CN114189867A - Base station-based resource processing method, device and device - Google Patents
Base station-based resource processing method, device and device Download PDFInfo
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- CN114189867A CN114189867A CN202111424843.0A CN202111424843A CN114189867A CN 114189867 A CN114189867 A CN 114189867A CN 202111424843 A CN202111424843 A CN 202111424843A CN 114189867 A CN114189867 A CN 114189867A
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
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Abstract
The application provides a resource processing method, a device and equipment based on a base station, which relate to the communication technology, and the method comprises the following steps: when the first base station is detected to have a fault, determining idle resources of a second base station corresponding to the first base station and the fault occurrence time; the first base station and the second base station are different types of provider equipment; predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments; and according to the traffic of the first base station at the next moment, allocating the idle resources of the second base station to the access user of the first base station. According to the method, the idle resources are allocated to the access users of the first base station in a targeted manner through the different network base station according to the constantly changing traffic of the first base station, and the technical problem of low utilization rate of the base station resources is solved.
Description
Technical Field
The present application relates to communications technologies, and in particular, to a method, an apparatus, and a device for processing resources based on a base station.
Background
Currently, with the rapid development of wireless communication technology, the number of access users such as 4/5G is also rapidly increasing, and a base station needs to provide a wireless network for more access users.
In the prior art, when a base station provides a wireless network for an access user, base stations of different operators are generally forcibly combined to obtain combined base station resources, and then the combined base station resources are allocated to the access user in a corresponding area.
However, in the prior art, since the number of access users in an area is dynamically changed, and the combined base station resource is a fixed value, when the combined base station resource is allocated to an access user, the base station cannot dynamically load all the access users, and thus the utilization rate of the base station resource is low.
Disclosure of Invention
The application provides a resource processing method, device and equipment based on a base station, which are used for solving the technical problem of low utilization rate of base station resources.
In a first aspect, the present application provides a resource processing method based on a base station, which is applied to an electronic device, and the method includes:
when a first base station is detected to have a fault, determining idle resources of a second base station corresponding to the first base station and the fault occurrence time; the first base station and the second base station are different types of provider equipment;
predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments;
and allocating the idle resources of the second base station to the access user of the first base station according to the traffic of the first base station at the next moment.
Further, when it is detected that the first base station fails, determining idle resources of a second base station corresponding to the first base station and a failure occurrence time includes:
when the first base station is detected to have a fault, determining the fault occurrence time of the first base station, and determining a second base station which is located in the same area as the first base station according to the corresponding relation among the first base station, the second base station and the area;
determining idle resources of the second base station.
Further, determining the idle resources of the second base station includes:
determining idle resources of the second base station according to the average value of the traffic of the second base station in a preset time range, a preset weight and the maximum available resources of the second base station;
wherein the idle resource of the second base station is w ═ P- (a + a ×) B; wherein P is the maximum available resource of the second base station, a is the average value of the traffic of the second base station within a preset time range, and B is the preset weight.
Further, allocating the idle resource of the second base station to the access user of the first base station according to the traffic of the first base station at the next time, includes:
determining a first access user number corresponding to the traffic of the first base station at the next moment and a second access user number corresponding to the idle resource;
if the idle resource of the second base station is determined to be smaller than the traffic of the first base station at the next moment, determining that the number of second access users corresponding to the idle resource is the number of first users to be allocated at the next moment;
allocating the idle resource of the second base station to the access user of the first base station according to the number of the first users to be allocated at the next moment;
if the idle resource of the second base station is determined to be more than or equal to the traffic of the first base station at the next moment, determining the first access user number as a second user number to be allocated at the next moment;
and allocating the idle resources of the second base station to the access users of the first base station according to the number of the second users to be allocated at the next moment.
Further, the method further comprises:
obtaining internal parameters of the first base station, and predicting the traffic of the first base station at the current moment according to a preset traffic prediction model;
based on the internal parameters and the traffic volume at the current moment, judging the running state of the first base station at the current moment through preset base station information;
and when the running state of the first base station at the current moment is abnormal, determining that the first base station has a fault.
Further, the method further comprises:
acquiring the number of access users of a base station at different moments;
determining the time interval of the number of access users at each moment in a plurality of preset time intervals;
counting the traffic corresponding to the number of the access users in each time interval;
and training an initial time training model according to the time intervals and the traffic corresponding to the number of the access users in each time interval until the time sequence model converges to obtain a service prediction model.
In a second aspect, the present application provides a base station-based resource processing apparatus, which is applied to an electronic device, and the apparatus includes:
a first determining unit, configured to determine, when a failure of a first base station is detected, idle resources of a second base station corresponding to the first base station and a failure occurrence time; the first base station and the second base station are different types of provider equipment;
the first prediction unit is used for predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments;
and the allocation unit is used for allocating the idle resources of the second base station to the access user of the first base station according to the traffic of the first base station at the next moment.
Further, the first determination unit includes:
the first determining module is used for determining the fault occurrence time of the first base station when the first base station is detected to have a fault, and determining a second base station which is located in the same area as the first base station according to the corresponding relation among the first base station, the second base station and the area;
a second determining module, configured to determine idle resources of the second base station.
Further, the second determining module is specifically configured to:
determining idle resources of the second base station according to the average value of the traffic of the second base station in a preset time range, a preset weight and the maximum available resources of the second base station;
wherein the idle resource of the second base station is w ═ P- (a + a ×) B; wherein P is the maximum available resource of the second base station, a is the average value of the traffic of the second base station within a preset time range, and B is the preset weight.
Further, the allocation unit includes:
a third determining module, configured to determine a first number of access users corresponding to a traffic of the first base station at a next time and a second number of access users corresponding to the idle resource;
a fourth determining module, configured to determine, if it is determined that the idle resource of the second base station is smaller than the traffic volume of the first base station at the next time, that the number of second access users corresponding to the idle resource is the number of first to-be-allocated users at the next time;
a first allocation module, configured to allocate, according to the number of first users to be allocated at the next time, idle resources of the second base station to access users of the first base station;
a fifth determining module, configured to determine that the first number of access users is a second number of users to be allocated at a next time if it is determined that idle resources of the second base station are greater than or equal to a traffic volume of the first base station at the next time;
and the second allocating module is used for allocating the idle resources of the second base station to the access users of the first base station according to the number of the second users to be allocated at the next moment.
Further, the apparatus further comprises:
the second prediction unit is used for acquiring internal parameters of the first base station and predicting the traffic of the first base station at the current moment according to a preset traffic prediction model;
the judging unit is used for judging the running state of the first base station at the current moment through preset base station information based on the internal parameters and the traffic at the current moment;
and the second determining unit is used for determining that the first base station has a fault when the running state of the first base station at the current moment is abnormal.
Further, the apparatus further comprises:
the base station comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring the number of access users of the base station at different moments;
a third determining unit, configured to determine, in a plurality of preset time intervals, a time interval in which the number of access users at each time is located;
a counting unit, which is used for counting the service volume corresponding to the number of the access users in each time interval;
and the training unit is used for training an initial time training model according to the time intervals and the traffic corresponding to the number of the access users in each time interval until the time sequence model converges to obtain a service prediction model.
In a third aspect, the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program operable on the processor, and the processor implements the method of the first aspect when executing the computer program.
In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon computer-executable instructions for implementing the method of the first aspect when executed by a processor.
In a fifth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements the method of the first aspect.
According to the resource processing method, device and equipment based on the base station, when a first base station is detected to have a fault, idle resources of a second base station corresponding to the first base station and the fault occurrence time are determined; the first base station and the second base station are different types of provider equipment; predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments; and according to the traffic of the first base station at the next moment, allocating the idle resources of the second base station to the access user of the first base station. In the scheme, when a first base station is detected to have a fault, the idle resources of a second base station corresponding to the first base station and the fault occurrence time are determined, then the traffic of the first base station at the next time is predicted based on a preset service prediction model and the fault occurrence time, and finally the idle resources of the second base station are allocated to the access user of the first base station according to the traffic of the first base station at the next time based on the load capacity of the idle resources. Therefore, according to the traffic of the first base station at the next moment predicted by the traffic prediction model, the idle resources of the second base station are allocated to the access users of the first base station, so that the idle resources are allocated to the access users of the first base station in a targeted manner through the different-network base station according to the traffic of the first base station changing at the moment, the phenomenon that the first base station still has the idle resources under the conditions of high resource load, resource shortage and the like is avoided, and the technical problem of low utilization rate of the base station resources is solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a schematic flowchart of a resource processing method based on a base station according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another base station-based resource processing method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a base station-based resource processing apparatus according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of another base station-based resource processing apparatus according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present application.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure.
In one example, as wireless communication technology rapidly develops, the number of access users such as 4/5G is rapidly increasing, and a base station needs to provide wireless networks for more access users. In the prior art, when a base station provides a wireless network for an access user, base stations of different operators are generally forcibly combined to obtain combined base station resources, and then the combined base station resources are allocated to the access user in a corresponding area. However, in the prior art, since the number of access users in an area is dynamically changed, and the combined base station resource is a fixed value, when the combined base station resource is allocated to an access user, the base station cannot dynamically load all the access users, and thus the utilization rate of the base station resource is low.
The application provides a resource processing method, device and equipment based on a base station, and aims to solve the technical problems in the prior art.
The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic flowchart of a resource processing method based on a base station according to an embodiment of the present application, and is applied to an electronic device, as shown in fig. 1, the method includes:
101. when the first base station is detected to have a fault, determining idle resources of a second base station corresponding to the first base station and the fault occurrence time; the first base station and the second base station are different types of provider equipment.
For example, the execution subject of this embodiment may be an electronic device, or a terminal device, or a resource processing device or device based on a base station, or other devices or devices that may execute this embodiment, which is not limited in this respect. In this embodiment, an execution main body is described as an electronic device.
Firstly, the operation condition of a first base station needs to be detected, when the first base station is detected to have a fault, the fault occurrence time of the first base station is determined, a second base station which is located in the same area with the first base station is determined according to the corresponding relation of the first base station, the second base station and the area, then an acquisition request is sent to the second base station, the acquisition request is used for determining the resource condition of the second base station, after the second base station receives the acquisition request, the second base station judges whether the access user of the first base station can be loaded or not on the basis of ensuring the resources used by the normal operation of the second base station, if the access user of the first base station can be loaded, the idle resources of the second base station are determined, and finally the idle resources are sent to electronic equipment, so that the electronic equipment obtains the idle resources of the second base station.
The first base station and the second base station are different types of provider equipment, coverage areas of the first base station and the second base station are basically the same, and under the condition that the first base station and the second base station operate normally, the first base station and the second base station respectively provide resources for access users in the areas.
102. Predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments.
For example, each time is located in a different time interval, and the service at each time is correspondingly located in a different time interval, so that a final service prediction model is obtained through multiple training according to the traffic of the base station in different time intervals as sample data, and the time series model is a supervision algorithm generally applicable in the field of machine learning at present, for example, the time series model may be: long Short-Term Memory network (LSTM), Auto-Regressive Moving Average Model (ARMA), and other algorithm models. The traffic is the total voice traffic and the total data traffic of the base station in a certain time interval, and further may include the maximum number of access users, total traffic on the internet, and call traffic of the base station in a certain time interval.
For example, the traffic of the base station at different times can be predicted according to the traffic prediction model, when the failure occurrence time of the first base station is obtained, the failure occurrence time is input into the traffic prediction model, and the traffic of the first base station at the next time can be predicted according to the traffic prediction model.
103. And according to the traffic of the first base station at the next moment, allocating the idle resources of the second base station to the access user of the first base station.
For example, when acquiring the traffic volume of the first base station at the next time, the electronic device first determines the load capacity of the idle resource of the second base station, and if the idle resource can load the entire traffic volume at the next time, the access terminals of all the access users of the first base station may be changed into the second base station, and the idle resource of the second base station is allocated to all the access users of the first base station according to the traffic volume of the first base station at the next time. Or, if the idle resources cannot load the entire traffic volume at the next time, the access end of a part of access users of the first base station may be changed into the second base station, and the idle resources of the second base station are allocated to the part of access users of the first base station according to the traffic volume of the first base station at the next time, at which time the second base station loads the traffic volume of the part at the next time. And if the second base station has no idle resources, not allocating the resources.
For example, the traffic of the first base station at the next time is 100 access subscribers, the total internet traffic a and the call traffic b corresponding to 100 access subscribers, so if the idle resources can load the total internet traffic a and the call traffic b corresponding to 100 access subscribers at the next time, the access ends of the 100 access subscribers of the first base station may be changed into the second base station, and the idle resources of the second base station are allocated to all the access subscribers of the first base station according to the traffic of the first base station at the next time. Or, if the idle resource cannot load the total internet traffic a and the call traffic b corresponding to 100 access users at the next time, and it is necessary to determine the number of access users that the idle resource can load, for example, it is determined that the number of access users that the idle resource can load is 50 according to the total internet traffic a, the call traffic b, and the idle resource corresponding to 100 access users, then the access ends of 50 access users of the first base station may be changed into the second base station, and the idle resource of the second base station is allocated to 50 access users of the first base station according to the traffic of the first base station at the next time. Or if the idle resources cannot load the total internet traffic a and the total call traffic b corresponding to the 100 access users at the next moment, the resource allocation is not performed.
In the embodiment of the application, when a first base station is detected to have a fault, determining idle resources of a second base station corresponding to the first base station and the moment of the fault; the first base station and the second base station are different types of provider equipment. Predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments. And according to the traffic of the first base station at the next moment, allocating the idle resources of the second base station to the access user of the first base station. In the scheme, when a first base station is detected to have a fault, the idle resources of a second base station corresponding to the first base station and the fault occurrence time are determined, then the traffic of the first base station at the next time is predicted based on a preset service prediction model and the fault occurrence time, and finally the idle resources of the second base station are allocated to the access user of the first base station according to the traffic of the first base station at the next time based on the load capacity of the idle resources. Therefore, according to the traffic of the first base station at the next moment predicted by the traffic prediction model, the idle resources of the second base station are allocated to the access users of the first base station, so that the idle resources are allocated to the access users of the first base station in a targeted manner through the different-network base station according to the traffic of the first base station changing at the moment, the phenomenon that the first base station still has the idle resources under the conditions of high resource load, resource shortage and the like is avoided, and the technical problem of low utilization rate of the base station resources is solved.
Fig. 2 is a schematic flowchart of another base station-based resource processing method according to an embodiment of the present application, and as shown in fig. 2, the method includes:
201. and acquiring the number of access users of the base station at different moments.
Illustratively, the electronic device may acquire access user terminals of the base station at different times, each access user terminal representing an access user, and therefore, the number of access users of the base station at different times may be determined according to the number of access user terminals, where the access user terminal includes: mobile terminal, thing networking terminal etc..
202. And determining the time interval of the number of the access users at each moment in a plurality of preset time intervals.
For example, the electronic device may preset a plurality of time intervals, determine each time, determine a time interval at which each time is located, and further determine a time interval at which the number of access users at each time is located, so that there are a plurality of access users in each time interval, and further may determine the traffic volume in each time interval. The time interval is a preset data acquisition interval, or may be a time interval determined by calculating according to data sampling points, and the timing unit of the time interval may be a conventional timing unit such as seconds and minutes, for example, the base station sampling data interval is 60 seconds, and the corresponding time interval is 60 seconds; similarly, the time interval is the final result of subtracting the first data sampling time from the second data sampling.
203. And counting the traffic corresponding to the number of the access users in each time interval.
Illustratively, the traffic includes voice traffic data, data traffic data, and the like, and the electronic device may count the voice traffic data and the data traffic data corresponding to the number of the access users in each time interval, and determine a ratio of the voice traffic data to the traffic and a ratio of the data traffic data to the traffic.
204. And training the initial time training model according to the time intervals and the traffic corresponding to the number of the access users in each time interval until the time sequence model converges to obtain a service prediction model.
For example, the electronic device may train an initial time training model according to the time interval and the voice service data and the data service data corresponding to the number of the access users in each time interval, and obtain a service prediction model when the time series model converges.
205. And obtaining internal parameters of the first base station, and predicting the traffic of the first base station at the current moment according to a preset traffic prediction model.
Illustratively, the internal parameters include a license standard, a bandwidth and other parameters of the first base station, and the electronic device may acquire the license standard, the bandwidth and other parameters of the first base station, and then input the current time into a preset service prediction model to predict the traffic of the first base station at the current time. Among the License standards, GNU General Public License (GPL), GNU Lesser General Public License (LGPL), BSD License, MIT License, Mozilla License1.1(MPL), Common Development and Distribution License (CDDL), Apache License, and the like.
206. And judging the running state of the first base station at the current moment through preset base station information based on the internal parameters and the traffic at the current moment.
For example, the preset base station information is an abnormal judgment standard in the case of the current networks 2G, 3G, 4G, 5G, the planned network 6G, and the like, and it should be noted that, for base stations with different parameter types, the upper limits of the corresponding traffic volumes are different, and for base stations with different network systems, the upper limits of the corresponding traffic volumes are different. Meanwhile, the base station exception standards of different network systems and different parameter types are also different, and the actual current network standards of different operators need to be referred to specifically. The electronic equipment can determine base station information corresponding to the current-time traffic based on the internal parameters and the current-time traffic, and then judge the operating state of the first base station at the current time according to the base station information, wherein the operating state includes base station phenomena affecting user voice and internet perception conditions, such as base station faults, high base station load, base station interference and the like.
For example, based on the internal parameters and the traffic volume at the current time, the electronic device determines that the base station information corresponding to the traffic volume at the current time is an abnormal judgment standard under the condition of 2G, and then judges the operating state of the first base station at the current time according to the abnormal judgment standard of 2G.
207. And when the running state of the first base station at the current moment is abnormal, determining that the first base station has a fault.
Exemplarily, when the operation state of the first base station at the current moment is the base station high load, the electronic device determines that the first base station fails; or when the running state of the first base station at the current moment is a base station fault, the electronic equipment determines that the first base station has the fault; or, when the operation state of the first base station at the current moment is the base station interference, the electronic device determines that the first base station has a fault.
208. When the first base station is detected to have a fault, determining the fault occurrence time of the first base station, and determining a second base station which is positioned in the same area with the first base station according to the corresponding relation among the first base station, the second base station and the area; the first base station and the second base station are different types of provider equipment.
For example, when detecting that the first base station fails, the electronic device may determine a failure occurrence time when the first base station fails, and determine a second base station located in the same area as the first base station according to a correspondence relationship among the first base station, the second base station, and the area. The first base station and the second base station are different types of provider equipment, and coverage areas of the first base station and the second base station are basically overlapped.
209. Determining idle resources of the second base station.
In one example, the idle resources of the second base station are determined according to the average value of the traffic of the second base station in a preset time range, a preset weight and the maximum available resources of the second base station; wherein, the idle resource of the second base station is w ═ P- (a + a × B); wherein, P is the maximum available resource of the second base station, A is the average value of the traffic of the second base station in the preset time range, and B is the preset weight.
Exemplarily, the electronic device determines the maximum available resource of the second base station, and then determines the idle resource of the second base station according to an average value and a preset weight of traffic of the second base station within a preset time range, where P is the maximum available resource of the second base station, a is the average value of the traffic of the second base station within the preset time range, the traffic may refer to the number of access users and the traffic usage resource of the access users, and B is the preset weight.
210. Predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments.
For example, this step can be referred to as step 102 in fig. 1, and is not described again.
211. And determining the number of first access users corresponding to the traffic of the first base station at the next moment and the number of second access users corresponding to the idle resources.
For example, the electronic device may determine, according to the traffic of the first base station at the next time, a first number of access users corresponding to the traffic of the next time, and determine a second number of access users corresponding to the idle resource.
212. And if the idle resource of the second base station is smaller than the traffic of the first base station at the next moment, determining that the number of the second access users corresponding to the idle resource is the number of the first to-be-allocated users at the next moment.
For example, the electronic device compares the idle resource of the second base station with the traffic of the first base station at the next time to determine the load capacity of the idle resource of the second base station, and if the idle resource is smaller than the total traffic of the first base station at the next time, it is determined that the number of second access users corresponding to the idle resource is the number of first users to be allocated at the next time, and at this time, the idle resource may bear part of the traffic of the first base station at the next time, that is, bear part of the access users of the first base station at the next time.
213. And allocating the idle resources of the second base station to the access users of the first base station according to the number of the first users to be allocated at the next moment.
For example, the electronic device may change the access end of a part of access users of the first base station to the second base station at the next time according to the first number of users to be allocated at the next time, and allocate the idle resources of the second base station to the part of access users of the first base station according to the traffic volume of the first base station at the next time.
214. And if the idle resource of the second base station is determined to be more than or equal to the traffic of the first base station at the next moment, determining the number of the first access users as the number of the second users to be distributed at the next moment.
Exemplarily, if the idle resource is greater than or equal to the traffic of the first base station at the next time, it indicates that the idle resource can load the entire traffic of the first base station at the next time, and further determines that the first access user number is the second to-be-allocated user number at the next time, at this time, the idle resource can bear the entire traffic of the first base station at the next time, that is, bear all the access users of the first base station at the next time.
215. And allocating the idle resources of the second base station to the access users of the first base station according to the number of the second users to be allocated at the next moment.
For example, the electronic device may change access ends of all access users of the first base station to the second base station at the next time according to the second number of users to be allocated at the next time, and allocate idle resources of the second base station to all access users of the first base station according to the traffic volume of the first base station at the next time.
In the embodiment of the application, the number of access users of the base station at different moments is obtained. And determining the time interval of the number of the access users at each moment in a plurality of preset time intervals. And counting the traffic corresponding to the number of the access users in each time interval. And training the initial time training model according to the time intervals and the traffic corresponding to the number of the access users in each time interval until the time sequence model converges to obtain a service prediction model. And obtaining internal parameters of the first base station, and predicting the traffic of the first base station at the current moment according to a preset traffic prediction model. And judging the running state of the first base station at the current moment through preset base station information based on the internal parameters and the traffic at the current moment. And when the running state of the first base station at the current moment is abnormal, determining that the first base station has a fault. When the first base station is detected to have a fault, determining the fault occurrence time of the first base station, and determining a second base station which is positioned in the same area with the first base station according to the corresponding relation among the first base station, the second base station and the area; the first base station and the second base station are different types of provider equipment. Determining idle resources of the second base station. Predicting the traffic of the first base station at the next moment based on a preset traffic prediction model and the fault occurrence moment; the service prediction model is obtained by training according to services at different moments. And determining the number of first access users corresponding to the traffic of the first base station at the next moment and the number of second access users corresponding to the idle resources. And if the idle resource of the second base station is smaller than the traffic of the first base station at the next moment, determining that the number of the second access users corresponding to the idle resource is the number of the first to-be-allocated users at the next moment. And allocating the idle resources of the second base station to the access users of the first base station according to the number of the first users to be allocated at the next moment. And if the idle resource of the second base station is determined to be more than or equal to the traffic of the first base station at the next moment, determining the number of the first access users as the number of the second users to be distributed at the next moment. And allocating the idle resources of the second base station to the access users of the first base station according to the number of the second users to be allocated at the next moment. Therefore, according to the traffic of the first base station at the next moment predicted by the traffic prediction model, the idle resources of the second base station are allocated to the access users of the first base station, so that the idle resources are allocated to the access users of the first base station in a targeted manner through the different-network base station according to the traffic of the first base station changing at the moment, the phenomenon that the first base station still has the idle resources under the conditions of high resource load, resource shortage and the like is avoided, and the technical problem of low utilization rate of the base station resources is solved.
Fig. 3 is a schematic structural diagram of a resource processing apparatus based on a base station according to an embodiment of the present application, which is applied to an electronic device, and as shown in fig. 3, the apparatus includes:
a first determining unit 31, configured to determine, when it is detected that a first base station fails, idle resources of a second base station corresponding to the first base station and a failure occurrence time; the first base station and the second base station are different types of provider equipment.
A first prediction unit 32, configured to predict traffic of the first base station at a next time based on a preset traffic prediction model and a fault occurrence time; the service prediction model is obtained by training according to services at different moments.
And an allocating unit 33, configured to allocate the idle resource of the second base station to the access user of the first base station according to the traffic of the first base station at the next time.
The apparatus of this embodiment may execute the technical solution in the method, and the specific implementation process and the technical principle are the same, which are not described herein again.
Fig. 4 is a schematic structural diagram of another resource processing apparatus based on a base station according to an embodiment of the present application, and based on the embodiment shown in fig. 3, as shown in fig. 4, the first determining unit 31 includes:
the first determining module 311 is configured to determine a failure occurrence time of the first base station when it is detected that the first base station fails, and determine a second base station located in the same area as the first base station according to a correspondence relationship among the first base station, the second base station, and the area.
A second determining module 312, configured to determine idle resources of the second base station.
In an example, the second determining module 312 is specifically configured to:
determining idle resources of the second base station according to the average value of the traffic of the second base station in a preset time range, a preset weight and the maximum available resources of the second base station; wherein, the idle resource of the second base station is w ═ P- (a + a × B); wherein, P is the maximum available resource of the second base station, A is the average value of the traffic of the second base station in the preset time range, and B is the preset weight.
In one example, the allocation unit 33 includes:
the third determining module 331 is configured to determine a first number of access users corresponding to a traffic of the first base station at a next time and a second number of access users corresponding to idle resources.
A fourth determining module 332, configured to determine, if it is determined that the idle resource of the second base station is smaller than the traffic volume of the first base station at the next time, that the number of second access users corresponding to the idle resource is the first number of users to be allocated at the next time.
The first allocating module 333 is configured to allocate, according to the first number of users to be allocated at the next time, the idle resource of the second base station to the access user of the first base station.
A fifth determining module 334, configured to determine that the first number of access users is the second number of users to be allocated at the next time if it is determined that the idle resource of the second base station is greater than or equal to the traffic volume of the first base station at the next time.
The second allocating module 335 is configured to allocate, according to the second number of users to be allocated at the next time, the idle resources of the second base station to the access user of the first base station.
In one example, the apparatus further comprises:
the second prediction unit 41 is configured to obtain internal parameters of the first base station, and predict traffic of the first base station at the current time according to a preset traffic prediction model.
And a determining unit 42, configured to determine, based on the internal parameter and the traffic volume at the current time, an operating state of the first base station at the current time according to preset base station information.
A second determining unit 43, configured to determine that the first base station has a fault when the operation state of the first base station at the current time is abnormal.
In one example, the apparatus further comprises:
an obtaining unit 44, configured to obtain the number of access users of the base station at different time.
A third determining unit 45, configured to determine, in a plurality of preset time intervals, a time interval in which the number of access users at each time is located.
And a counting unit 46, configured to count traffic corresponding to the number of access users in each time interval.
And the training unit 47 is configured to train the initial time training model according to the time interval and the traffic corresponding to the number of the access users in each time interval until the time series model converges to obtain a traffic prediction model.
The apparatus of this embodiment may execute the technical solution in the method, and the specific implementation process and the technical principle are the same, which are not described herein again.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 5, the electronic device includes: memory 51, processor 52.
The memory 51 has stored therein a computer program that is executable on the processor 52.
The processor 52 is configured to perform the methods provided in the embodiments described above.
The electronic device further comprises a receiver 53 and a transmitter 54. The receiver 53 is used for receiving commands and data transmitted from an external device, and the transmitter 54 is used for transmitting commands and data to an external device.
Fig. 6 is a block diagram of an electronic device, which may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, etc., according to an embodiment of the present application.
The processing component 602 generally controls overall operation of the device 600, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component 602 may include one or more processors 620 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 602 can include one or more modules that facilitate interaction between the processing component 602 and other components. For example, the processing component 602 can include a multimedia module to facilitate interaction between the multimedia component 608 and the processing component 602.
The memory 604 is configured to store various types of data to support operations at the apparatus 600. Examples of such data include instructions for any application or method operating on device 600, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 604 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The multimedia component 608 includes a screen that provides an output interface between the device 600 and the user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 608 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the device 600 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 610 is configured to output and/or input audio signals. For example, audio component 610 includes a Microphone (MIC) configured to receive external audio signals when apparatus 600 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 604 or transmitted via the communication component 616. In some embodiments, audio component 610 further includes a speaker for outputting audio signals.
The I/O interface 612 provides an interface between the processing component 602 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor component 614 includes one or more sensors for providing status assessment of various aspects of the apparatus 600. For example, the sensor component 614 may detect an open/closed state of the device 600, the relative positioning of the components, such as a display and keypad of the device 600, the sensor component 614 may also detect a change in position of the device 600 or a component of the device 600, the presence or absence of user contact with the device 600, orientation or acceleration/deceleration of the device 600, and a change in temperature of the device 600. The sensor assembly 614 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 614 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 614 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 616 is configured to facilitate communications between the apparatus 600 and other devices in a wired or wireless manner. The apparatus 600 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 616 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 616 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus 600 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer readable storage medium comprising instructions, such as the memory 604 comprising instructions, executable by the processor 620 of the apparatus 600 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
Embodiments of the present application also provide a non-transitory computer-readable storage medium, where instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method provided by the above embodiments.
An embodiment of the present application further provides a computer program product, where the computer program product includes: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to perform the solution provided by any of the embodiments described above.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (15)
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