CN115426030B - Satellite energy saving method and satellite energy saving device based on big data - Google Patents
Satellite energy saving method and satellite energy saving device based on big data Download PDFInfo
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- CN115426030B CN115426030B CN202211083945.5A CN202211083945A CN115426030B CN 115426030 B CN115426030 B CN 115426030B CN 202211083945 A CN202211083945 A CN 202211083945A CN 115426030 B CN115426030 B CN 115426030B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1851—Systems using a satellite or space-based relay
- H04B7/18519—Operations control, administration or maintenance
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- H—ELECTRICITY
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- H04B7/00—Radio transmission systems, i.e. using radiation field
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- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1853—Satellite systems for providing telephony service to a mobile station, i.e. mobile satellite service
- H04B7/18539—Arrangements for managing radio, resources, i.e. for establishing or releasing a connection
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The application provides a satellite energy saving method and a satellite energy saving device based on big data, wherein the satellite energy saving method comprises the following steps: acquiring current satellite position information of a satellite group according to the running orbit of a satellite; determining a target area corresponding to the current position of the satellite group based on the satellite position information, and collecting big data information corresponding to the target area in a historical time period; analyzing the big data information, and determining a network use peak time period corresponding to the target area in a plurality of target time periods; acquiring current time, and determining a satellite communication demand vector according to the current time and a network use peak time period; and determining the number of satellites currently required to be activated according to the satellite communication demand vector and a preset load threshold, and activating satellites corresponding to the number of satellites in the satellite group. According to the satellite energy saving method and the satellite energy saving device, the satellite energy saving effect is achieved.
Description
Technical Field
The application relates to the technical field of satellite communication, in particular to a satellite energy saving method and a satellite energy saving device based on big data.
Background
With the development of network communication technology and the proposal of a 6G (6 th generation mobile networks, sixth generation mobile communication technology) technology heaven-earth integration concept, satellites can cover land and sea, and break the spatial barrier of communication. Even if the satellite can cover a large range, for some areas with little human smoke, such as deserts, remote land sea areas, original forests and other land-wide areas, the satellite can cover a large range, which is certainly waste of precious satellite energy, and when an emergency event or a natural disaster is encountered, a great deal of satellite energy is consumed by emergency mobilizing the satellite. However, the only means for obtaining energy from the satellite is to obtain solar energy through irradiation of sunlight, but the satellite also has a backlight time period, so that energy saving of the satellite is a very challenging problem.
Disclosure of Invention
In view of this, the present application aims to provide a satellite energy-saving method and a satellite energy-saving device based on big data, which combine the analysis and application of big data to help regulate and control the activation or dormancy of satellites, so as to avoid the invalid coverage of satellites when satellite groups pass through unmanned areas or areas with little people and smoke, thereby achieving the effect of satellite energy saving.
In a first aspect, an embodiment of the present application provides a satellite energy saving method based on big data, where the satellite energy saving method includes:
acquiring current satellite position information of a satellite group according to the running orbit of a satellite;
determining a target area corresponding to the current position of the satellite group based on the satellite position information, and collecting big data information corresponding to the target area in a historical time period; the historical time period comprises a plurality of target time periods, and each target time period corresponds to different big data information;
analyzing the big data information, and determining a network use peak time period corresponding to the target area in a plurality of target time periods;
acquiring current time, and determining a satellite communication demand vector according to the current time and a network use peak time period;
and determining the number of satellites currently required to be activated according to the satellite communication demand vector and a preset load threshold, and activating satellites corresponding to the number of satellites in the satellite group.
Further, the big data information includes a number of network registered users within the target region; the analyzing the big data information, and determining a network usage peak time period corresponding to the target area in a plurality of target time periods, includes:
And determining a target time period with the highest network registration user number in a plurality of target time periods according to the network registration user number corresponding to each target time period, and determining the target time period with the highest network registration user number as the network use peak time period.
Further, the determining the satellite communication demand vector according to the current time and the network usage peak time period includes:
judging whether the current time is in the network use peak time period or not;
if yes, determining a first preset load rate as the satellite communication demand vector;
if not, determining a second preset load rate as the satellite communication demand vector; wherein the first preset load factor is greater than the second preset load factor.
Further, the determining, according to the satellite communication demand vector and a preset load threshold, the number of satellites currently required to be activated, and activating the satellites corresponding to the number of satellites in the satellite group, includes:
judging whether the satellite communication demand vector is larger than or equal to the load threshold value or not;
if yes, determining the first preset number as the satellite number;
If not, determining a second preset number as the satellite number; wherein the first preset number is greater than the second preset number;
determining satellites to be activated corresponding to the number of the satellites in the satellite group, and determining satellites except the satellites to be activated in the satellite group as dormant satellites;
sending an activation instruction to the satellite to be activated, and controlling the satellite to be activated to enter an activation state;
and sending a dormancy instruction to the dormancy satellite, and controlling the dormancy satellite to enter a dormancy state.
In a second aspect, embodiments of the present application further provide a satellite energy saving device based on big data, the satellite energy saving device including:
the position information acquisition module is used for acquiring the current satellite position information of the satellite group according to the running orbit of the satellite;
the big data information acquisition module is used for determining a target area corresponding to the current position of the satellite group based on the satellite position information and acquiring big data information corresponding to the target area in a historical time period; the historical time period comprises a plurality of target time periods, and each target time period corresponds to different big data information;
The peak time period determining module is used for analyzing the big data information and determining a network use peak time period corresponding to the target area in a plurality of target time periods;
the demand vector determining module is used for obtaining the current time and determining a satellite communication demand vector according to the current time and the network use peak time period;
the satellite activation module is used for determining the number of satellites which need to be activated currently according to the satellite communication demand vector and a preset load threshold, and activating satellites corresponding to the number of satellites in the satellite group.
Further, the big data information includes a number of network registered users within the target region; the peak time period determining module is used for analyzing the big data information, and when determining that the network corresponding to the target area uses the peak time period in a plurality of target time periods, the peak time period determining module is further used for:
and determining a target time period with the highest network registration user number in a plurality of target time periods according to the network registration user number corresponding to each target time period, and determining the target time period with the highest network registration user number as the network use peak time period.
Further, when the demand vector determining module is configured to determine a satellite communication demand vector according to the current time and the network usage peak time period, the demand vector determining module is further configured to:
judging whether the current time is in the network use peak time period or not;
if yes, determining a first preset load rate as the satellite communication demand vector;
if not, determining a second preset load rate as the satellite communication demand vector; wherein the first preset load factor is greater than the second preset load factor.
Further, when the satellite activation module is configured to determine, according to the satellite communication demand vector and a preset load threshold, the number of satellites currently required to be activated, and activate the satellites corresponding to the number of satellites in the satellite group, the satellite activation module is further configured to:
judging whether the satellite communication demand vector is larger than or equal to the load threshold value or not;
if yes, determining the first preset number as the satellite number;
if not, determining a second preset number as the satellite number; wherein the first preset number is greater than the second preset number;
Determining satellites to be activated corresponding to the number of the satellites in the satellite group, and determining satellites except the satellites to be activated in the satellite group as dormant satellites;
sending an activation instruction to the satellite to be activated, and controlling the satellite to be activated to enter an activation state;
and sending a dormancy instruction to the dormancy satellite, and controlling the dormancy satellite to enter a dormancy state.
In a third aspect, embodiments of the present application further provide an electronic device, including: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, the processor and the memory are communicated through the bus when the electronic device is running, and the machine-readable instructions are executed by the processor to perform the steps of the big data based satellite energy saving method.
In a fourth aspect, embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the big data based satellite power saving method as described above.
According to the big data-based satellite energy saving method, firstly, current satellite position information of a satellite group is obtained according to the running orbit of a satellite; then, determining a target area corresponding to the current position of the satellite group based on the satellite position information, and collecting big data information corresponding to the target area in a historical time period; analyzing the big data information, and determining a network use peak time period corresponding to the target area in a plurality of target time periods; acquiring current time, and determining a satellite communication demand vector according to the current time and a network use peak time period; and finally, determining the number of satellites currently required to be activated according to the satellite communication demand vector and a preset load threshold, and activating satellites corresponding to the number of satellites in the satellite group.
Compared with the satellite energy-saving method in the prior art, the method has the advantages that the big data information of the target area is utilized to conduct data analysis, the network use peak time period of the target area is analyzed, the satellite communication demand vector is determined according to the network use peak time period and the current time, and the number of satellites of the currently required activated satellites is determined according to the satellite communication demand vector. Therefore, the method and the device accurately analyze the real demand of the target area for the network by utilizing the characteristics of large data quantity, high speed, high reality and the like of big data analysis, and efficiently and accurately assist in regulating the satellite state. And then the number of satellites to be activated is regulated according to the real demand, so that unnecessary data transmission of the satellites can be reduced when the demand of a target area for a network is smaller, thereby realizing satellite energy conservation in an unmanned area or a region with rare people, avoiding invalid coverage of the satellites when the satellite passes through the unmanned area or the region with rare people, and achieving the effect of satellite energy conservation. When the demand of the target area for the network is large, a large number of satellites are activated, so that the network in the densely populated city can be ensured to be smooth. According to the method and the device, by combining analysis and application of big data, the activation or dormancy of the satellite is regulated and controlled in an assisted mode, invalid coverage of the satellite when the satellite group passes through an unmanned area or an area with rare people is avoided, and therefore the effect of satellite energy conservation is achieved.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered limiting the scope, and that other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a satellite energy saving method based on big data according to an embodiment of the present application;
fig. 2 is a flowchart of a satellite activation method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a satellite energy saving device based on big data according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, every other embodiment that a person skilled in the art would obtain without making any inventive effort is within the scope of protection of the present application.
First, application scenarios applicable to the present application will be described. The method and the device can be applied to the technical field of satellite communication.
With the development of network communication technology and the proposal of a 6G (6 th generation mobile networks, sixth generation mobile communication technology) technology heaven-earth integration concept, satellites can cover land and sea, and break the spatial barrier of communication. Even if the satellite can cover a large range, for some areas with little human smoke, such as deserts, remote land sea areas, original forests and other land-wide areas, the satellite can cover a large range, which is certainly waste of precious satellite energy, and when an emergency event or a natural disaster is encountered, a great deal of satellite energy is consumed by emergency mobilizing the satellite. However, the only means for obtaining energy from the satellite is to obtain solar energy through irradiation of sunlight, but the satellite also has a backlight time period, so that energy saving of the satellite is a very challenging problem.
Based on the above, the embodiment of the application provides a satellite energy saving method based on big data, which combines analysis and application of the big data to assist in adjusting and controlling activation or dormancy of satellites, so that invalid coverage of the satellites when satellite groups pass through an unmanned area or a region with little people are avoided, and the satellite energy saving effect is achieved.
Referring to fig. 1, fig. 1 is a flowchart of a satellite energy saving method based on big data according to an embodiment of the present application. As shown in fig. 1, the satellite energy saving method based on big data provided in the embodiment of the present application includes:
s101, acquiring current satellite position information of a satellite group according to the running orbit of the satellite.
The satellite position information refers to position information corresponding to a current position of the satellite group. Here, the satellite position information may be latitude and longitude information corresponding to a position where the satellite group is currently located.
For the above step S101, in implementation, the satellite position information of the current satellite group is obtained according to the actual orbit of the satellite.
S102, determining a target area corresponding to the current position of the satellite group based on the satellite position information, and collecting big data information corresponding to the target area in a historical time period.
The target area refers to a certain area on the earth through which the satellite group is passing. Here, the target area may be a country or a city, and the present application is not particularly limited. The historical time period refers to a past period of time, and as an alternative embodiment, the historical time period may be one day in the past, may be a week previous to the current time, or may be a month previous to the current time. For example, when the current time is 2022, 9, 1, thursday, the historical time period may be 2022, 8, 31, 00, to 2022, 8, 31, 23, 59, the historical time period may be 2022, 8, 22, one week, to 2022, 8, 28, sunday, or 2022, 8, 1, to 2022, 8, 31. The big data information refers to data information generated by the target region during a history period. Here, the big data information may be a population count in the target region or a number of registered users in the target region, or the like. Here, the history period includes a plurality of target periods, each of which corresponds to different big data information. Specifically, the target time period refers to a plurality of sub-time points within the history time period. For example, when the historical time period is 2022, 8, 31, 00:00 to 2022, 8, 31, 23:59, the target time period may be each hour of the historical time period; when the history period is 2022, 8, 22 days monday to 2022, 8, 28 days monday, the target period may be each day in the history period; when the history period is 2022, 8-month 1-day to 2022, 8-month 31-day, the target period may be each day of the history period.
Here, it should be noted that the above examples of the history period and the target period are merely examples, and in practice, the history period and the target period are not limited to the above examples.
For the above step S102, in implementation, the satellite group is located based on the satellite position information of the current position of the satellite group, and the target area corresponding to the current position of the satellite group is determined. Specifically, the latitude and longitude ranges corresponding to all areas on the earth are traversed, a target latitude and longitude range containing satellite position information of a satellite group is determined, and then the corresponding target area is determined according to the target latitude and longitude range. After the target region is determined, big data information generated in the target region in the historical time period is collected.
And S103, analyzing the big data information, and determining a network use peak time period corresponding to the target area in a plurality of target time periods.
The peak network usage period refers to a period of time in which the network demand is greatest in the target area. Here, as an example, continuing the example in step S102 described above, when the history period is one past day and the target period is each hour in the history period, the determined network usage peak period should also be one hour; when the historical time period is the week above the current time and the target time period is each day in the historical time period, the determined network usage peak time period should be one day; when the historical time period is the month last to the current time and the target time period is each day in the historical time period, the determined network usage peak time period should also be one day.
For the step S103, in implementation, after the big data information generated in the target area in the historical time period is collected, the big data information is analyzed to obtain the network usage peak time period corresponding to the target area.
According to the embodiment provided by the application, when big data analysis is performed, big data information of a target area can be collected through big data cloud, and then the collected big data information is uploaded to a network element of a ground 5G core network NWDAF (network data analytics function, network data analysis function) for analysis. The NWDAF is a data analysis network element based on the network data automatic sensing and analysis network, and participates in the full life cycle of network planning, construction, operation and maintenance, optimization and operation, so that the network is easy to maintain and control, the network resource utilization rate is improved, and the user experience is improved. The NWDAF can solve the data security problem and the signal overhead problem reported on a large amount of measured data, and can also solve the low-delay problem, thereby improving the rate of analysis on large data.
As an alternative embodiment, the big data information includes a number of network registered users within the target area.
The number of network-registered users refers to the number of users who use network electronic devices to perform network communication in a target area.
Specifically, the number of network registered users in the target area may be determined by network tracking the users while using the network electronic device.
For the step S103, the analyzing the big data information to determine the network usage peak time period corresponding to the target area includes:
and determining a target time period with the highest network registration user number in a plurality of target time periods according to the network registration user number corresponding to each target time period, and determining the target time period with the highest network registration user number as the network use peak time period.
For the above steps, in the implementation, after the number of network registered users corresponding to each target time period is obtained in step S102, the number of network registered users corresponding to each target time period is compared, a target time period with the highest number of network registered users is determined in a plurality of target time periods, and the target time period with the highest number of network registered users is determined as the network usage peak time period.
And S104, acquiring the current time, and determining a satellite communication demand vector according to the current time and the network use peak time period.
It should be noted that, the satellite communication demand vector refers to a load rate of the target area on satellite demand under the specified number of satellites, and the number of satellites can be determined to be turned on according to the satellite communication demand vector within the range of the preset load threshold of the satellite group. Here, the satellite communication need vector has a dynamic value, e.g., the value of the satellite communication need vector may be floating upwards before the network is in use for a peak period of time; after peak periods of network usage, the value of the satellite communication demand vector may float down, varying according to different times.
For the above step S104, in the implementation, after determining the network usage peak time period corresponding to the target area, the current time is obtained, and the satellite communication demand vector is determined according to the current time and the network usage peak time period.
For the step S104, the determining the satellite communication demand vector according to the current time and the network usage peak time period includes:
Step 1041, determining whether the current time is within the network usage peak time period.
Step 1042, if yes, determining the first preset load factor as the satellite communication demand vector.
Step 1043, if not, determining a second preset load factor as the satellite communication demand vector.
The preset load factor refers to a preset load factor of the target area under the specified satellite number. Here, the first preset load factor is greater than the second preset load factor. For example, the first preset load factor may be set to 80% and the second preset load factor may be set to 40%, which is not particularly limited in this application.
For the above steps 1041 to 1043, in a specific implementation, it is first determined whether the current time is within the peak network usage period. If the current time is within the peak network usage time period, the current satellite communication demand vector of the target area is considered to be higher, and the step 1042 is executed, where the first preset load factor is determined as the satellite communication demand vector. If the current time is not in the peak period of network usage, and the current satellite communication demand vector of the target area is considered to be lower, the step 1043 is executed, and the second preset load factor is determined as the satellite communication demand vector.
For example, continuing the embodiment in step S102, the current time is 2022, 9, 1, 10:35, the historical time period is 2022, 8, 31, 0:00, 2022, 8, 31, 23:59, the target time period is each hour of the historical time period, and the determined peak network usage time period is 10:00-11 in one day: 00, which is that it can be determined that the current time is within the peak network usage period, the above step 1042 is executed to determine the first preset load factor as the satellite communication demand vector. For example, continuing the embodiment in step S102, where the current time is 2022, 9, 1, and thursday, the historical time period is 2022, 8, 22, and one week to 2022, 8, 28, and sunday, the target time period is each day of the historical time period, and the determined peak network usage time period is three weeks in a week, which is that it may be determined that the current time is not within the peak network usage time period, step 1043 is performed, and the second preset load factor is determined as the satellite communication demand vector. In example three, when the current time is 2022, 9, 1, and the historical time period is 2022, 8, 1, and 2022, 8, 31, and the target time period is each day in the historical time period, the determined peak network usage time period is the first day in one month, which is when it may be determined that the current time is within the peak network usage time period, step 1042 is executed to determine the first preset load factor as the satellite communication demand vector.
S105, determining the number of satellites to be activated currently according to the satellite communication demand vector and a preset load threshold, and activating satellites corresponding to the number of satellites in the satellite group.
It should be noted that, the load threshold is preset to determine whether the load rate of the target area for the network needs to be greater in the current time. For example, the load threshold may be set to 60% in advance, and the present application is not particularly limited. The number of satellites refers to the number of satellites that currently need to be activated.
For the above step S105, in the implementation, the number of satellites currently required to be activated is determined according to the satellite communication demand vector determined in step S104 and the preset load threshold, and the satellites corresponding to the number of satellites in the satellite group are activated.
Referring to fig. 2, fig. 2 is a flowchart of a satellite activating method according to an embodiment of the present application. As shown in fig. 2, for the step S105, the determining, according to the satellite communication demand vector and a preset load threshold, the number of satellites that need to be activated currently, and activating the satellites corresponding to the number of satellites in the satellite group, includes:
S201, judging whether the satellite communication demand vector is greater than or equal to the load threshold;
s202, if yes, determining the first preset number as the satellite number.
And S203, if not, determining the second preset number as the satellite number.
It should be noted that the preset number refers to a preset number of satellites that need to be activated in the satellite group. Here, the first preset number is greater than the second preset number. And the first preset number and the second preset number are smaller than the number of satellites in the satellite group. For example, the first preset number may be set to 80 and the second preset number may be set to 30, which is not particularly limited in this application.
For the above steps S201 to S203, in the implementation, after determining the satellite communication demand vector, it is determined whether the satellite communication demand vector is greater than or equal to the load threshold. If the satellite communication demand vector is greater than or equal to the load threshold, it is considered that the current demand of the target area for the network is greater, for example, when the satellite acting area is a place where the urban openings are gathered, the demand of the user terminal for the network is greater, and a large number of satellites need to be activated, and step S202 is executed, where the larger first preset number is determined as the number of satellites. If the satellite communication demand vector is smaller than the load threshold, the demand of the target area for the network is considered to be smaller, for example, when the satellite action area is a region with few people, such as a desert, a remote sea area, an original forest, and the like, and the demand of the user terminal for the network is smaller, a large number of satellites do not need to be activated, and the energy-saving mode can be started, and the step S203 is executed, and the smaller second preset number is determined as the satellite number.
S204, determining satellites to be activated corresponding to the number of the satellites in the satellite group, and determining satellites except the satellites to be activated in the satellite group as dormant satellites.
S205, sending an activation instruction to the satellite to be activated, and controlling the satellite to be activated to enter an activation state.
S206, sending a dormancy instruction to the dormancy satellite, and controlling the dormancy satellite to enter a dormancy state.
It should be noted that, the satellite to be activated refers to a satellite that needs to be activated for data transmission. Dormant satellites refer to satellites that may enter a dormant state. The activation instruction refers to an instruction to wake up the satellite to be activated. The sleep instruction refers to an instruction to put the satellite into a sleep state.
For the above steps S204 to S206, in the implementation, after determining the number of satellites, determining the satellites to be activated corresponding to the number of satellites in the satellite group, and determining the satellites in the satellite group except for the satellites to be activated as dormant satellites. And sending an activation instruction to the satellite to be activated, and controlling the satellite to be activated to enter an activation state. And sending a dormancy instruction to the dormancy satellite, and controlling the dormancy satellite to enter a dormancy state. Therefore, the active command and the sleep command are sent to wake up the dormant satellite or enable the satellite to be in a dormant state, so that unnecessary data transmission of the satellite can be reduced when the network demand of a target area is smaller, energy saving of the satellite can be achieved in an unmanned area or a region with little human smoke, invalid coverage of the satellite when the satellite passes through the unmanned area or the region with little human smoke is avoided, and the energy saving effect of the satellite is achieved. When the demand of the target area for the network is large, a large number of satellites are activated, so that the network in the densely populated city can be ensured to be smooth.
According to the big data-based satellite energy saving method, firstly, current satellite position information of a satellite group is obtained according to the running orbit of a satellite; then, determining a target area corresponding to the current position of the satellite group based on the satellite position information, and collecting big data information corresponding to the target area in a historical time period; analyzing the big data information, and determining a network use peak time period corresponding to the target area in a plurality of target time periods; acquiring current time, and determining a satellite communication demand vector according to the current time and a network use peak time period; and finally, determining the number of satellites currently required to be activated according to the satellite communication demand vector and a preset load threshold, and activating satellites corresponding to the number of satellites in the satellite group.
Compared with the satellite energy-saving method in the prior art, the method has the advantages that the big data information of the target area is utilized to conduct data analysis, the network use peak time period of the target area is analyzed, the satellite communication demand vector is determined according to the network use peak time period and the current time, and the number of satellites of the currently required activated satellites is determined according to the satellite communication demand vector. Therefore, the method and the device accurately analyze the real demand of the target area for the network by utilizing the characteristics of large data quantity, high speed, high reality and the like of big data analysis, and efficiently and accurately assist in regulating the satellite state. And then the number of satellites to be activated is regulated according to the real demand, so that unnecessary data transmission of the satellites can be reduced when the demand of a target area for a network is smaller, thereby realizing satellite energy conservation in an unmanned area or a region with rare people, avoiding invalid coverage of the satellites when the satellite passes through the unmanned area or the region with rare people, and achieving the effect of satellite energy conservation. When the demand of the target area for the network is large, a large number of satellites are activated, so that the network in the densely populated city can be ensured to be smooth. According to the method and the device, by combining analysis and application of big data, the activation or dormancy of the satellite is regulated and controlled in an assisted mode, invalid coverage of the satellite when the satellite group passes through an unmanned area or a region with rare people is avoided, and therefore the effect of satellite energy conservation is achieved.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a satellite energy saving device based on big data according to an embodiment of the present application. As shown in fig. 3, the satellite power saving device 300 includes:
a position information obtaining module 301, configured to obtain current satellite position information of a satellite group according to an orbit of a satellite;
the big data information obtaining module 302 is configured to determine a target area corresponding to a current position of the satellite group based on the satellite position information, and collect big data information corresponding to the target area in a historical time period; the historical time period comprises a plurality of target time periods, and each target time period corresponds to different big data information;
the peak time period determining module 303 is configured to analyze the big data information, and determine a network usage peak time period corresponding to the target area from a plurality of target time periods;
the demand vector determining module 304 is configured to obtain a current time, and determine a satellite communication demand vector according to the current time and a peak time period of the network usage;
the satellite activation module 305 is configured to determine, according to the satellite communication demand vector and a preset load threshold, the number of satellites currently required to be activated, and activate satellites corresponding to the number of satellites in the satellite group.
Further, the big data information includes a number of network registered users within the target region; the peak time period determining module 303 is further configured to, when the peak time period determining module 303 is configured to analyze the big data information and determine a peak time period of network usage corresponding to the target area in a plurality of target time periods,:
and determining a target time period with the highest network registration user number in a plurality of target time periods according to the network registration user number corresponding to each target time period, and determining the target time period with the highest network registration user number as the network use peak time period.
Further, when the demand vector determining module 304 is configured to determine a satellite communication demand vector according to the current time and the peak time period of network usage, the demand vector determining module 304 is further configured to:
judging whether the current time is in the network use peak time period or not;
if yes, determining a first preset load rate as the satellite communication demand vector;
if not, determining a second preset load rate as the satellite communication demand vector; wherein the first preset load factor is greater than the second preset load factor.
Further, when the satellite activating module 305 is configured to determine, according to the satellite communication demand vector and a preset load threshold, the number of satellites currently required to be activated, and activate the satellites corresponding to the number of satellites in the satellite group, the satellite activating module 305 is further configured to:
judging whether the satellite communication demand vector is larger than or equal to the load threshold value or not;
if yes, determining the first preset number as the satellite number;
if not, determining a second preset number as the satellite number; wherein the first preset number is greater than the second preset number;
determining satellites to be activated corresponding to the number of the satellites in the satellite group, and determining satellites except the satellites to be activated in the satellite group as dormant satellites;
sending an activation instruction to the satellite to be activated, and controlling the satellite to be activated to enter an activation state;
and sending a dormancy instruction to the dormancy satellite, and controlling the dormancy satellite to enter a dormancy state.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 4, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.
The memory 420 stores machine-readable instructions executable by the processor 410, and when the electronic device 400 is running, the processor 410 communicates with the memory 420 through the bus 430, and when the machine-readable instructions are executed by the processor 410, the steps of the big data based satellite energy saving method in the method embodiments shown in fig. 1 and fig. 2 can be executed, and the specific implementation can refer to the method embodiments and will not be repeated herein.
The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps of the big data based satellite energy saving method in the method embodiments shown in the foregoing fig. 1 and fig. 2 may be executed, and a specific implementation manner may refer to the method embodiments and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should be noted that: like reference numerals and letters in the following figures denote like items, and thus once an item is defined in one figure, no further definition or explanation of it is required in the following figures, and furthermore, the terms "first," "second," "third," etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the foregoing examples are merely specific embodiments of the present application, and are not intended to limit the scope of the present application, but the present application is not limited thereto, and those skilled in the art will appreciate that while the foregoing examples are described in detail, the present application is not limited thereto. Any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or make equivalent substitutions for some of the technical features within the technical scope of the disclosure of the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. A satellite energy conservation method based on big data, the satellite energy conservation method comprising:
acquiring current satellite position information of a satellite group according to the running orbit of a satellite;
determining a target area corresponding to the current position of the satellite group based on the satellite position information, and collecting big data information corresponding to the target area in a historical time period; the historical time period comprises a plurality of target time periods, and each target time period corresponds to different big data information;
analyzing the big data information, and determining a network use peak time period corresponding to the target area in a plurality of target time periods;
acquiring current time, and determining a satellite communication demand vector according to the current time and a network use peak time period;
determining the number of satellites currently required to be activated according to the satellite communication demand vector and a preset load threshold, and activating satellites corresponding to the number of satellites in the satellite group;
the determining a satellite communication demand vector according to the current time and the network usage peak time period comprises the following steps:
judging whether the current time is in the network use peak time period or not;
If yes, determining a first preset load rate as the satellite communication demand vector;
if not, determining a second preset load rate as the satellite communication demand vector; wherein the first preset load factor is greater than the second preset load factor.
2. The satellite energy saving method of claim 1, wherein the big data information comprises a number of network registered users within the target region; the analyzing the big data information, and determining a network usage peak time period corresponding to the target area in a plurality of target time periods, includes:
and determining a target time period with the highest network registration user number in a plurality of target time periods according to the network registration user number corresponding to each target time period, and determining the target time period with the highest network registration user number as the network use peak time period.
3. The method for saving energy by satellite according to claim 1, wherein determining the number of satellites currently required to be activated according to the satellite communication demand vector and a preset load threshold, and activating the satellites corresponding to the number of satellites in the satellite group, comprises:
Judging whether the satellite communication demand vector is larger than or equal to the load threshold value or not;
if yes, determining the first preset number as the satellite number;
if not, determining a second preset number as the satellite number; wherein the first preset number is greater than the second preset number;
determining satellites to be activated corresponding to the number of the satellites in the satellite group, and determining satellites except the satellites to be activated in the satellite group as dormant satellites;
sending an activation instruction to the satellite to be activated, and controlling the satellite to be activated to enter an activation state;
and sending a dormancy instruction to the dormancy satellite, and controlling the dormancy satellite to enter a dormancy state.
4. A satellite energy conservation device based on big data, the satellite energy conservation device comprising:
the position information acquisition module is used for acquiring the current satellite position information of the satellite group according to the running orbit of the satellite;
the big data information acquisition module is used for determining a target area corresponding to the current position of the satellite group based on the satellite position information and acquiring big data information corresponding to the target area in a historical time period; the historical time period comprises a plurality of target time periods, and each target time period corresponds to different big data information;
The peak time period determining module is used for analyzing the big data information and determining a network use peak time period corresponding to the target area in a plurality of target time periods;
the demand vector determining module is used for obtaining the current time and determining a satellite communication demand vector according to the current time and the network use peak time period;
the satellite activation module is used for determining the number of satellites which are required to be activated currently according to the satellite communication demand vector and a preset load threshold value, and activating satellites corresponding to the number of satellites in the satellite group;
the demand vector determining module is further configured to, when determining a satellite communication demand vector according to the current time and the network usage peak time period,:
judging whether the current time is in the network use peak time period or not;
if yes, determining a first preset load rate as the satellite communication demand vector;
if not, determining a second preset load rate as the satellite communication demand vector; wherein the first preset load factor is greater than the second preset load factor.
5. The satellite energy saver of claim 4, wherein the big data information includes a number of network registered users within the target area; the peak time period determining module is used for analyzing the big data information, and when determining that the network corresponding to the target area uses the peak time period in a plurality of target time periods, the peak time period determining module is further used for:
And determining a target time period with the highest network registration user number in a plurality of target time periods according to the network registration user number corresponding to each target time period, and determining the target time period with the highest network registration user number as the network use peak time period.
6. The satellite energy saving device of claim 4, wherein the satellite activation module is further configured to, when determining, according to the satellite communication demand vector and a preset load threshold, a number of satellites currently required to be activated and activating satellites corresponding to the number of satellites in the satellite group:
judging whether the satellite communication demand vector is larger than or equal to the load threshold value or not;
if yes, determining the first preset number as the satellite number;
if not, determining a second preset number as the satellite number; wherein the first preset number is greater than the second preset number;
determining satellites to be activated corresponding to the number of the satellites in the satellite group, and determining satellites except the satellites to be activated in the satellite group as dormant satellites;
sending an activation instruction to the satellite to be activated, and controlling the satellite to be activated to enter an activation state;
And sending a dormancy instruction to the dormancy satellite, and controlling the dormancy satellite to enter a dormancy state.
7. An electronic device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating via said bus when the electronic device is running, said machine readable instructions when executed by said processor performing the steps of the big data based satellite power saving method according to any of claims 1 to 3.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the big data based satellite power saving method according to any of claims 1 to 3.
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