Accelerated profit obtaining system and method
阅读说明：本技术 加速收益获取系统及方法 (Accelerated profit obtaining system and method ) 是由 覃艳君 潘坤 尹海波 于 2019-10-14 设计创作，主要内容包括：本发明公开了一种加速收益获取系统及方法,用以更加直观地体现加速系统的实际加速效果,为加速服务的进一步优化提供着积极的数据支持。所述系统包括：第一获取模块,获取预设应用的第一数据传输特征；第二获取模块,获取所述预设应用使用加速器之后的第二数据传输特征；确定模块,根据所述第一数据传输特征和所述第二数据传输特征,确定所述加速器对所述预设应用产生的加速收益。(The invention discloses an acceleration gain acquisition system and method, which are used for more intuitively reflecting the actual acceleration effect of an acceleration system and providing positive data support for further optimization of acceleration service. The system comprises: the first acquisition module is used for acquiring a first data transmission characteristic of a preset application; the second acquisition module is used for acquiring second data transmission characteristics of the preset application after the accelerator is used; and the determining module is used for determining the acceleration benefit of the accelerator on the preset application according to the first data transmission characteristic and the second data transmission characteristic.)
1. An accelerated revenue capture system, comprising:
the first acquisition module is used for acquiring a first data transmission characteristic of a preset application;
the second acquisition module is used for acquiring second data transmission characteristics of the preset application after the accelerator is used;
and the determining module is used for determining the acceleration benefit of the accelerator on the preset application according to the first data transmission characteristic and the second data transmission characteristic.
2. The system of claim 1, wherein the first acquisition module comprises:
the first obtaining submodule is used for obtaining a first data transmission characteristic which is initial on the basis that the accelerator is not used by the preset application; or
And the second acquisition submodule is used for acquiring a first universal data transmission characteristic on the basis of not using the accelerator, wherein the first universal data transmission characteristic is predicted by the initial first data transmission characteristic.
3. The system of claim 2,
the initial first data transmission characteristics comprise an initial average delay time, an initial delay standard deviation and an initial packet drop rate;
the general first data transmission characteristics comprise a general average delay time, a general standard deviation of delay and a general packet drop rate;
the second data transmission characteristics comprise an accelerated average delay time, an accelerated delay standard deviation and an accelerated packet drop rate.
4. The system of claim 3,
the second acquisition sub-module includes:
the first calculating unit is used for calculating the general packet dropping rate based on the accelerated packet dropping rate;
a second calculating unit, configured to calculate the general average delay time based on the initial average delay time, the initial packet drop rate, and the general packet drop rate;
a third calculating unit, configured to calculate the universal delay standard deviation based on the initial delay standard deviation, the initial packet drop rate, and the universal packet drop rate.
5. The system of claim 4,
the first calculating unit calculates the initial packet dropping rate through a first preset formula;
wherein esLR represents the initial packet drop rate, pLR represents the packet drop rate after acceleration, isWifilAccel ═ 1 represents that WIFI and mobile data networks are simultaneously used when the accelerator is accelerated, and isWifilAccel ═ 0 represents that WIFI and mobile data networks are not simultaneously used when the accelerator is accelerated;
esAvg represents the generalized average delay time, esSd represents the generalized delay standard deviation,
the determination module is further configured to predict an acceleration gain generated by the accelerator for the preset application according to a third preset formula,
wherein PCT represents the acceleration gain, w is a weight value, pAvg represents the average delay after the acceleration, pSd represents the standard deviation of the delay after the acceleration, and k is an empirical coefficient.
6. The system of claim 3,
the determining module comprises:
and the third obtaining submodule is used for obtaining the acceleration benefit of the accelerator on the preset application according to the initial delay standard deviation, the accelerated delay standard deviation, the initial average delay time, the accelerated average delay time and the accelerated packet drop rate.
7. The system of any one of claims 1 to 6, further comprising:
the scoring module is used for scoring the accelerators according to the acceleration benefits of the accelerators to the preset application and the second data transmission characteristics of the preset application after the accelerators are used when the accelerators exist;
a first determining module, configured to determine recommended features of the accelerators according to the scoring data of the accelerators, where at least one of the recommended features includes: recommending priority, recommending mode and recommending time;
the recommendation module is used for recommending the user according to the recommendation characteristics of the accelerators;
and the updating module is used for updating the recommendation characteristics of the accelerators according to the use information of the accelerators by the user after the accelerators are recommended for the user.
8. The system of any one of claims 1 to 6, further comprising:
a second determining module, configured to, when there are multiple accelerators, determine an acceleration level of each accelerator according to an acceleration benefit, generated by each accelerator of the multiple accelerators, to the preset application and a second data transmission characteristic after the preset application uses the accelerator;
the judging module is used for judging whether the acceleration level of each accelerator reaches a preset acceleration level or not;
the feedback module is used for feeding back the acceleration level of each accelerator to the operation center of each accelerator when the preset acceleration level is not reached so that the operation center of each accelerator can optimize each service link of each accelerator;
and the execution module is used for circularly executing the steps until the acceleration level of each accelerator reaches the preset acceleration level.
9. An accelerated revenue capture method, comprising:
acquiring a first data transmission characteristic of a preset application;
acquiring a second data transmission characteristic after the accelerator is used by the preset application;
and determining the acceleration benefit of the accelerator on the preset application according to the first data transmission characteristic and the second data transmission characteristic.
Technical Field
The invention relates to the technical field of games, in particular to an accelerated income acquisition system and method.
Background
At present, various hand-trip accelerators such as rapid-trip hand-trip accelerators provide excellent acceleration services for more and more hand-trip players, and meanwhile, relevant statistical analysis also provides positive data support for further optimization of the acceleration services. In the background, a relatively accurate numerical value is needed to more intuitively embody the actual acceleration effect of the acceleration system, namely, the comprehensive acceleration promotion yield (PCT). Therefore, how to calculate the comprehensive acceleration promotion yield more intelligently and accurately becomes an urgent problem to be solved.
Disclosure of Invention
The invention provides an acceleration gain acquisition system and method, which are used for intelligently and accurately predicting the acceleration gain generated by an accelerator on a preset application based on a first data transmission characteristic of the preset application and a second data transmission characteristic after the accelerator is used by acquiring the first data transmission characteristic and the second data transmission characteristic, so that the actual acceleration effect of an acceleration system is more intuitively reflected, and positive data support is provided for further optimization of acceleration service.
The invention provides an accelerated gain acquisition system, comprising:
the first acquisition module is used for acquiring a first data transmission characteristic of a preset application;
the second acquisition module is used for acquiring second data transmission characteristics of the preset application after the accelerator is used;
and the determining module is used for determining the acceleration benefit of the accelerator on the preset application according to the first data transmission characteristic and the second data transmission characteristic.
In one embodiment, the first obtaining module comprises:
the first obtaining submodule is used for obtaining first data transmission characteristics of the preset application on the basis that the accelerator is not used; or
And the second acquisition submodule is used for acquiring a first universal data transmission characteristic on the basis of not using the accelerator, wherein the first universal data transmission characteristic is predicted by the initial first data transmission characteristic.
In one embodiment, the initial first data transmission characteristic comprises an initial average delay time, an initial standard deviation of delay, and an initial packet drop rate;
the general first data transmission characteristics comprise a general average delay time, a general standard deviation of delay and a general packet drop rate;
the second data transmission characteristics comprise an accelerated average delay time, an accelerated delay standard deviation and an accelerated packet drop rate.
In one embodiment, the second obtaining sub-module includes:
the first calculating unit is used for calculating the general packet dropping rate based on the accelerated packet dropping rate;
a second calculating unit, configured to calculate the general average delay time based on the initial average delay time, the initial packet drop rate, and the general packet drop rate;
a third calculating unit, configured to calculate the universal delay standard deviation based on the initial delay standard deviation, the initial packet drop rate, and the universal packet drop rate.
In one embodiment, the first calculating unit calculates the initial packet drop rate according to a first preset formula;
wherein esLR represents the initial packet drop rate, pLR represents the packet drop rate after acceleration, isWifilAccel ═ 1 represents that WIFI and mobile data networks are simultaneously used when the accelerator is accelerated, and isWifilAccel ═ 0 represents that WIFI and mobile data networks are not simultaneously used when the accelerator is accelerated;
esAvg represents the generalized average delay time, esSd represents the generalized delay standard deviation,
the determination module is further configured to predict an acceleration gain generated by the accelerator for the preset application according to a third preset formula,
wherein PCT represents the acceleration gain, w is a weight value, pAvg represents the average delay after the acceleration, pSd represents the standard deviation of the delay after the acceleration, and k is an empirical coefficient.
In one embodiment, the determining module comprises:
and the third obtaining submodule is used for obtaining the acceleration gain of the accelerator on the preset application according to the initial delay standard deviation, the accelerated delay standard deviation, the initial average delay time, the accelerated average delay time and the accelerated packet drop rate.
In one embodiment, the system further comprises:
the scoring module is used for scoring the accelerators according to the acceleration benefits of the accelerators to the preset application and second data transmission characteristics of the preset application after the accelerators are used when the accelerators exist;
a first determining module, configured to determine recommended features of the accelerators according to the scoring data of the accelerators, where at least one of the recommended features includes: recommending priority, recommending mode and recommending time;
the recommendation module is used for recommending the user according to the recommendation characteristics of the accelerators;
and the updating module is used for updating the recommended features of the accelerators according to the use information of the accelerators by the user after the accelerators are recommended for the user.
In one embodiment, the system further comprises:
a second determining module, configured to, when there are multiple accelerators, determine an acceleration level of each accelerator according to an acceleration benefit, generated by each accelerator of the multiple accelerators, to the preset application and a second data transmission characteristic after the preset application uses the accelerator;
the judging module is used for judging whether the acceleration level of each accelerator reaches a preset acceleration level or not;
the feedback module is used for feeding the acceleration level of each accelerator back to the operation center of each accelerator when the preset acceleration level is not reached so that the operation center of each accelerator can optimize each service link of each accelerator;
and the execution module is used for circularly executing the steps until the acceleration level of each accelerator reaches the preset acceleration level.
Another aspect of the present invention further provides an accelerated profit obtaining method, including:
acquiring a first data transmission characteristic of a preset application;
acquiring a second data transmission characteristic after the accelerator is used by the preset application;
and acquiring the acceleration benefit of the accelerator on the preset application according to the first data transmission characteristic and the second data transmission characteristic.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a block diagram illustrating an accelerated revenue acquisition system in accordance with an exemplary embodiment.
FIG. 2 is a probability distribution diagram of the initial delayed mean according to an embodiment of the present invention.
Fig. 3 is a probability distribution diagram of an initial packet drop rate according to an embodiment of the present invention.
FIG. 4 is a probability distribution diagram of an initial delay standard deviation according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Fig. 1 is a system for accelerating revenue acquisition according to an embodiment of the present invention, as shown in fig. 1, the system includes:
a first obtaining module 101, configured to obtain a first data transmission characteristic of a preset application;
a second obtaining module 102, configured to obtain a second data transmission characteristic after the accelerator is used by the preset application;
a determining module 103, configured to determine, according to the first data transmission characteristic and the second data transmission characteristic, an acceleration benefit (PCT in the following table) generated by the accelerator for the preset application.
By acquiring the first data transmission characteristic of the preset application and the second data transmission characteristic after the accelerator is used, the acceleration benefit of the accelerator on the preset application can be intelligently and accurately predicted based on the two items of information, so that the actual acceleration effect of an acceleration system is more intuitively reflected, the effect of the accelerator is changed into visual data, and positive data support is provided for further optimization of acceleration service.
This includes, but is not limited to, predicting the acceleration benefits generated by the accelerator for the predetermined application, and also predicting the acceleration benefits generated by the accelerator for all other applications that use the accelerator.
In one embodiment, the first obtaining module comprises:
a first obtaining submodule, configured to obtain an initial first data transmission characteristic of the preset application (such as a certain game application) without using the accelerator, where the accelerator refers to various game accelerators; or
And the second acquisition submodule is used for acquiring a first universal data transmission characteristic on the basis of not using the accelerator, wherein the first universal data transmission characteristic is predicted from the initial first data transmission characteristic and is used for representing the data transmission characteristics of all applications (including preset applications) which can use the accelerator when the accelerator is not used.
In one embodiment, the initial first data transmission characteristic comprises an initial average delay time, an initial standard deviation of delay, and an initial packet drop rate;
the general first data transmission characteristics comprise a general average delay time, a general standard deviation of delay and a general packet drop rate;
the second data transmission characteristics comprise an accelerated average delay time, an accelerated delay standard deviation and an accelerated packet drop rate.
The initial first data transmission characteristic is a real data transmission characteristic when the accelerator is not used by the preset application, and the transmission characteristic is limited to the preset application and cannot be used for directly calculating the acceleration benefit when the accelerator is used by other applications, so that the data transmission characteristics of all the applications without the accelerator can be predicted by using the real data transmission characteristic when the accelerator is not used by the preset application (namely, the data transmission characteristics when the accelerator is not used by all the applications are predicted), and thus the acceleration benefit when the accelerator is used by all the applications can be predicted by using the first data transmission characteristic, but only the acceleration benefit when the accelerator is used by the preset application can be predicted.
The initial standard deviation of the delay is the standard deviation of the initial delay time; the standard deviation of the delay after acceleration is the standard deviation of the delay time after the accelerator is used;
the average delay time after acceleration is the average of the delay time after the accelerator is used;
the accelerated packet drop rate is the packet drop rate after the accelerator is used. And the packet drop rate is the network packet drop rate.
In one embodiment, the second obtaining sub-module includes:
the first calculating unit is used for calculating the general packet dropping rate based on the accelerated packet dropping rate;
a second calculating unit, configured to calculate the general average delay time based on the initial average delay time, the initial packet drop rate, and the general packet drop rate;
a third calculating unit, configured to calculate the universal delay standard deviation based on the initial delay standard deviation, the initial packet drop rate, and the universal packet drop rate.
Since the initial first data transmission characteristic has a certain limitation, the general packet dropping rate can be calculated by using the accelerated packet dropping rate generated by the accelerator, and then the general average delay time and the general delay standard deviation are respectively predicted by using the initial average delay time, the initial packet dropping rate, the general packet dropping rate and the initial delay standard deviation, so as to predict the acceleration gain which can be brought by all the applications using the accelerator, including the preset application.
In one embodiment, the first calculating unit calculates the initial packet drop rate according to a first preset formula;
wherein esLR represents the initial packet drop rate, pLR represents the packet drop rate after acceleration, isWifilAccel ═ 1 represents that WIFI and mobile data networks are simultaneously used when the accelerator is accelerated, and isWifilAccel ═ 0 represents that WIFI and mobile data networks are not simultaneously used when the accelerator is accelerated;
esAvg represents the generalized average delay time, esSd represents the generalized delay standard deviation,expected value representing the initial average delay time
the determination module is further configured to predict an acceleration gain generated by the accelerator for the preset application according to a third preset formula,
wherein PCT represents the acceleration gain, w is a weight value, pAvg represents the average delay after the acceleration, pSd represents the standard deviation of the delay after the acceleration, and k is an empirical coefficient.
Through the first preset formula, the second preset formula and the third preset formula, the accelerator can accurately predict the acceleration benefits brought by all applications using the accelerator including the preset application.
In one embodiment, the determining module comprises:
and the third obtaining submodule is used for obtaining the acceleration gain of the accelerator on the preset application according to the initial delay standard deviation, the accelerated delay standard deviation, the initial average delay time, the accelerated average delay time and the accelerated packet drop rate.
By acquiring the initial delay standard deviation and the initial average delay time of the preset application, the accelerated delay standard deviation generated after the accelerator is used, the accelerated average delay time and the accelerated packet dropping rate, the acceleration benefit of the accelerator on the preset application can be intelligently and accurately predicted based on the information, so that the actual acceleration effect of an acceleration system is more intuitively reflected, and positive data support is provided for further optimization of acceleration service.
In one embodiment, the system further comprises:
the scoring module is used for scoring the accelerators according to the acceleration benefits of the accelerators to the preset application and second data transmission characteristics of the preset application after the accelerators are used when the accelerators exist;
a first determining module, configured to determine recommended features of the accelerators according to the scoring data of the accelerators, where at least one of the recommended features includes: recommending priority, recommending mode and recommending time;
the higher the scoring data is, the better the acceleration performance of the accelerator is, so that the higher the scoring data is, the higher the recommendation priority is, the closer the recommendation time is to the time of the user playing the preset application, and the more direct the recommendation mode is, the easier the user finds.
The recommendation mode can be different modes such as short message, WeChat, QQ, microblog, website and the like.
The recommendation module is used for recommending the user according to the recommendation characteristics of the accelerators;
and the updating module is used for updating the recommendation characteristics of the accelerators according to the use information of the user on the accelerators after recommending the accelerators for the user, wherein the use information comprises whether the user uses the accelerator, the use duration and the use times of the accelerator, whether the accelerator is recommended to other users, whether opinions are made for the accelerator and the like.
According to the acceleration benefits generated by each accelerator to the preset application and the second data transmission characteristics of the preset application after each accelerator is used by the preset application, each accelerator can be accurately scored, then the recommendation characteristics of each accelerator are determined according to the scoring data of each accelerator, specifically, different scoring data correspond to different recommendation priorities, recommendation modes and recommendation time so as to intelligently recommend to a user according to the recommendation characteristics of each accelerator, and then the recommendation characteristics of each accelerator are continuously updated in a circulating mode according to the use information of the user to each accelerator, so that each accelerator is ensured to be more accurate, and not only the acceleration condition of each accelerator is met, but also the use condition of the user is met.
In one embodiment, the system further comprises:
a second determining module, configured to, when there are multiple accelerators, determine an acceleration level of each accelerator according to an acceleration benefit, generated by each accelerator of the multiple accelerators, to the preset application and a second data transmission characteristic after the preset application uses the accelerator;
the judging module is used for judging whether the acceleration level of each accelerator reaches a preset acceleration level or not;
the feedback module is used for feeding the acceleration level of each accelerator back to the operation center of each accelerator when the preset acceleration level is not reached so that the operation center of each accelerator can optimize each service link of each accelerator;
and the execution module is used for circularly executing the steps until the acceleration level of each accelerator reaches the preset acceleration level.
When a plurality of accelerators exist, the acceleration level of each accelerator can be accurately determined according to the acceleration yield generated by each accelerator in the plurality of accelerators to the preset application and the use of the preset application by the second data transmission characteristics behind each accelerator, then whether the acceleration level of each accelerator reaches the preset acceleration level is judged, and when the acceleration level is not reached, the acceleration level of each accelerator is fed back to the operation center of each accelerator so that the operation center of each accelerator optimizes each service link of each accelerator, thereby constantly optimizing each accelerator, constantly improving the acceleration performance of each accelerator until the acceleration level of each accelerator reaches the preset acceleration level, and further ensuring that the performance of the accelerator is better optimized.
On the other hand, the invention also provides an accelerated gain acquisition method, which comprises the following steps:
acquiring a first data transmission characteristic of a preset application;
acquiring a second data transmission characteristic after the accelerator is used by the preset application;
and determining the acceleration benefit of the accelerator on the preset application according to the first data transmission characteristic and the second data transmission characteristic.
The technical solution of the present invention will be further explained in detail below:
in the data statistics of the fast-play hand-play accelerator, the game acceleration quality mainly depends on three items of data of average delay, packet drop rate and standard deviation in the game process. Therefore, the value of the comprehensive promotion Profit (PCT) is calculated by three values of average delay, packet dropping rate and standard deviation before and after the acceleration of the game.
The following are the nomenclature and abbreviations for several concepts as shown in table 2:
TABLE 2
The average value, the standard deviation and the packet drop rate of the delay are collectively referred to as quality statistics items.
The comprehensive accelerated promotion income measurement and calculation system has the following structure:
third, calculating method for comprehensive promoted Profit (PCT)
1 calculation scheme for comprehensive profit increase (PCT)
PCT values were measured from three estimates of mean delay, standard deviation, and packet drop rate before proxy (i.e., initial in table 2) and after proxy (i.e., accelerated in table 2).
2 revenue estimation based on big data analysis
When there is no comparison data before acceleration, it is necessary to combine statistical data (here, statistical estimation is performed by using sampling data of a game application with a certain depth of cooperation) and estimate a set of quality statistical data under a zero-benefit condition by using an algorithm, including:
the packet loss rate is as follows: esLR; mean delay: esAvg; standard deviation: esSd;
and after the estimation value is obtained, calculating the comprehensive promotion income:
w is a weighted value of the delay mean value in two evaluation terms of the mean value and the standard deviation, according to statistical experience, w is generally equal to 0.5, k is an empirical coefficient, and the w is obtained by actual data comparison statistics, wherein k is equal to 0.8.
The esAvg and esSd are calculated by an algorithm according to esLR, the estimated value esLR of the zero-income state packet dropping rate is obtained by pLR in combination with the sample statistical conclusion, and the value of esLR is not less than pLR, so in the above formula, esLR does not directly participate in the calculation of the comprehensive improvement income PCT.
According to the statistical data, the probability distribution of the delay mean, the standard deviation and the packet dropping rate conforms to normal population or log-normal distribution.
When pLR is 0, both esAvg and esSd can take the statistically derived most probable event, pLR > 0, according to an algorithm to derive esAvg and esSd (related to network quality, esLR).
TABLE 3 data meanings and values
The zero-yield packet drop rate estimation value esLR is obtained by known acceleration packet drop rate pLR and estimation, under the condition that the approved acceleration node server ensures normal operation, if the probability is pLR > 0, esLR > 0 exists, and under the same network quality of the client, the probability of statistical data is combined at the same time, the estimation value esLR is obtained approximately:
in reality, the packet drop rate can intuitively reflect the network state of the current device, the sizes of the delay mean and the standard deviation are related to the network quality, and the delay mean and the variance have strong correlation with the packet drop rate. The isWifilAccel ═ 1 indicates that the WIFI and the mobile data network are simultaneously used when the acceleration mechanism of the accelerator is acceleration (i.e. 2G \3G \4G \5G network), and the isWifilAccel ═ 0 indicates that the WIFI and the mobile data network are not simultaneously used when the acceleration mechanism of the accelerator is acceleration (i.e. the acceleration mechanism is only using the WIFI network or only using the mobile data network).
The following is a deductive demonstration process of the model.
2.1 network quality assessment
Since the mean delay value, the standard deviation and the packet drop rate are related to the network state of the current device, the estimated values of the mean delay value and the standard deviation with zero profit should be dynamically adjusted according to the fluctuation range of the network.
From the statistical conclusions, esLR was obtained (see above formula for details). And (3) combining the statistical conclusion and the experience in the actual game process to obtain a high-probability event: when pLR is equal to or greater than 10%, acceleration is not beneficial, i.e., PCT is 0, so in this case, for the estimation of esAvg and esSd, the range of pLR is [0,0.1 ] and the range of esLR is [0,1 ").
2.2 probability distribution
The following are the probability distribution of the delay mean, the standard deviation and the packet drop rate by counting 1000 groups of samples randomly extracted from the speed measurement data of a certain known game:
the mean, standard deviation and sample value range corresponding to fig. 2 (delayed mean probability distribution):
mean value: 68.49302
Standard deviation: 76.04803
The corresponding mean, standard deviation and sample value ranges of fig. 2 (probability distribution of dropped packet rate):
mean value: 1.628492
Standard deviation: 10.04404
Mean, standard deviation and sample value ranges corresponding to fig. 4 (delay standard deviation probability distribution)
avg:48.13827
sd:151.9806
After each acceleration is completed, an estimated value esLR of the zero-revenue-state packet drop rate can be obtained from the known data acceleration packet drop rate pLR (including the complementary packet conversion) in combination with the network quality evaluation and the actual situation, wherein esLR is related to the network state, and the estimated values esAvg and esSd of the zero-revenue-state delay mean and the standard deviation are also related to the network state, so that esAvg and esSd are considered to have a certain correlation with esLR.
The probability distribution curves of the three items of data are approximately considered to be similar (the probability distribution curves can be considered to be approximately approximate to a certain scaling relation due to the same fluctuation influence factors), so that under the condition that esLR is known, the distribution curves of the packet dropping rate can be mapped to the distribution curves of the delay mean value and the standard deviation according to the relation of the corresponding distribution curves.
From the probability distribution characteristics:
2.3 probability distribution mapping
Setting: the probability distribution function of the packet drop rate is: f (x) is provided with
Delayed mean valueHas a probability distribution function of g (y) having
the probability distribution function of the standard deviation of the delay is p (z) with
for f (x) and g (y), n>In the case of 100:
since the value range of y is n/100 times x, under the same probability distribution, if x's probability distribution is enlarged by n/100 times, then there are:
in this case, f (x) and g (y) have the same lateral coordinate in the probability distribution coordinate system and the changed σxAlso approximately n/100 times enlarged, and is recorded as
at this time, the process of the present invention,the curve is substantially fitted to g (y), so that:
will be provided with
The same can be obtained:
2.4 estimation value measurement by probability distribution mapping method
Therefore, after the estimated value esLR in the zero-benefit state is estimated according to the known value pLR, the estimated delay mean value esAvg and the estimated standard deviation esSd in the zero-benefit state can be calculated according to the approximate mapping relationship of the probability distribution by esLR:
as will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is intended to include such modifications and variations.
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