CN108833261B - Client message pushing optimization method and device based on Android platform - Google Patents
Client message pushing optimization method and device based on Android platform Download PDFInfo
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Abstract
The embodiment of the invention discloses an Android platform-based client message push optimization method and device, electronic equipment and a storage medium, relates to the technical field of message push, and aims to solve the problem that the message push arrival rate is not high in the prior art. The method comprises the following steps: testing the model to be optimized according to a plurality of preset pushing schemes, and selecting the pushing scheme with the highest message pushing arrival rate; and sending the selected pushing scheme to the model to be optimized for execution.
Description
Technical Field
The invention relates to the technical field of message pushing, in particular to a method and a device for optimizing message pushing based on an Android platform client, electronic equipment and a storage medium.
Background
With the popularity and development of mobile devices, the market of the Android system of google in the current mobile terminal device system is up to 85.9% (data from mobile terminal data published by the foreign media Gartner in 2018 in the whole year), the market of china is also about 70% (without data support, data is collected in each large mobile terminal statistical platform), and the application of the mobile terminal product Android platform in the express industry is the largest.
The mobile terminal application product can not push messages, any mobile terminal product has little dependence on message pushing, and the express industry product has stronger requirements on stability and arrival rate of message pushing. Google corporation introduced GCM (Google Cloud Messaging ) to guarantee that applications running on android systems have very high push guarantees, but with Google exiting the china market, the service cannot be used domestically. And because google originally developed an Android system in the early stage, many mobile phone manufacturers in China can install customized systems (such as a millet mobile phone MIUI system, a huawei mobile phone EMUI, a charm mobile phone flash OS and the like) into mobile devices developed by themselves. The support and implementation means of the customized systems for the message pushing capability are different, the pushing arrival rate of Android applications in the industry is not high, most companies only adopt the pushing service of third-party companies (message pushing implemented by long connection with high survival rate), and the public data shows that forty percent of comprehensive arrival rate is the top in the industry.
Firstly, due to the fact that a delivery person cannot timely notify due to the fact that the delivery scheduling is changed, the working efficiency of the delivery person is not consistent with the expectation, the technical trust of the delivery person is reduced, and the product effectiveness is not expected.
Disclosure of Invention
In view of this, embodiments of the present invention provide an Android platform-based client message push optimization method, an Android platform-based client message push optimization device, an electronic device, and a storage medium, which can improve a message push arrival rate.
In a first aspect, an embodiment of the present invention provides an Android platform based client message push optimization method, including:
testing the model to be optimized according to a plurality of preset pushing schemes, and selecting the pushing scheme with the highest message pushing arrival rate;
and sending the selected pushing scheme to the model to be optimized for execution.
With reference to the first aspect, in an embodiment of the first aspect, the preset multiple push schemes include two or more of the following: a system level push, a self-development push long connection mode, a self-development push polling mode, a third party push service, Google push and a combined push scheme; wherein the combined push scheme comprises at least one of: a self-development push polling mode + a long connection mode, a self-development push polling mode + a third-party push, a third-party push A + a third-party push B.
With reference to the first aspect, in another implementation manner of the first aspect, the testing a model to be optimized according to a plurality of preset push schemes, and selecting a push scheme with a highest message push arrival rate includes:
judging whether the machine type to be optimized supports the system-level push service, if so, testing the message push arrival rate when the machine type adopts the system-level push service, if the message push arrival rate exceeds a preset arrival rate threshold value, taking the system-level push as the selected push scheme, and if not, executing the next step;
selecting two push schemes except for a system-level push scheme and a push scheme subjected to an ABtest test from the preset push schemes according to a preset sequence, carrying out the ABtest test on various different models to obtain test results, and issuing the push scheme with a high test result in the two push schemes to the model to be optimized for testing, wherein the various different models comprise the model to be optimized;
and judging whether the message pushing arrival rate of the model to be optimized exceeds a preset arrival rate threshold, if so, taking the pushing scheme with a high test result as the selected pushing scheme, and otherwise, turning to the previous step.
With reference to the first aspect, in a further implementation manner of the first aspect, the issuing a push scheme with a high test result in the two push schemes to the model to be optimized for testing includes:
obtaining test data of the model to be optimized under the pushing scheme with the high test result, wherein the test data comprises a unique mobile equipment mark, an equipment model, a system version, a customized system type, a customized version, electric quantity after arrival, electric quantity before arrival, network delay after arrival and the pushing arrival rate of the equipment;
and performing cluster analysis on the test data to make a decision on the selection of a pushing scheme.
With reference to the first aspect, in a further implementation manner of the first aspect, the performing cluster analysis on the test data to make a decision on selection of a push scheme includes:
dividing the network condition into intervals, wherein the network condition is weak network when the time is more than 5000ms, the network condition is normal when the time is less than 5000ms, and the network condition is no network condition when the time delay data is not available; dividing the electric quantity into low electric quantity, non-low electric quantity and charging, wherein less than twenty percent is low electric quantity, more than twenty percent is normal electric quantity, and distinguishing whether a user starts a power saving mode or not; dividing the memory condition into a normal memory and a low memory provided by a mobile phone system;
if the current push scheme is found to have great influence on the electric quantity and the memory so as to enable the user not to use the mobile phone, the current push scheme is not selected, and the ABTest test and selection of the next push scheme are carried out.
With reference to the first aspect, in a further implementation manner of the first aspect, when the selected push scheme is a combined push scheme, the message includes a unique flag, so that when a client receives messages pushed by different services, repeated messages are filtered out through the unique flag.
In a second aspect, an embodiment of the present invention provides an Android platform based client message pushing optimization device, including:
the test and selection module is used for testing the model to be optimized according to a plurality of preset push schemes and selecting the push scheme with the highest message push arrival rate;
and the issuing module is used for issuing the selected pushing scheme to the model to be optimized for execution.
With reference to the second aspect, in an embodiment of the second aspect, the preset multiple pushing schemes include two or more of the following: a system level push, a self-development push long connection mode, a self-development push polling mode, a third party push service, Google push and a combined push scheme; wherein the combined push scheme comprises at least one of: a self-development push polling mode + a long connection mode, a self-development push polling mode + a third-party push, a third-party push A + a third-party push B.
With reference to the second aspect, in another implementation manner of the second aspect, the testing and selecting module includes:
the first judgment submodule is used for judging whether the machine type to be optimized supports the system-level push service or not, if so, testing the message push arrival rate when the machine type to be optimized adopts the system-level push service, if the message push arrival rate exceeds a preset arrival rate threshold value, taking the system-level push as the selected push scheme, and if not, turning to the test submodule;
the test sub-module is used for selecting two push schemes except for a system-level push scheme and a push scheme subjected to an ABtest test from the preset push schemes according to a preset sequence, carrying out the ABtest test on various different models to obtain test results, and sending the push scheme with a high test result in the two push schemes to the model to be optimized for testing, wherein the various different models comprise the model to be optimized;
and the second judgment submodule is used for judging whether the message push arrival rate of the model to be optimized exceeds a preset arrival rate threshold value, if so, the push scheme with a high test result is taken as the selected push scheme, and otherwise, the test submodule is switched to the test submodule.
With reference to the second aspect, in a further embodiment of the second aspect, the test submodule includes:
the obtaining submodule is used for obtaining test data of the machine type to be optimized under the pushing scheme with the high test result, wherein the test data comprises a unique mark of mobile equipment, an equipment model, a system version, a customized system type, a customized version, electric quantity after arrival, electric quantity before arrival, network delay after arrival and the pushing arrival rate of the equipment;
and the analysis submodule is used for carrying out cluster analysis on the test data so as to make a decision on the selection of the pushing scheme.
With reference to the second aspect, in a further embodiment of the second aspect, the analysis submodule includes:
the division submodule is used for carrying out interval division on the network condition, wherein the weak network is above 5000ms, the normal network condition is below 5000ms, and the network-free condition is realized if no delay data exists; dividing the electric quantity into low electric quantity, non-low electric quantity and charging, wherein less than twenty percent is low electric quantity, more than twenty percent is normal electric quantity, and distinguishing whether a user starts a power saving mode or not; dividing the memory condition into a normal memory and a low memory provided by a mobile phone system;
and the selection submodule is used for not selecting the current push scheme and carrying out the ABtest test and selection of the next push scheme if the fact that the current push scheme has great influence on the electric quantity and the memory so that a user cannot use the mobile phone is found.
With reference to the second aspect, in a further implementation manner of the second aspect, when the selected push scheme is a combined push scheme, the message includes a unique flag, so that when a client receives a message pushed by a different service, a duplicate message is filtered by the unique flag.
In a third aspect, an embodiment of the present invention provides an electronic device, where the electronic device includes: the device comprises a shell, a processor, a memory, a circuit board and a power circuit, wherein the circuit board is arranged in a space enclosed by the shell, and the processor and the memory are arranged on the circuit board; a power supply circuit for supplying power to each circuit or device of the electronic apparatus; the memory is used for storing executable program codes; the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, for performing any of the methods described above.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement any of the methods described above.
According to the message push optimization method and device based on the Android platform client, the electronic equipment and the storage medium, firstly, a model to be optimized is tested according to a plurality of preset push schemes, the push scheme with the highest message push arrival rate is selected, and then the selected push scheme is issued to the model to be optimized for execution. The method and the device can improve the message push arrival rate because the push scheme with the highest message push arrival rate is selected and provided for the model to be optimized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a first embodiment of an Android platform-based client message push optimization method according to the present invention;
fig. 2 is a flowchart of a second embodiment of the method for optimizing message pushing based on an Android platform client according to the present invention;
fig. 3 is a structural diagram of a first embodiment of an Android platform client-based message push optimization device according to the present invention;
fig. 4 is a structural diagram of a second embodiment of the Android platform client-based message push optimization device according to the present invention;
fig. 5 is a block diagram of an embodiment of an electronic device of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides an Android platform based client message push optimization method, including:
step 101: testing the model to be optimized according to a plurality of preset pushing schemes, and selecting the pushing scheme with the highest message pushing arrival rate;
in this step, the preset multiple push schemes include two or more of the following schemes: a system level push, a self-development push long connection mode, a self-development push polling mode, a third party push service, Google push and a combined push scheme; wherein the combined push scheme comprises at least one of: a self-development push polling mode + a long connection mode, a self-development push polling mode + a third-party push, a third-party push A + a third-party push B.
The system-level pushing refers to pushing services of systems such as millet and Huashi, the self-development refers to pushing technologies developed by users, the third-party pushing services are pushing services provided by others on the market, such as pigeon pushing, aurora pushing, friend alliance pushing and the like, and the combined pushing scheme is used for trying to adopt a combined pushing scheme of overlapping (namely simultaneously using) two or more pushing services when the pushing arrival rate of a single pushing mode does not meet the requirement so as to improve the pushing arrival rate.
The larger the number of push schemes preset, the better to provide a wide range of selectivity. For example, the following table of preset push schemes may be used:
step 102: and sending the selected pushing scheme to the model to be optimized for execution.
In this embodiment, a model to be optimized is tested according to a plurality of preset push schemes, a push scheme with the highest message push arrival rate is selected, and then the selected push scheme is issued to the model to be optimized for execution. Since the push scheme with the highest message push arrival rate is selected and provided for the model to be optimized, the message push arrival rate can be improved in the embodiment. The embodiment is suitable for industries with certain requirements on the message push arrival rate, such as the express industry and the like.
In a further embodiment, as shown in fig. 2, the step 101 comprises:
step 1011: judging whether the machine type to be optimized supports the system-level push service, if so, testing the message push arrival rate when the machine type adopts the system-level push service, if the message push arrival rate exceeds a preset arrival rate threshold value, taking the system-level push as the selected push scheme, and if not, executing the next step;
in this step, it is first determined whether the mobile end system supports the system-level push service, and the push arrival rate is tested, and if the mobile end system supports the system-level push service, which is up to 99.9% (usually, the declared arrival rate of the system-level push), the arrival rate of the device is already optimal, and at this time, the system-level push can be directly used as the selected push scheme. The preset arrival rate threshold may be flexibly set according to actual needs, and may be set to a desired value such as 90%, 80%, 50%, or the like.
Step 1012: selecting two push schemes except for a system-level push scheme and a push scheme subjected to an ABtest test from the preset push schemes according to a preset sequence, carrying out the ABtest test on various different models to obtain test results, and issuing the push scheme with a high test result in the two push schemes to the model to be optimized for testing, wherein the various different models comprise the model to be optimized;
in this step, when the mobile end system does not support the system-level push service, triggering a push configuration decision in this step, selecting a push scheme with the highest priority (for example, manually configuring self-development push service polling + long connection combination with the highest priority) from preset push schemes, and performing different machine groups and ABtests in different time periods with a push scheme with the next highest priority (for example, manually configuring third-party push service 'Homing pigeon' with the next highest priority), and acquiring mobile phone test data; and after the test result is obtained, selecting a high result and issuing the high result to the model to be optimized, and testing the result with larger data volume.
ABtest test examples: meanwhile, different push services are used in the same time period of the same type group at the same level of the day, for example, if the push A is used from Monday to Friday of the week, the push B is used for the same user group from Monday to Friday of the next week. And collecting effect data of the users, and determining AB which is used preferentially based on the comprehensive arrival rate.
Step 1013: and judging whether the message pushing arrival rate of the model to be optimized exceeds a preset arrival rate threshold, if so, taking the pushing scheme with a high test result as the selected pushing scheme, and otherwise, turning to the previous step.
In this step, if the obtained result does not meet the expected value (for example, the preset arrival rate threshold is 45%), a scheme with a lower priority is continuously selected from the scheme list for comparison until a push scheme higher than the expected value is selected, and the scheme can be improved to the priority list and a conclusion is reported to a technician. If eventually all solutions are not as desirable, the best performing solution may be selected and the technician notified.
Therefore, by testing a plurality of preset pushing schemes, the pushing scheme with the highest message pushing arrival rate can be selected.
As is well known, the running environment of an Android client mobile phone is very complex. There are network, power, authority configuration, memory condition, CPU pressure, etc. influencing factors. The decision of which data should be wanted and which data should not be wanted is crucial. Through continuous attempts, it is found that the main factors influencing the push arrival rate are (1) the survival of the self-developed push service and (2) whether the system-level push service is supported. Factors influencing (1) include electric quantity (a low-electric-quantity system automatically closes background service), memory (a low-memory system automatically relates to background service), network (a network can not reach to cause message can not reach), and user authority (whether service is agreed to run in background or not).
Therefore, to increase the accuracy of the push solution decision, the step 1012 may include:
step 10121: obtaining test data of the model to be optimized under the pushing scheme with high test result, wherein the test data comprises:
1) unique mark of mobile equipment
2) Model of the device
3) System version
4) Customized system type, customized version
5) Electric quantity after arrival, electric quantity before arrival (estimated)
6) Network delay before arrival and network delay after arrival
7) Push arrival rate of the device.
Note 1: the method for estimating the electric quantity comprises the following steps that a client acquires the charging state of a mobile phone, and the electric quantity at the moment is judged according to the time dimension, for example: if the ratio of 10: 00, 90% of electricity, 10: 45 not reached, 11: 15, the electric quantity is 75%, so that the electric quantity is estimated to be between 75-90% when the electric quantity does not reach, and if the electric quantity is charged in the meantime, the electric quantity percentage range is shortened.
Note 2: the index data which does not arrive can be collected and stored in the mobile phone, and the index data can be uploaded when the network condition is excellent.
Step 10122: and performing cluster analysis on the test data to make a decision on the selection of a pushing scheme.
In this step, the test data is comprehensively processed to obtain the overall arrival rate of the device and the type of device and various types of information of the type of device, so as to facilitate analysis, and specifically, cluster analysis (i.e., sorting by type, for example, according to the model and the system version) may be performed to make a decision on the push scheme selection of the model to be optimized.
The specific processing scheme of the test data clustering analysis is as follows:
the test data is stored with a mobile device unique identifier, contains all the fields, and is added with a statistical time period (time) field.
Dividing the network condition into network delay of non-arrival time and arrival time, and dividing intervals, wherein the network condition is weak for more than 5000ms, the network condition is normal for less than 5000ms, and the network condition is no-network condition if no-delay data exists;
the power is divided into low power, non-low power and charging when the power does not arrive and when the power arrives, wherein the power is low when the power is less than twenty percent and normal when the power is more than twenty percent, and whether a user starts a power saving mode or not is distinguished.
The memory condition is divided into normal memory and low memory provided by the mobile phone system.
All software installed in the handset is stored.
The push arrival rate of the handset.
Push scheme currently in use for the handset (systematic, self-research, combinational, GCM, etc.)
For example: all models are classified into systems customized by various manufacturers according to model dimensions (such as millet, Huawei and charm). And (4) carrying out independent processing and decision making on different models, and if the current push scheme is found to have great influence on the electric quantity and the memory so that a user cannot use the mobile phone, not selecting the current push scheme, and carrying out ABtest test and selection on the next push scheme.
And when the rest data are not ideal for final decision, technicians intervene manually.
In the above embodiment, preferably, when the extracted push scheme is the combined push scheme, the message includes a unique flag (the flag ensures uniqueness of the message), so that when the client receives messages pushed by different services, repeated messages are filtered out through the unique flag. Therefore, the user can be ensured to receive the message only once, and the influence on the user experience caused by the repeated reception of the same message is avoided.
Specifically, the client may store a unique flag of the notified message, record whether the user is processing the message effectively, and display the message that arrives first according to time sequence when receiving messages of the same content pushed by different services. The rest of the message is discarded. If the arrival time difference is large, whether the displayed message is displayed or not is determined according to whether the user is effective to process, and if the user does not read the message, the repeated message is not continuously displayed.
In conclusion, in practical application, the technical scheme can effectively solve the problem of continuously optimizing and preferentially pushing optimization, and can select the optimized scheme to operate in multiple comparisons in response to the appearance of new models. And under the condition that the samples and the schemes are accumulated fully, a large amount of manpower resources of technicians can be saved.
But also has the beneficial effects on the industry:
1. the performance of various push services of a large number of applications is obtained, and technical conclusion and data are output to the industry beneficially.
2. Greatly improving the comprehensive arrival rate of the product pushing service so as to improve the working efficiency of product users.
3. The use characteristics of the application push service in the express delivery industry are obtained so as to research a better product scheme.
Fig. 3 is a schematic structural diagram of a first embodiment of an Android platform client-based message push optimization device according to the present invention, and as shown in fig. 3, the device of this embodiment may include:
the test and selection module 31 is configured to test a model to be optimized according to a plurality of preset push schemes, and select a push scheme with the highest message push arrival rate;
and the issuing module 32 is configured to issue the selected pushing scheme to the model to be optimized for execution.
The apparatus of this embodiment may be used to implement the technical solution of the method embodiment shown in fig. 1, and the implementation principle and the technical effect are similar, which are not described herein again.
Preferably, the preset multiple pushing schemes include two or more of the following schemes: a system level push, a self-development push long connection mode, a self-development push polling mode, a third party push service, Google push and a combined push scheme; wherein the combined push scheme comprises at least one of: a self-development push polling mode + a long connection mode, a self-development push polling mode + a third-party push, a third-party push A + a third-party push B.
Fig. 4 is an embodiment improved on the embodiment of fig. 3, and as shown in fig. 4, the testing and selecting module 31 includes:
the first determining sub-module 311 is configured to determine whether the model to be optimized supports the system-level push service, if so, test a message push arrival rate when the model adopts the system-level push service, if the message push arrival rate exceeds a preset arrival rate threshold, use the system-level push as the selected push scheme, and if not, transfer to the testing sub-module 312;
the test sub-module 312 is configured to select two push schemes, other than the system-level push scheme and the push scheme that has been subjected to the ABTest test, from the preset multiple push schemes according to a preset sequence, perform the ABTest on multiple different machine types to obtain a test result, and send the push scheme with a higher test result of the two push schemes to the machine type to be optimized for testing, where the multiple different machine types include the machine type to be optimized;
and the second judging submodule 313 is configured to judge whether the message push arrival rate of the model to be optimized exceeds a preset arrival rate threshold, if so, take the push scheme with the high test result as the selected push scheme, and otherwise, turn to the testing submodule 312.
The apparatus of this embodiment may be used to implement the technical solution of the method embodiment shown in fig. 2, and the implementation principle and the technical effect are similar, which are not described herein again.
Preferably, the test sub-module 312 includes:
the obtaining submodule is used for obtaining test data of the machine type to be optimized under the pushing scheme with the high test result, wherein the test data comprises a unique mark of mobile equipment, an equipment model, a system version, a customized system type, a customized version, electric quantity after arrival, electric quantity before arrival, network delay after arrival and the pushing arrival rate of the equipment;
and the analysis submodule is used for carrying out cluster analysis on the test data so as to make a decision on the selection of the pushing scheme.
Preferably, the analysis submodule includes:
the division submodule is used for carrying out interval division on the network condition, wherein the weak network is above 5000ms, the normal network condition is below 5000ms, and the network-free condition is realized if no delay data exists; dividing the electric quantity into low electric quantity, non-low electric quantity and charging, wherein less than twenty percent is low electric quantity, more than twenty percent is normal electric quantity, and distinguishing whether a user starts a power saving mode or not; dividing the memory condition into a normal memory and a low memory provided by a mobile phone system;
and the selection submodule is used for not selecting the current push scheme and carrying out the ABtest test and selection of the next push scheme if the fact that the current push scheme has great influence on the electric quantity and the memory so that a user cannot use the mobile phone is found.
Preferably, when the selected push scheme is the combined push scheme, the message includes a unique flag, so that when the client receives messages pushed by different services, repeated messages are filtered through the unique flag. Therefore, the user can be ensured to receive the message only once, and the influence on the user experience caused by the repeated reception of the same message is avoided.
An embodiment of the present invention further provides an electronic device, as shown in fig. 5, which can implement the process of the method embodiment shown in fig. 1-2 of the present invention, where the electronic device includes: the device comprises a shell 41, a processor 42, a memory 43, a circuit board 44 and a power circuit 45, wherein the circuit board 44 is arranged inside a space enclosed by the shell 41, and the processor 42 and the memory 43 are arranged on the circuit board 44; a power supply circuit 45 for supplying power to each circuit or device of the electronic apparatus; the memory 43 is used for storing executable program code; the processor 42 executes a program corresponding to the executable program code by reading the executable program code stored in the memory 43, for performing the method described in any of the method embodiments described above.
For the specific execution process of the above steps by the processor 42 and the steps further executed by the processor 42 by running the executable program code, reference may be made to the description of the method embodiment shown in fig. 1-2 of the present invention, which is not described herein again.
The electronic device exists in a variety of forms, including but not limited to:
(1) a mobile communication device: such devices are characterized by mobile communications capabilities and are primarily targeted at providing voice, data communications. Such terminals include: smart phones (e.g., iphones), multimedia phones, functional phones, and low-end phones, among others.
(2) Ultra mobile personal computer device: the equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such terminals include: PDA, MID, and UMPC devices, etc., such as ipads.
(3) A portable entertainment device: such devices can display and play multimedia content. This type of device comprises: audio, video players (e.g., ipods), handheld game consoles, electronic books, and smart toys and portable car navigation devices.
(4) A server: the device for providing the computing service comprises a processor, a hard disk, a memory, a system bus and the like, and the server is similar to a general computer architecture, but has higher requirements on processing capacity, stability, reliability, safety, expandability, manageability and the like because of the need of providing high-reliability service.
(5) And other electronic equipment with data interaction function.
The embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements the method steps described in any of the above method embodiments.
Embodiments of the invention also provide an application program, which is executed to implement the method provided by any one of the method embodiments of the invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. The term "comprising", without further limitation, means that the element so defined is not excluded from the group consisting of additional identical elements in the process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment. For convenience of description, the above devices are described separately in terms of functional division into various units/modules. Of course, the functionality of the units/modules may be implemented in one or more software and/or hardware implementations of the invention.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A client message pushing optimization method based on an Android platform is characterized by comprising the following steps:
testing the model to be optimized according to a plurality of preset pushing schemes, and selecting the pushing scheme with the highest message pushing arrival rate;
sending the selected pushing scheme to the model to be optimized for execution;
wherein the preset multiple pushing schemes comprise two or more of the following schemes: a system level push, a self-development push long connection mode, a self-development push polling mode, a third party push service, Google push and a combined push scheme; wherein the combined push scheme comprises at least one of: a self-development push polling mode + a long connection mode, a self-development push polling mode + third-party push, a third-party push A + a third-party push B;
the method comprises the following steps of testing a model to be optimized according to a plurality of preset pushing schemes, and selecting the pushing scheme with the highest message pushing arrival rate, wherein the pushing scheme comprises the following steps:
judging whether the machine type to be optimized supports the system-level push service, if so, testing the message push arrival rate when the machine type adopts the system-level push service, if the message push arrival rate exceeds a preset arrival rate threshold value, taking the system-level push as the selected push scheme, and if not, executing the next step;
selecting two push schemes except for a system-level push scheme and a push scheme subjected to an ABtest test from the preset push schemes according to a preset sequence, carrying out the ABtest test on various different models to obtain test results, and issuing the push scheme with a high test result in the two push schemes to the model to be optimized for testing, wherein the various different models comprise the model to be optimized;
judging whether the message pushing arrival rate of the model to be optimized exceeds a preset arrival rate threshold, if so, taking the pushing scheme with a high test result as the selected pushing scheme, and otherwise, turning to the previous step;
wherein, the issuing the push scheme with the high test result in the two push schemes to the model to be optimized for testing comprises:
obtaining test data of the model to be optimized under the pushing scheme with the high test result, wherein the test data comprises a unique mobile equipment mark, an equipment model, a system version, a customized system type, a customized version, electric quantity after arrival, electric quantity before arrival, network delay after arrival and the pushing arrival rate of the equipment;
performing cluster analysis on the test data to make a decision on the selection of a pushing scheme;
when the selected push scheme is the combined push scheme, the message contains a unique mark, so that when the client receives messages pushed by different services, repeated messages are filtered through the unique mark.
2. The Android platform client message push optimization method of claim 1, wherein the performing cluster analysis on the test data to make a decision on selection of a push scheme comprises:
dividing the network condition into intervals, wherein the network condition is weak network when the time is more than 5000ms, the network condition is normal when the time is less than 5000ms, and the network condition is no network condition when the time delay data is not available; dividing the electric quantity into low electric quantity, non-low electric quantity and charging, wherein less than twenty percent is low electric quantity, more than twenty percent is normal electric quantity, and distinguishing whether a user starts a power saving mode or not; dividing the memory condition into a normal memory and a low memory provided by a mobile phone system;
if the current push scheme is found to have great influence on the electric quantity and the memory so as to enable the user not to use the mobile phone, the current push scheme is not selected, and the ABTest test and selection of the next push scheme are carried out.
3. The utility model provides a message propelling movement optimizing device based on Android platform customer end which characterized in that includes:
the test and selection module is used for testing the model to be optimized according to a plurality of preset push schemes and selecting the push scheme with the highest message push arrival rate;
the issuing module is used for issuing the selected pushing scheme to the model to be optimized for execution;
wherein the preset multiple pushing schemes comprise two or more of the following schemes: a system level push, a self-development push long connection mode, a self-development push polling mode, a third party push service, Google push and a combined push scheme; wherein the combined push scheme comprises at least one of: a self-development push polling mode + a long connection mode, a self-development push polling mode + third-party push, a third-party push A + a third-party push B;
wherein, the test and selection module comprises:
the first judgment submodule is used for judging whether the machine type to be optimized supports the system-level push service or not, if so, testing the message push arrival rate when the machine type to be optimized adopts the system-level push service, if the message push arrival rate exceeds a preset arrival rate threshold value, taking the system-level push as the selected push scheme, and if not, turning to the test submodule;
the test sub-module is used for selecting two push schemes except for a system-level push scheme and a push scheme subjected to an ABtest test from the preset push schemes according to a preset sequence, carrying out the ABtest test on various different models to obtain test results, and sending the push scheme with a high test result in the two push schemes to the model to be optimized for testing, wherein the various different models comprise the model to be optimized;
the second judgment submodule is used for judging whether the message pushing arrival rate of the model to be optimized exceeds a preset arrival rate threshold value, if so, the pushing scheme with a high test result is taken as the selected pushing scheme, and otherwise, the testing submodule is switched to;
wherein the test submodule comprises:
the obtaining submodule is used for obtaining test data of the machine type to be optimized under the pushing scheme with the high test result, wherein the test data comprises a unique mark of mobile equipment, an equipment model, a system version, a customized system type, a customized version, electric quantity after arrival, electric quantity before arrival, network delay after arrival and the pushing arrival rate of the equipment;
the analysis submodule is used for carrying out cluster analysis on the test data so as to make a decision on the selection of a pushing scheme;
when the selected push scheme is the combined push scheme, the message contains a unique mark, so that when the client receives messages pushed by different services, repeated messages are filtered through the unique mark.
4. The Android platform client-based message push optimization device of claim 3, wherein the analysis submodule comprises:
the division submodule is used for carrying out interval division on the network condition, wherein the weak network is above 5000ms, the normal network condition is below 5000ms, and the network-free condition is realized if no delay data exists; dividing the electric quantity into low electric quantity, non-low electric quantity and charging, wherein less than twenty percent is low electric quantity, more than twenty percent is normal electric quantity, and distinguishing whether a user starts a power saving mode or not; dividing the memory condition into a normal memory and a low memory provided by a mobile phone system;
and the selection submodule is used for not selecting the current push scheme and carrying out the ABtest test and selection of the next push scheme if the fact that the current push scheme has great influence on the electric quantity and the memory so that a user cannot use the mobile phone is found.
5. An electronic device, characterized in that the electronic device comprises: the device comprises a shell, a processor, a memory, a circuit board and a power circuit, wherein the circuit board is arranged in a space enclosed by the shell, and the processor and the memory are arranged on the circuit board; a power supply circuit for supplying power to each circuit or device of the electronic apparatus; the memory is used for storing executable program codes; the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory for performing the method of any of the preceding claims 1-2.
6. A computer readable storage medium, characterized in that the computer readable storage medium stores one or more programs which are executable by one or more processors to implement the method of any of the preceding claims 1-2.
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