WO2019061663A1 - Procédé d'optimisation de déploiement de point d'accès sans fil wifi, serveur et support de stockage - Google Patents

Procédé d'optimisation de déploiement de point d'accès sans fil wifi, serveur et support de stockage Download PDF

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Publication number
WO2019061663A1
WO2019061663A1 PCT/CN2017/108771 CN2017108771W WO2019061663A1 WO 2019061663 A1 WO2019061663 A1 WO 2019061663A1 CN 2017108771 W CN2017108771 W CN 2017108771W WO 2019061663 A1 WO2019061663 A1 WO 2019061663A1
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Prior art keywords
hotspot
hotspots
business circle
business
user
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English (en)
Chinese (zh)
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金新
王建明
肖京
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Ping An Technology Shenzhen Co Ltd
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Ping An Technology Shenzhen Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/16—Discovering, processing access restriction or access information

Definitions

  • the present application relates to the field of computer technologies, and in particular, to a Wi-Fi hotspot deployment optimization method, a server, and a computer readable storage medium.
  • Wi-Fi Wireless-Fidelity
  • Wi-Fi Wireless-Fidelity
  • the characteristics of control and restraint, blindness and randomness are very obvious.
  • Consumer electronics products such as mobile phones, game consoles, and portable computers are becoming more and more popular.
  • the richness of terminal products will make the penetration rate of Wi-Fi higher and higher. It is of substantial significance to strengthen the coverage of Wi-Fi signals.
  • the person in the field determines whether the current location of the to-be-arranged space exists by calculating the coverage area of the hot spot, and if so, adjusts the location of the hot spot toward the blind spot outside the coverage area of the hot spot, or at a position close to the blind spot.
  • a hot spot is arranged until the entire location of the space to be laid is covered by at least one hot spot, thereby optimizing the arrangement of the Wi-Fi hotspot.
  • Wi-Fi hotspot deployment needs to be optimized, it is necessary to consider the traffic volume in the business circle and the user satisfaction with the Wi-Fi hotspot in the business circle, so as to be based on user satisfaction and within the business circle.
  • the traffic aggregation area determines what problems exist in the deployment of existing Wi-Fi hotspots. Therefore, how to make full use of Wi-Fi hotspots, adjust the location of existing Wi-Fi hotspot deployments, and increase the signal coverage of Wi-Fi hotspots.
  • the crowd improving the user's online experience, is an urgent problem to be solved.
  • the present application provides a Wi-Fi hotspot deployment optimization method, a server, and a computer readable storage medium, the main purpose of which is to understand the user's satisfaction with the Wi-Fi hotspot in the business circle and the distribution of Wi-Fi hotspots in the business circle.
  • An optimization scheme for Wi-Fi hotspot deployment in the business circle is given to enhance the user experience of Wi-Fi hotspots.
  • the present application provides a server, including: a memory, a processor, and a Wi-Fi hotspot deployment optimization program stored on the memory, where the optimization program is executed by the processor to implement the following steps:
  • the collecting step collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the current location of the first mobile terminal Latitude and longitude;
  • a first calculating step calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level
  • the list of Wi-Fi hotspots is aggregated in multiple business districts;
  • a second calculating step calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi- in the plurality of shopping districts a concentrated area of Fi hotspots;
  • a third calculating step reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal, the Wi-Fi hotspot in the multiple shopping districts User satisfaction;
  • the number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle.
  • the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle it is determined that the user satisfaction of the first business circle needs to be adjusted.
  • the location of the Wi-Fi hotspot is determined that the user satisfaction of the first business circle needs to be adjusted.
  • the present application further provides a Wi-Fi hotspot deployment optimization method, where the method includes:
  • the acquiring step collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal;
  • a first calculating step calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level
  • the list of Wi-Fi hotspots is aggregated in multiple business districts;
  • a second calculating step calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi- in the plurality of shopping districts a concentrated area of Fi hotspots;
  • a third calculating step reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal, the Wi-Fi hotspot in the multiple shopping districts User satisfaction;
  • the number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle.
  • the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle it is determined that the user satisfaction of the first business circle needs to be adjusted. of The location of the Wi-Fi hotspot.
  • the present application further provides a computer readable storage medium, where the Wi-Fi hotspot deployment optimization program is stored, and the optimized program is executed by the processor to implement the foregoing Steps to deploy an optimization method for Wi-Fi hotspots.
  • the method, the server, and the computer readable storage medium provided by the present application calculate the user's satisfaction with the Wi-Fi hotspots of each business circle by acquiring historical data of all Wi-Fi hotspots scanned by the mobile terminal. According to the calculation result, the optimization scheme of Wi-Fi hotspot deployment in the business circle with lower user satisfaction is given according to the calculation result, and the Wi-Fi hotspot coverage population is increased, and the user's Internet access is increased. Experience.
  • FIG. 1 is a schematic diagram of a preferred embodiment of a server of the present application.
  • FIG. 2 is a schematic block diagram of a preferred embodiment of the Wi-Fi hotspot deployment optimization program of FIG. 1;
  • FIG. 3 is a flowchart of a preferred embodiment of a Wi-Fi hotspot deployment optimization method according to the present application.
  • the application provides a server 1.
  • a server 1 Referring to FIG. 1, a schematic diagram of a preferred embodiment of the server 1 of the present application is shown.
  • the server 1 includes a memory 11, a processor 12, a network interface 13, and a communication bus 14.
  • the communication bus 14 is used to implement connection communication between these components.
  • Server 1 can be a rack server, a blade server, a tower server, or a rack server.
  • the network interface 13 may include a standard wired interface, a wireless interface (such as a WI-FI interface). Usually used to connect to mobile terminals.
  • the server 1 connects the plurality of first mobile terminals 21 and the second mobile terminal 22 through the network interface 13.
  • the first mobile terminal 21 and the second mobile terminal 22 may be terminal devices having a wireless local area network configuration and display function, such as a notebook, a tablet, a smart phone, and an e-book reader.
  • the memory 11 includes at least one type of readable storage medium.
  • the at least one type of readable storage medium may be a non-volatile storage medium such as a flash memory, a hard disk, a multimedia card, a card type memory, or the like.
  • the readable storage medium may be an internal storage unit of the server 1, such as a hard disk of the server 1.
  • the readable storage medium may also be an external storage device of the server 1, such as a plug-in hard disk equipped on the server 1, a smart memory card (SMC), and security. Digital (Secure Digital, SD) card, flash card (Flash Card), etc.
  • the readable storage medium of the memory 11 is generally used to store a Wi-Fi hotspot deployment optimization program installed in the server 1, a Wi-Fi hotspot collected by the first mobile terminal 21, and historical data of the user. Model files of pre-determined and updated logistic regression models, distribution of human traffic within each business district obtained from third parties, etc.
  • the memory 11 can also be used to temporarily store data that has been output or is about to be output.
  • the processor 12 may be a Central Processing Unit (CPU), microprocessor or other data processing chip for running program code or processing data stored in the memory 11, such as performing Wi-Fi. Hotspot deployment optimizer, etc.
  • CPU Central Processing Unit
  • microprocessor or other data processing chip for running program code or processing data stored in the memory 11, such as performing Wi-Fi. Hotspot deployment optimizer, etc.
  • FIG. 1 shows only server 1 with components 11-14 and Wi-Fi hotspot deployment optimizer 10, but it should be understood that not all illustrated components may be implemented, alternative implementations may be more or less Component.
  • the server 1 may further include a user interface
  • the user interface may include an input unit such as a keyboard
  • the optional user interface may further include a standard wired interface and a wireless interface.
  • the server 1 may further include a display, which may also be referred to as a display screen or a display unit.
  • a display may also be referred to as a display screen or a display unit.
  • it may be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch sensor, or the like.
  • the display is used to display information processed in the server 1 and a user interface for displaying visualizations.
  • the server 1 may further include a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, and the like, and details are not described herein.
  • RF Radio Frequency
  • a Wi-Fi hotspot deployment optimizer 10 is stored in the memory 11, and the processor 12 performs the following steps when executing the Wi-Fi hotspot deployment optimization program 10 stored in the memory 11:
  • the acquiring step collecting the positioning information of the first mobile terminal 21 at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal 21 at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal 21;
  • a first calculating step calculating a hash value of the latitude and longitude of the current location of the first mobile terminal 21, taking a result of the first preset level of the hash value, and using the first preset level as a result of the first preset level
  • the list of Wi-Fi hotspots scanned by the location is aggregated in multiple business districts;
  • a second calculating step calculating a latitude and longitude hash value of the current position of the first mobile terminal 21, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi in the plurality of business circles - the concentrated area of the Fi hotspot;
  • a third calculating step reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal 21, Wi-Fi in the multiple shopping districts Hot user satisfaction;
  • the traffic aggregation area and the Wi-Fi hotspot concentration area determine the location of the Wi-Fi hotspot that needs to be adjusted to improve the user satisfaction of the first business circle.
  • each city has a plurality of different business districts, wherein the business circle refers to a certain range of areas, and the first user refers to accessing and using the Wi-Fi hotspots in each business circle through the first mobile terminal 21.
  • the second user refers to the staff of the Wi-Fi hotspot provider, and the second user knows the distribution of Wi-Fi hotspots in each business circle through the second mobile terminal 22 and the first user to Wi-Fi in each business circle
  • the user satisfaction of the hotspot is that the first mobile terminal 21 is installed with an APP for connecting to the Wi-Fi hotspot, and the APP can obtain location information (latitude and longitude) of the first mobile terminal 21 at the current location, and the second mobile terminal 22 is installed with Wi-Fi hotspot deployment optimizer 10 client program.
  • Hotspot vendors can use a variety of channels to understand the areas where the first users of each city's business districts gather, such as obtaining relevant data through third parties.
  • the APP scans the Wi-Fi hotspot list available at the current location through the first mobile terminal 21, and collects all Wi-Fi hotspots in the Wi-Fi hotspot list.
  • Historical data within a preset time (one week), including: Wi-Fi name, time of access, time of operation, operational status (connection success, connection failure, login success, login failure, etc.), frequency of access, availability by operator Etc. Then, the above historical data is sent to the server 1.
  • the server 1 extracts key historical data, such as Wi-Fi identification, time, location, connection operation, Internet access duration, number of successful connections, and number of connection failures, through the data collection technology (Extract-Transform-Load, ETL).
  • ETL Extract-Transform-Load
  • Wi-Fi hotspot the transmitting device of the Wi-Fi hotspot in the Wi-Fi hotspot list (hereinafter referred to as Wi-Fi hotspot) is also Located near the location of the first mobile terminal 21, the location of the Wi-Fi hotspot can be estimated based on the location information of the first mobile terminal 21.
  • the geohash algorithm can be used to calculate the latitude and longitude hash values, and the hash values of different levels can be different. For example, one to nine results can be taken, and the six-level result is expressed as a range of 1.2 km*1.2 km. (Approximately can be understood as the scope of a business circle), taking a seven-level result indicating a range of 152m * 152m.
  • the Wi-Fi hotspot lists scanned by the first mobile terminal at the current location are a, b, c, d, and e, respectively, assuming a first preset.
  • the level is six
  • the server 1 reads the latitude and longitude of the current position of the first mobile terminal A, B, C, D, E from the memory 11, performs a geohash operation, and calculates the latitude and longitude hash value of the current position of each first mobile terminal 21. If the six-level hash value of the first mobile terminal A, B, C, D, and E is the same, it is determined that the first mobile terminal A, B, C, D, and E are in the same business circle.
  • the Wi-Fi hotspots in the Wi-Fi lists a, b, c, d, and e are also located in the business circle.
  • the second calculation step is needed to determine the area of the Wi-Fi hotspot in the business circle.
  • the second calculating step includes: according to the second preset The result of the level, the Wi-Fi hotspot list in each business circle is divided into different regional blocks smaller than the business circle; in the Wi-Fi hotspot list in the different regional blocks, the Wi with the same Wi-Fi hotspot will be The -Fi hotspot list is merged to form a new Wi-Fi hotspot list; the different regional blocks in which the Wi-Fi hotspot list with the same Wi-Fi hotspot is located are merged to form a new regional block, and Wi-Fi in different new regional blocks is determined.
  • the second preset level is seven levels, performing a geohash operation on the latitude and longitude of the current location of the first mobile terminal A, B, C, D, and E, and taking a seven-level result of the hash value, wherein the first mobile terminal A, C The seven-level result is the same, the seventh-level results of the first mobile terminal B, E are the same, and the multiple Wi-Fi hotspots in the Wi-Fi hotspot list a, c are divided into the regional block P, and the Wi-Fi hotspot list b is The plurality of Wi-Fi hotspots in the e are divided into the area block Q, and the plurality of Wi-Fi hotspots in the Wi-Fi hotspot list d are separately divided into the area block O.
  • Wi-Fi hotspot list merges into one Wi-Fi hotspot list until there is no duplicate Wi-Fi hotspot between each Wi-Fi hotspot list in the same block, that is, if there is originally 20 in a certain block
  • a list of Wi-Fi hotspots, after deduplication, the number of Wi-Fi hotspot lists will be less than or equal to 20.
  • Wi-Fi hotspot it can be understood that, assuming that the transmitting device of a Wi-Fi hotspot is located between two points, and both points are within the coverage of the Wi-Fi hotspot, then different first mobile terminals located between the two points 21 can scan the Wi-Fi hotspot, that is, according to different latitude and longitude in the positioning information of the first mobile terminal 21, the same Wi-Fi hotspot may be divided into the middle lines of two adjacent different regional blocks. There is a nearby Wi-Fi hotspot, so this type of Wi-Fi hotspot needs to be further processed.
  • the area blocks P and Q are adjacent, and the same Wi-Fi hotspot exists in the Wi-Fi hotspot list in the area blocks P and Q, then the area blocks P and Q are merged into a new area block, and De-duxing the Wi-Fi hotspots in all Wi-Fi hotspot lists in this new block, maximizing the number of Wi-Fi hotspots in the new block; then, in multiple new blocks
  • the Wi-Fi hotspots are merged and de-duplicated until there are no duplicate Wi-Fi hotspots in all the blocks in the business circle and in the block.
  • Some of the new blocks have a large number of Wi-Fi hotspots, and some have few Wi-Fi.
  • the obtained distribution of each block and the number of Wi-Fi hotspots in each block are linked to the electronic map of the business circle, so that the area where the Wi-Fi hotspot is concentrated in the business circle can be determined.
  • S is the first user's satisfaction with the Wi-Fi hotspots in each business circle
  • C is the average connection success rate of Wi-Fi hotspots in each business circle
  • L is the average landing of Wi-Fi hotspots in each business circle.
  • Success rate T 1 is the average online time (in min) of Wi-Fi hotspots in each business circle
  • T 2 is the average connection of Wi-Fi hotspots in each business circle to power consumption (in s).
  • the abnormal values (such as the maximum value and the minimum value) need to be removed when calculating C, L, T 1 and T 2 , and the actual network time length is rounded when calculating T 1 , and the value is 20 minutes over 10 minutes. Take 10 minutes for less than 10 minutes.
  • the third calculating step includes: calculating, according to historical data of the Wi-Fi hotspot in each business circle within a preset time period and a predetermined logistic regression model, the first user to Wi- in each business circle. User satisfaction of Fi hotspots.
  • the Wi-Fi operator may collect a first user's user satisfaction sample for the Wi-Fi hotspot in the business circle through an operation questionnaire or a user scoring system, and the predetermined logistic regression model is used to calculate the first user to each business circle.
  • User satisfaction of the internal Wi-Fi hotspot, the model file of the logistic regression model is stored in the memory 11, which can collect the user satisfaction sample and the key historical data of the Wi-Fi hotspot in the business circle in the past three months. Offline training is available.
  • the advantage of the offline training model is that it utilizes a large amount of historical data, and the sample is sufficient.
  • the advantage of the online training model is that it can use the latest data, the model can adapt to the changes of real-time data, and the online model is more accurate in the case of large data distribution and historical gap.
  • the above-mentioned logistic regression model can be updated every three days. Then, the key historical data of the Wi-Fi hotspot in each business circle in the latest week is read from the memory 11, and the updated logistic regression model is input, and the user satisfaction of the first user to the Wi-Fi hotspot in the business circle is calculated.
  • an electronic map is installed on the second mobile terminal 22, and a map of all cities is displayed to the second user through the electronic map, and when the second user selects a certain city, the location and the merchants of all the business districts of the city are also displayed.
  • User satisfaction in Wi-Fi hotspots in the circle When a Wi-Fi hotspot provider needs to optimize the deployment of a Wi-Fi hotspot in a certain business circle to improve the user satisfaction of the Wi-Fi hotspot in the business circle, the business circle is selected, and the server 1 will respond to the click operation.
  • the server 1 filters out the user from the number of the first user and the current number of the first user of the business circle B (for example, a ⁇ 50).
  • the highest satisfaction business circle G according to the relationship between the number of Wi-Fi hotspots in the business circle G and the number of first users, determine whether the Wi-Fi hotspot should be increased or decreased in the business circle B, and then aggregate according to the traffic flow in the business circle B. The area is compared with the concentrated area of the Wi-Fi hotspot in the business circle B, and it is determined that the location of the Wi-Fi hotspot needs to be adjusted in the business circle B.
  • the number of Wi-Fi hotspots in the business circle G (for example, m) is significantly more than the number of Wi-Fi hotspots in the business circle B (for example, n), then the corresponding number (mn) needs to be added in the business circle B.
  • the Wi-Fi hotspot is equal to the number of Wi-Fi hotspots in the business district G; if the number of Wi-Fi hotspots in the business circle G is less than B or equivalent, the number of Wi-Fi hotspots does not cause the business circle B, G user
  • the main reason for the difference in satisfaction is to further consider whether the location of the Wi-Fi hotspot is reasonable.
  • the demand for the Wi-Fi hotspot is also relatively large. Then, after reading the distribution area of the traffic flow in the business circle B obtained from the third party from the memory 11 The comparison between the traffic aggregation area in the business circle B and the centralized area of the Wi-Fi hotspot in the business circle B obtained through the second calculation step is the same.
  • the first user aggregation area of circle B has fewer Wi-Fi hotspots, and there are more Wi-Fi hotspots in the area where there are fewer first users, so it is necessary to adjust some Wi-Fi hotspots from the area where the first user is less to the first user.
  • the quality problem may exist in the Wi-Fi hotspot in the business circle B. It is recommended to replace the Wi-Fi hotspot.
  • the server 1 displays the distribution of the Wi-Fi hotspots in the shopping circle to the second user through the first display area of the second mobile terminal 22, and displays the improvement in the business circle B in the second display area of the second mobile terminal 22.
  • Wi-Fi hotspot user satisfaction Wi-Fi hotspot adjustment program Wi-Fi hotspot adjustment program.
  • the server 1 proposed in the above embodiment calculates the user's satisfaction with the Wi-Fi hotspots of each business circle and the Wi-Fi hotspots in each business circle by acquiring the historical data of all the Wi-Fi hotspots scanned by the first mobile terminal 21.
  • an optimization scheme for Wi-Fi hotspot deployment in the business circle with lower user satisfaction is given, and the Wi-Fi hotspot coverage population is increased to improve the user's online experience.
  • the Wi-Fi hotspot deployment optimizer 10 may also be partitioned into one or more modules, one or more modules being stored in the memory 11 and being processed by one or more processors 12 implementations to complete this application.
  • a module as referred to in this application refers to a series of computer program instructions that are capable of performing a particular function.
  • FIG. 2 it is a block diagram of a preferred embodiment of the Wi-Fi hotspot deployment optimization program 10 of FIG.
  • the Wi-Fi hotspot deployment optimization program 10 can be divided into: an acquisition module 110, a first calculation module 120, a second calculation module 130, a third calculation module 140, and an optimization module 150, which are implemented by the modules 110-150.
  • the functions or operational steps are similar to the above, and are not described in detail here, exemplarily, for example:
  • the collecting module 110 is configured to collect the positioning information of the first mobile terminal 21 at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal 21 at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal 21. ;
  • the first calculation module 120 is configured to calculate a latitude and longitude hash value of the current location of the first mobile terminal 21, and take a result of the first preset level of the hash value, and the first mobile terminal according to the result of the first preset level 21
  • the list of Wi-Fi hotspots scanned at the current location is aggregated in multiple business districts;
  • the second calculation module 130 is configured to calculate a latitude and longitude hash value of the current location of the first mobile terminal 21, and take a result of the second preset level of the hash value, and determine the location according to the result of the second preset level. a concentrated area of Wi-Fi hotspots in multiple business districts;
  • the third calculation module 140 is configured to read historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculate a first user of the first mobile terminal 21 to be in the multiple shopping districts. User satisfaction of Wi-Fi hotspots; and
  • the optimization module 150 is configured to filter out a second business circle from the plurality of business circles in response to a click operation of the second user in the second mobile terminal 22 to select a first business circle from the plurality of shopping circles.
  • the number of first users in the plurality of business districts is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the first user
  • the relationship between the numbers determines the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle.
  • the traffic aggregation area and the Wi-Fi hotspot concentration area in the first business circle the first business circle user is determined to be improved. Satisfaction needs to adjust the location of the Wi-Fi hotspot.
  • the present application also provides a Wi-Fi hotspot deployment optimization method.
  • FIG. 3 it is a flowchart of a preferred embodiment of a Wi-Fi hotspot deployment optimization method of the present application.
  • the method can be performed by a server, which can be implemented by software and/or hardware.
  • the Wi-Fi hotspot deployment optimization method includes: Step S10 to Step S60.
  • step S10 the location information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location are collected, where the location information includes the latitude and longitude of the current location of the first mobile terminal;
  • Step S20 calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level.
  • Wi-Fi hotspot lists are aggregated across multiple business districts;
  • Step S30 calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining a Wi-Fi hotspot in the plurality of business circles according to the result of the second preset level Concentrated area
  • Step S40 Read historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculate a user of the first mobile terminal to the Wi-Fi hotspot in the multiple shopping districts. Satisfaction; and
  • Step S50 In response to the click operation of the second user selecting a first business circle from the plurality of shopping circles, the second user selects a second business circle from the plurality of business circles, the second business
  • the number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle.
  • the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle it is determined that the user satisfaction of the first business circle needs to be adjusted.
  • the location of the Wi-Fi hotspot is determined that the user satisfaction of the first business circle needs to be adjusted.
  • each city has a plurality of different business districts, wherein the business circle refers to a certain range of regions, and the first user refers to accessing and using the Wi-Fi hotspots in each commercial circle through the first mobile terminal.
  • the second user refers to the staff of the Wi-Fi hotspot provider, and the second user passes the second mobile terminal. Solving the distribution of Wi-Fi hotspots in each business circle and the user satisfaction of the first user to Wi-Fi hotspots in each business circle.
  • the first mobile terminal is equipped with an APP for connecting to a Wi-Fi hotspot, and the APP can be obtained.
  • the location information (latitude and longitude) of the first mobile terminal at the current location, and the client program of the Wi-Fi hotspot deployment optimization program is installed on the second mobile terminal.
  • Hotspot vendors can use a variety of channels to understand the areas where the first users of each city's business districts gather, such as obtaining relevant data through third parties.
  • the APP scans the Wi-Fi hotspot list available at the current location through the first mobile terminal, and collects all the Wi-Fi hotspots in the Wi-Fi hotspot list.
  • Historical data within a preset time (one week), including: Wi-Fi name, time of access, time of operation, operation status (connection success, connection failure, login success, login failure, etc.), frequency of access, availability of operators, etc. And then send the above historical data to the server.
  • the server extracts key historical data, such as Wi-Fi identification, time, location, connection operation, Internet access duration, number of successful connections, and number of connection failures, through the data collection technology (Extract-Transform-Load, ETL).
  • ETL Extract-Transform-Load
  • Wi-Fi hotspot the transmitting device of the Wi-Fi hotspot (hereinafter referred to as Wi-Fi hotspot) in the Wi-Fi hotspot list is also located.
  • the location of the first mobile terminal is located, and therefore, the location of the Wi-Fi hotspot can be estimated according to the location information of the first mobile terminal.
  • the geohash algorithm can be used to calculate the latitude and longitude hash values, and the hash values of different levels can be different. For example, one to nine results can be taken, and the six-level result is expressed as a range of 1.2 km*1.2 km. (Approximately can be understood as the scope of a business circle), taking a seven-level result indicating a range of 152m * 152m.
  • the Wi-Fi hotspot lists scanned by the first mobile terminal at the current location are a, b, c, d, and e, respectively, assuming a first preset.
  • the level is six levels
  • the server reads the latitude and longitude of the current position of the first mobile terminal A, B, C, D, E from the memory, performs a geohash operation, calculates the latitude and longitude hash value of the current position of each first mobile terminal, and takes a hash.
  • the Wi-Fi hotspots in the Wi-Fi lists a, b, c, d, and e are also located in the business district.
  • the second calculation step is needed to determine the area of the Wi-Fi hotspot in the business circle.
  • the second calculating step includes: according to the second preset level.
  • the Wi-Fi hotspot list in each business district is divided into different regional blocks smaller than the business circle; in the Wi-Fi hotspot list in the different regional blocks, Wi-s with the same Wi-Fi hotspot will be The Fi hotspot list is merged to form a new Wi-Fi hotspot list; the different regional blocks in which the Wi-Fi hotspot list with the same Wi-Fi hotspot is located are merged to form a new regional block, and different Wi-Fi hotspots in the new local block are determined.
  • the number of Wi-Fi hotspots in each business district is based on the number of Wi-Fi hotspots in the new block of the business district.
  • the second preset level is seven
  • the seventh-level results of A and C are the same.
  • the seven-level results of the first mobile terminals B and E are the same.
  • the Wi-Fi hotspots in the Wi-Fi hotspot list a and c are divided into the regional block P, and Wi-Fi is used.
  • the plurality of Wi-Fi hotspots in the hotspot list b, e are divided into the regional block Q, and the plurality of Wi-Fi hotspots in the Wi-Fi hotspot list d are separately divided into the regional block O. If there are duplicate Wi-Fi hotspots in the Wi-Fi hotspot list in the same area block, deduplication is performed on the Wi-Fi hotspots in each of the two Wi-Fi hotspot lists, and the two Wis after deduplication are performed.
  • Wi-Fi hotspot list merges into one Wi-Fi hotspot list until there is no duplicate Wi-Fi hotspot between each Wi-Fi hotspot list in the same block, that is, if there is originally 20 in a certain block
  • a list of Wi-Fi hotspots, after deduplication, the number of Wi-Fi hotspot lists will be less than or equal to 20.
  • Wi-Fi hotspots can be scanned, that is, according to the latitude and longitude in different first mobile terminal positioning information, the same Wi-Fi hotspot may be divided into the vicinity of the middle line of two adjacent different regional blocks. Wi-Fi hotspots, therefore, need to further process this type of Wi-Fi hotspot.
  • the area blocks P and Q are adjacent, and the same Wi-Fi hotspot exists in the Wi-Fi hotspot list in the area blocks P and Q, then the area blocks P and Q are merged into a new area block, and De-duxing the Wi-Fi hotspots in all Wi-Fi hotspot lists in this new block, maximizing the number of Wi-Fi hotspots in the new block; then, in multiple new blocks
  • the Wi-Fi hotspots are merged and de-duplicated until there are no duplicate Wi-Fi hotspots in all the blocks in the business circle and in the block.
  • Some of the new blocks have a large number of Wi-Fi hotspots, and some have few Wi-Fi.
  • the obtained distribution of each block and the number of Wi-Fi hotspots in each block are linked to the electronic map of the business circle, so that the area where the Wi-Fi hotspot is concentrated in the business circle can be determined.
  • S is the first user's satisfaction with the Wi-Fi hotspots in each business circle
  • C is the average connection success rate of Wi-Fi hotspots in each business circle
  • L is the average landing of Wi-Fi hotspots in each business circle.
  • Success rate T 1 is the average online time (in min) of Wi-Fi hotspots in each business circle
  • T 2 is the average connection of Wi-Fi hotspots in each business circle to power consumption (in s).
  • the abnormal values (such as the maximum value and the minimum value) need to be removed when calculating C, L, T 1 and T 2 , and the actual network time length is rounded when calculating T 1 , and the value is 20 minutes over 10 minutes. Take 10 minutes for less than 10 minutes.
  • the third calculating step includes: calculating, according to historical data of the Wi-Fi hotspot in each business circle within a preset time period and a predetermined logistic regression model, the first user to Wi- in each business circle. User satisfaction of Fi hotspots.
  • the Wi-Fi operator may collect a first user's user satisfaction sample for the Wi-Fi hotspot in the business circle through an operation questionnaire or a user scoring system, and the predetermined logistic regression model is used to calculate the first user to each business circle.
  • User satisfaction of the internal Wi-Fi hotspot, the model file of the logistic regression model is stored in the memory, which can be collected through the collected user satisfaction sample and the key historical data of the Wi-Fi hotspot within the business circle in the past three months. Trained.
  • the advantage of the offline training model is that it utilizes a large amount of historical data, and the sample is sufficient.
  • the advantage of the online training model is that it can use the latest data, the model can adapt to the changes of real-time data, and the online model is more accurate in the case of large data distribution and historical gap.
  • the above-mentioned logistic regression model can be updated every three days. Then, the key historical data of the Wi-Fi hotspot in each business circle in the last week is read from the memory, and the updated logistic regression model is input, and the first user's user satisfaction with the Wi-Fi hotspot in the business circle is calculated.
  • an electronic map is installed on the second mobile terminal, and the map of all cities is displayed to the second user through the electronic map, and when the second user selects a certain city, the location and the business districts of all the business districts of the city are also displayed.
  • User satisfaction within the Wi-Fi hotspot When a Wi-Fi hotspot provider needs to optimize the deployment of Wi-Fi hotspots in a certain business circle to improve the user satisfaction of Wi-Fi hotspots in the business circle, select the business circle, and the server will respond to the click operation to For example, in the business circle B, the number of the first user is a, and the server selects the user satisfaction from the number of the first user and the current number of the first user of the business circle B (for example, a ⁇ 50).
  • the highest business circle G determines whether the Wi-Fi hotspot should be increased or decreased in the business circle B, and then according to the traffic flow area in the business circle B and The concentrated areas of the Wi-Fi hotspots in the business district B are compared, and it is determined that the location of the Wi-Fi hotspot needs to be adjusted in the business circle B.
  • the number of Wi-Fi hotspots in the business circle G (for example, m) is significantly more than the number of Wi-Fi hotspots in the business circle B (for example, n)
  • the corresponding number (mn) needs to be added in the business circle B.
  • the Wi-Fi hotspot is equal to the number of Wi-Fi hotspots in the business district G; if the number of Wi-Fi hotspots in the business circle G is less than B or equivalent, the number of Wi-Fi hotspots does not cause the business circle B,
  • the main reason for the difference in user satisfaction is to consider whether the location of the Wi-Fi hotspot is reasonable.
  • the demand for the Wi-Fi hotspot is also relatively large. Then, after reading the distribution area of the traffic flow in the business circle B obtained from the third party from the memory 11 The comparison between the traffic aggregation area in the business circle B and the centralized area of the Wi-Fi hotspot in the business circle B obtained through the second calculation step is the same.
  • the first user aggregation area of circle B has fewer Wi-Fi hotspots, and there are more Wi-Fi hotspots in the area where there are fewer first users, so it is necessary to adjust some Wi-Fi hotspots from the area where the first user is less to the first user.
  • Aggregation area if the first user aggregation area and the centralized area of the Wi-Fi hotspot are consistent, then Ming may be a quality problem in the Wi-Fi hotspot in the business district B. It is recommended to replace the Wi-Fi hotspot.
  • preset time and the like need to be preset parameters, which can be adjusted according to user needs.
  • the method further includes: displaying a concentrated area of the Wi-Fi hotspot in the first business circle on the electronic map of the second mobile terminal, and displaying Wi-Fi that needs to be adjusted to improve user satisfaction in the first business circle.
  • the server displays the distribution of the Wi-Fi hotspots in the business circle to the second user through the first display area of the second mobile terminal, and displays the Wi-Fi hotspot user in the business circle B in the second display area of the second mobile terminal. Satisfaction adjustment scheme for Wi-Fi hotspots.
  • the first display area and the second display area are only different to indicate that the two display areas are different.
  • the Wi-Fi hotspot deployment optimization method proposed by the foregoing embodiment obtains the historical data of all the Wi-Fi hotspots scanned by the first mobile terminal, and calculates the user's satisfaction with the Wi-Fi hotspots of each commercial circle, and the Wi in each business circle.
  • the aggregation area of the Fi hotspot is based on the calculation result, and the optimization scheme for the Wi-Fi hotspot deployment in the business circle with lower user satisfaction is given, and the Wi-Fi hotspot coverage population is increased to improve the user's online experience.
  • the embodiment of the present application further provides a computer readable storage medium, where the Wi-Fi hotspot deployment optimization program is stored, and when the optimization program is executed by the processor, the following operations are implemented:
  • the acquiring step collecting the positioning information of the first mobile terminal at the current location and the Wi-Fi hotspot list scanned by the first mobile terminal at the current location, where the positioning information includes the latitude and longitude of the current location of the first mobile terminal;
  • a first calculating step calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the first preset level of the hash value, and scanning the first mobile terminal at the current location according to the result of the first preset level
  • the list of Wi-Fi hotspots is aggregated in multiple business districts;
  • a second calculating step calculating a latitude and longitude hash value of the current location of the first mobile terminal, taking a result of the second preset level of the hash value, and determining, according to the result of the second preset level, the Wi- in the plurality of shopping districts a concentrated area of Fi hotspots;
  • a third calculating step reading historical data of the Wi-Fi hotspot in the Wi-Fi hotspot list in a preset time, and calculating, by the first user of the first mobile terminal, the Wi-Fi hotspot in the multiple shopping districts User satisfaction;
  • the number of first users in the plurality of business circles is equal to the number of first users in the first business circle and the user satisfaction is the highest, according to the number of Wi-Fi hotspots in the second business circle and the number of first users Correlation relationship, determine the number of Wi-Fi hotspots that need to be adjusted to improve the user satisfaction of the first business circle.
  • the traffic flow aggregation area and the Wi-Fi hotspot concentration area in the first business circle it is determined that the user satisfaction of the first business circle needs to be adjusted.
  • the location of the Wi-Fi hotspot is determined that the user satisfaction of the first business circle needs to be adjusted.
  • the specific implementation manner of the computer-readable storage medium of the present application is substantially the same as the specific implementation manner of the foregoing Wi-Fi hotspot deployment optimization method, and details are not described herein again.
  • a disk including a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods described in the various embodiments of the present application.
  • a terminal device which may be a mobile phone, a computer, a server, or a network device, etc.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Security & Cryptography (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

La présente invention concerne un procédé d'optimisation du déploiement d'un point d'accès sans fil WiFi, le procédé consistant à : acquérir des informations de positionnement d'un premier terminal mobile ainsi qu'une liste de points d'accès sans fil WiFi balayés, les informations de positionnement comprenant la latitude et la longitude du premier terminal mobile ; agréger des listes de points d'accès sans fil WiFi à l'intérieur de multiples quartiers d'affaires ; déterminer une zone centralisée de points d'accès sans WiFi à l'intérieur des multiples quartiers d'affaires ; calculer la satisfaction d'utilisateur d'un premier utilisateur pour un point d'accès sans fil WiFi à l'intérieur des multiples quartiers d'affaires ; passer au crible un second quartier d'affaires en réponse à une opération d'un second utilisateur sélectionnant un premier quartier d'affaires, et, selon le nombre de points d'accès sans fil WiFi et le nombre de premiers utilisateurs dans le second quartier d'affaires, ainsi qu'une zone centralisée de trafic humain et une zone centralisée de points d'accès sans fil WiFi dans le premier quartier d'affaires, déterminer le nombre et les emplacements de points d'accès sans fil WiFi nécessitant un réglage pour améliorer la satisfaction de l'utilisateur dans le premier quartier d'affaires. L'invention concerne en outre un serveur et à un support de stockage lisible par ordinateur. La présente invention concerne une solution d'optimisation de déploiement d'un point d'accès sans fil WiFi dans un quartier d'affaires en utilisant la distribution de point d'accès sans fil WiFi dans le quartier d'affaires ainsi que la satisfaction de l'utilisateur de façon à améliorer l'expérience de l'utilisateur de recourir à Internet..
PCT/CN2017/108771 2017-09-26 2017-10-31 Procédé d'optimisation de déploiement de point d'accès sans fil wifi, serveur et support de stockage Ceased WO2019061663A1 (fr)

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