternative embodiments, the functions indicated in the blocks may not occur in the order shown in the figures. For example, two blocks shown consecutively may actually be completed as a single step, executed simultaneously, substantially simultaneously, or with partial or complete temporal overlap, or the blocks may sometimes be executed in reverse order, depending on the functions 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, may be implemented using a dedicated hardware-based system that performs the specified function or action or executes a combination of dedicated hardware and computer instructions.

[0056] Various embodiments of the invention have been described for illustrative purposes, but are not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope of the described embodiments. The terminology used herein has been chosen to best explain the principles of the embodiments, their practical application, or technical improvements to technologies found in the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

Claims

1. A computer-implemented method for wireless communication, the computer-implemented method comprising: An instruction is received by one or more computer processors, wherein the instruction is for wireless communication performed by a computing device; In response to receiving the instruction, one or more computer processors determine an optimal location for conducting the wireless communication based on the location of the computing device and a list of optimal locations; and The optimized location is transmitted to the computing device performing the wireless communication by one or more computer processors; The process of transmitting the optimized location to the computing device performing the wireless communication by one or more computer processors includes: One or more computer processors transmit a location indication of the optimized location to an Internet of Things (IoT) device based on the location of the wireless communication, wherein the indication includes causing the IoT device to provide a notification, and wherein the notification is selected from a list including audible, visual, and holographic.

2. The computer-implemented method according to claim 1, wherein, Transmitting the optimized location to the computing device performing the wireless communication by one or more computer processors includes: One or more computer processors transmit the physical coordinates of the optimized location to the device performing the wireless communication, based on the location of the wireless communication.

3. The computer-implemented method according to claim 1, wherein, Creating the optimized location list includes: Multiple data are received by one or more computer processors; One or more computer processors determine the list of optimized locations for multiple locations based on the plurality of data.

4. The computer-implemented method according to claim 3, wherein, One of the multiple data is selected from the group consisting of: the signal strength of the computing device, the season of the year at the location of the computing device, the weather conditions at the location of the computing device, the location type of the location of the computing device, the azimuth of the location of the computing device, network congestion determined at a given point in time at the location, the validity of calls completed at a given point in time at the location, and the historical success rate at a given point in time.

5. The computer-implemented method according to claim 3, wherein, The data is received from the Internet of Things (IoT) device.

6. The computer-implemented method according to claim 3 further includes: One or more computer processors determine whether a threshold event has occurred; In response to determining that the threshold event has not yet occurred, one or more computer processors receive updated data; as well as The optimized location list is updated by one or more computer processors using the received update data.

7. A computer program product for wireless communication, the computer program product comprising program instructions that, when executed by a processor, perform the following operations: Receive an instruction, wherein the instruction is for wireless communication performed by a computing device; In response to receiving the instruction, an optimal location for performing the wireless communication is determined based on the location of the computing device and a list of optimal locations; as well as The optimized location is transmitted to the computing device performing the wireless communication; Transmitting the optimized location to the computing device performing the wireless communication includes the following operations: Location indications of the optimized location are transmitted to IoT devices based on the location of the wireless communication, wherein the indications include enabling the IoT devices to provide notifications, and wherein the notifications are selected from a list including audible, visual, and holographic.

8. The computer program product according to claim 7, wherein, Transmitting the optimized location to the computing device performing the wireless communication includes the following operations: The physical coordinates of the optimized location are transmitted to the device performing the wireless communication based on the location of the wireless communication.

9. The computer program product according to claim 7, wherein, Creating the optimized location list includes the following operations: Receive multiple data; The optimized location list is determined for multiple locations based on the aforementioned data.

10. The computer program product according to claim 9, wherein, One of the multiple data is selected from the group consisting of: the signal strength of the computing device, the season of the year at the location of the computing device, the weather conditions at the location of the computing device, the location type of the location of the computing device, the azimuth of the location of the computing device, network congestion determined at a given point in time at the location, the validity of calls completed at a given point in time at the location, and the historical success rate at a given point in time.

11. The computer program product according to claim 9, wherein, The data is received from the Internet of Things (IoT) device.

12. The computer program product of claim 9, further comprising program instructions that, when executed by a processor, implement one or more of the following operations: Determine if a threshold event has occurred; In response to determining that the threshold event has not yet occurred, updated data is received; and The optimized location list is updated using the received update data.

13. A computer system for wireless communication, the computer system comprising: One or more computer processors; One or more computer-readable storage media; as well as 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, the program instructions comprising: Program instructions for receiving instructions, wherein the instructions are for wireless communication by a computing device; In response to receiving the instruction, program instructions are given to determine an optimal location for performing the wireless communication based on the location of the computing device and a list of optimal locations; and Program instructions to transmit the optimized location to the computing device performing the wireless communication. The program instructions for transmitting the optimized location to the computing device performing the wireless communication include program instructions for the following operations: Location indications of the optimized location are transmitted to IoT devices based on the location of the wireless communication, wherein the indications include enabling the IoT devices to provide notifications, and wherein the notifications are selected from a list including audible, visual, and holographic.

14. The computer system according to claim 13, wherein, The program instructions for transmitting the optimized location to the computing device performing the wireless communication include program instructions for the following operations: The physical coordinates of the optimized location are transmitted to the device performing the wireless communication based on the location of the wireless communication.

15. The computer system according to claim 13, wherein, Creating the optimized location list includes program instructions for the following operations: Receive multiple data; The optimized location list is determined for multiple locations based on the aforementioned data.

16. The computer system according to claim 15, wherein, One of the multiple data is selected from the group consisting of: the signal strength of the computing device, the season of the year at the location of the computing device, the weather conditions at the location of the computing device, the location type of the location of the computing device, the azimuth of the location of the computing device, network congestion determined at a given point in time at the location, the validity of calls completed at a given point in time at the location, and the historical success rate at a given point in time.

17. The computer system according to claim 15, wherein, The data is received from the Internet of Things (IoT) device.

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