CN104467997B - A kind of method and apparatus of the terminal energy-conservation based on wireless signal strength prediction - Google Patents
A kind of method and apparatus of the terminal energy-conservation based on wireless signal strength prediction Download PDFInfo
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Abstract
The invention discloses a kind of terminal power-economizing method and device based on wireless signal strength prediction, wherein, methods described includes, obtain the predicted value of wireless signal strength in actual time window, according to the predicted value of wireless signal strength in the actual time window, selection meets the time window for sending and requiring, prioritization is carried out to the waiting list for meeting each application program in the time window for sending requirement, according to the prioritization result, each application program uses the request of wireless signal in the response waiting list.The terminal power-economizing method based on wireless signal strength prediction and device that the present invention is provided can improve the utilization ratio of high-quality wireless signal, while reduce the energy ezpenditure of wireless signal, so as to the energy to terminal is using optimizing.
Description
Technical Field
The invention relates to the field of mobile computing, in particular to a terminal energy-saving method and device based on wireless signal strength prediction.
Background
As a well-developed technology, wireless networking (WIFI), which provides a personal computer and a handheld terminal (e.g., a mobile phone, a tablet computer, etc.) with convenient network access, especially a smart phone, makes it an indispensable part of the daily life of a user.
The energy consumed when the WIFI is used for data packet transmission is far lower than the energy consumed when the 3G network and the 4G network are used for data packet transmission. For example, when transmitting a data packet, the energy consumed for transmission using WIFI is only 0.04J, while the 3G network and the 4G LTE network consume 7.38J and 12.76J, respectively. However, for the same size data transmission, the drop in wireless signal strength from-50 dBm to-90 dBm results in 810.5% excess energy consumption, so that a poor WIFI link not only reduces the overall throughput, but also greatly extends the WIFI transmission duration, which results in a significant increase in the energy consumed per byte of transmission.
In the prior art, a scheduling strategy is designed on a personal computer and a handheld terminal (such as a mobile phone and a tablet personal computer) or a WIFI access point to improve the energy utilization efficiency of WIFI, but the method does not substantially solve the influence of wireless signal strength on WIFI energy consumption, and the energy yield of the method can be quickly offset by a poor wireless signal environment, so that the energy utilization efficiency of WIFI is low and the energy consumption is high when the quality of a wireless signal is unstable.
Disclosure of Invention
In view of the above, the present invention provides a method and an apparatus for saving power of a terminal based on wireless signal strength prediction, so as to improve utilization efficiency of a high-quality wireless signal and reduce energy consumption of the wireless signal, thereby optimizing energy usage of the terminal.
In a first aspect, an embodiment of the present invention provides a terminal energy saving method based on wireless signal strength prediction, where the method includes:
obtaining a predicted value of the wireless signal strength in the current time window;
selecting a time window which meets the sending requirement according to the predicted value of the wireless signal strength in the current time window;
carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement;
and responding to the request of each application program in the waiting queue for using the wireless signal according to the priority sorting result.
Further, the obtaining the predicted value of the wireless signal strength in the current time window includes:
collecting the strength value of the wireless signal in a historical time window;
calculating a distribution function of the wireless signal intensity in the current time window according to the acquired wireless signal intensity value in the historical time window;
and obtaining a predicted value of the wireless signal intensity in the current time window by utilizing edge probability distribution according to the distribution function of the wireless signal intensity in the current time window.
Further, the prioritizing the wait queues of the applications within the time window that meets the sending requirement includes:
acquiring application parameters of each application program, wherein the application parameters comprise the waiting time of each application program in a waiting queue, the correlation between each application program and a user and the blocking deadline of each application program;
and carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement according to the application parameters of the application programs.
Further, responding to the request for each application in the waiting queue to use the wireless signal according to the result of the prioritization comprises:
judging whether the transmission data of each application program in the time window meeting the sending requirement is smaller than the capacity of the time window meeting the sending requirement,
if yes, responding to the request of each application program in the waiting queue for using the wireless signal according to the priority sorting result;
and if not, cutting the transmission data of each application program in the time window meeting the sending requirement into first transmission data and second transmission data, wherein the first transmission data is transmitted in the time window meeting the sending requirement, and the second transmission data is transmitted in the next time window meeting the sending requirement.
Further, the method further comprises:
detecting an application program running in real time in the terminal;
when a real-time running application is detected, a request for the real-time running application to use the wireless signal is responded.
In a second aspect, an embodiment of the present invention provides a terminal power saving device based on wireless signal strength prediction, where the device includes:
the prediction module is used for obtaining a predicted value of the wireless signal strength in the current time window;
the window selection module is used for selecting a time window which meets the sending requirement according to the predicted value of the wireless signal strength in the current time window;
the priority module is used for carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement;
and the first response module is used for responding to the request of each application program in the waiting queue for using the wireless signal according to the priority sorting result.
Further, the prediction module comprises:
the acquisition unit is used for acquiring the strength value of the wireless signal in the historical time window;
the calculating unit is used for calculating a distribution function of the wireless signal strength in the current time window according to the acquired strength value of the wireless signal in the historical time window;
and the prediction unit is used for obtaining a predicted value of the wireless signal strength in the current time window by utilizing the marginal probability distribution according to the distribution function of the wireless signal strength in the current time window.
Further, the priority module includes:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring application parameters of each application program, and the application parameters comprise the waiting time of each application program in a waiting queue, the correlation between each application program and a user and the blocking deadline of each application program;
and the sequencing unit is used for carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement according to the application parameters of the application programs.
Further, the first response module comprises:
the judging unit is used for judging whether the transmission data of each application program in the time window meeting the sending requirement is smaller than the capacity of the time window meeting the sending requirement;
a response unit, configured to respond to a request for each application program in the waiting queue to use a wireless signal according to the priority ranking result when transmission data of each application program in a time window meeting a sending requirement is smaller than a capacity of the time window meeting the sending requirement;
and the cutting unit is used for cutting the transmission data of each application program in the time window meeting the sending requirement into first transmission data and second transmission data when the transmission data of each application program in the time window meeting the sending requirement is larger than the capacity of the time window meeting the sending requirement, wherein the first transmission data is transmitted in the time window meeting the sending requirement, and the second transmission data is transmitted in the next time window meeting the sending requirement.
Further, the apparatus further comprises:
the detection module is used for detecting the application program running in the terminal in real time;
and the second response module is used for responding to the request of the real-time running application program for using the wireless signal when the real-time running application program is detected.
According to the terminal energy-saving method and device based on wireless signal strength prediction, provided by the embodiment of the invention, the strength of the wireless signal in the current time window is predicted, the time window which meets the sending requirement is selected, the priority ranking is carried out on each application degree in the time window which meets the sending requirement, and the request of each application program for using the wireless signal is responded according to the priority ranking result, so that the utilization efficiency of the high-quality wireless signal is improved, the energy consumption of the wireless signal is reduced, the transmission of the wireless signal can be controlled in real time, and the energy use of the terminal is optimized.
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The above and other features and advantages of the present invention will become more apparent to those of ordinary skill in the art by describing in detail exemplary embodiments thereof with reference to the attached drawings, in which:
fig. 1 is a flowchart of a terminal power saving method based on wireless signal strength prediction according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of an experimental environment of wireless signal strength prediction in a terminal power saving method based on wireless signal strength prediction according to a first embodiment of the present invention;
FIG. 3 is a diagram illustrating the capacity of the time window for responding to the transmission data and meeting the transmission requirements of each application according to one embodiment of the present invention;
fig. 4 is a structural diagram of a terminal power saving apparatus based on wireless signal strength prediction according to a second embodiment of the present invention;
fig. 5 is a schematic diagram illustrating operation of intelligent radio network control according to a second embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings.
First embodiment
Fig. 1 is a flowchart of a terminal power saving method based on wireless signal strength prediction according to a first embodiment of the present invention, which may be applied to a personal computer or a handheld device to optimize the power usage of a terminal, as shown in fig. 1, wherein the handheld device may be a smart phone, a tablet computer, or the like, and the terminal power saving method based on wireless signal strength prediction includes:
and step 11, obtaining a predicted value of the wireless signal strength in the current time window.
Fig. 2 is a schematic diagram of an experimental environment of wireless signal strength prediction in a terminal energy saving method based on wireless signal strength prediction according to a first embodiment of the present invention, and as shown in fig. 2, in order to predict the strength of a wireless signal, 36 measurement points are selected to perform wireless signal strength sampling, each sampling lasts for 2 minutes, and in order to make a measurement result more accurate, a Kernel Density (KDE) estimation method is used to filter out a measurement error. The method utilizes the sampling values within a time window to smooth out the effects of errors, and the formula is as follows:
wherein K represents a kernel function, h represents a window size, and h is determined by the following formula according to the Silverman criterion:
from experimental verification, it can be inferred that the wireless signal strength is mostly concentrated on an average value for a fixed location, and thus it is assumed that the signal strength follows a gaussian distribution for the same locus. Table 1 shows the results of the Kolmogorov-Smirnov test with a confidence level of 0.05 as default, and the K-S test is used to check whether the wireless signal strength within a time window is gaussian, as shown in table 1:
TABLE 1 Kolmogorov-Smirnov test results
| Network name | Average window value h | Number of samples taken | Acceptance rate |
| Sense | 0.8689 | 58725 | 97.2％ |
| WiFi | 0.9384 | 29633 | 94.5％ |
| Holdtech007 | 0.7839 | 29385 | 81.3％ |
| NETGEAR89 | 0.2840 | 12888 | 96.3％ |
| NETGEAR22 | 1.0747 | 29610 | 87.5％ |
| Sum of | 0.79 | 160241 | 91.36％ |
As can be seen from table 1, 91.36% of the samples passed the K-Smirnov test even under relatively stringent validation conditions. Thus, the signal strength at a fixed point follows a gaussian distribution over a small time interval.
However, in practical applications, since a large amount of samples cannot be taken from all positions of the wireless signal, and at the same time, the wireless signal strength at the same position is also different in different time windows, the gaussian process is a random process that extends a static gaussian variable to a time sequence. Unlike traditional training methods, the gaussian process does not model inference on random variables. The method only carries out posterior probability calculation on sampling points, and the characteristic accords with the characteristic of no prior knowledge of the scene, so that the intensity of the wireless signal is predicted by adopting a Gaussian process, and the predicted value of the intensity of the wireless signal in the current time window is obtained.
To use the gaussian process, we need to make some assumptions: for any time window hiAssume that the wireless signal strength can be represented by the following equation:
ri＝f(hi)+∈,i＝1,2,3,…
where ∈ is white Gaussian noise, f is a possible mapping from h to riAnd ri(i ≠ j) is independent of each other.
Assuming that there are m sets of sampled signals of the radio signal within a time window, the radio signal strength of which is denoted by r, then for any random sequence of the radio signal strength r, { r }k1,rk2,...,rkmThe sum of these random variables satisfies the following expression:
wherein,is a windowIs the variance. It can be seen from the above equation that the combination of these random variables follows a gaussian distribution, and therefore, it can be concluded that the strength of the wireless signal follows a gaussian distribution within a small time window.
Therefore, the intensity of the wireless signal can be predicted in real time by adopting a gaussian process, and specifically, the obtaining the predicted value of the intensity of the wireless signal in the current time window may include:
and step 111, collecting the strength value of the wireless signal in the historical time window.
Each time window can contain M groups of sampling signals of wireless signals, the wireless signal intensity of the M groups of sampling signals obeys Gaussian distribution, and the conditional distribution characteristics of the wireless signal intensity in the current time window are obtained by collecting the intensity values of the wireless signals in the historical time window.
And 112, calculating a distribution function of the wireless signal strength in the current time window according to the acquired wireless signal strength value in the historical time window.
Let x beAAnd xBAre two continuous variables derived from gaussian processes that obey a joint gaussian distribution N (μ, Σ), whose conditional probability distribution is represented by the following equation:
their probability distribution also follows a gaussian distribution, i.e.:
wherein
Assuming that the wireless signal strength r follows a Gaussian process with a mean value of 0 and a covariance of K in a time window, the current time window h*Wireless signal strength and training set inA gaussian process that satisfies a joint distribution is satisfied,
wherein,and adding the noise formula and the jointly distributed Gaussian formula to obtain a distribution function of the wireless signal strength in the current time window as follows:
and 113, obtaining a predicted value of the wireless signal strength in the current time window by utilizing the marginal probability distribution according to the distribution function of the wireless signal strength in the current time window.
According to the distribution function of the wireless signal intensity in the current time window, the predicted value of the wireless signal intensity in the current time window is obtained by utilizing the marginal probability distribution as follows:
wherein After simplification, a confidence interval with a confidence level of α can be obtained:
furthermore, for the kernel function K, it measures the correlation between two windows, and this correlation determines the influence of the training set data on the final result. Typically, the kernel function K is represented by the following formula:
the kernel function K is essentially a covariance, and the most basic requirement is that the determinant must be greater than or equal to 0, i.e. must be a semi-positive definite matrix, and in order to meet this requirement, a square exponential kernel (RBF) is used. This models the relationship between variables that follow a gaussian distribution, a property that satisfies the needs of our scenario. The expression for this kernel is as follows:
wherein γ represents the kernel length of the kernel function, and as can be seen from the above equation, if two time windows are relatively close to each other, the intensities of the wireless signals in the two time windows have strong correlation, that is, the wireless signals have space-time correlation, and therefore, the predicted value of the intensity of the wireless signals can be obtained in real time by using gaussian distribution.
And step 12, selecting the time window which meets the sending requirement according to the predicted value of the wireless signal intensity in the current time window.
Since the terminal device consumes more energy when communicating using a radio signal with a poor quality, it needs to communicate under the condition of a good quality radio signal, and in order to obtain a radio signal with a good quality, it needs to select a time window meeting the transmission requirement according to the predicted value of the radio signal strength in the current time window, specifically, the time window meeting the transmission requirement can be selected by the following method.
Because the intensity distributions of the wireless signals in different time windows are different, a progressive threshold setting method is adopted, if the predicted value of the wireless signal intensity in the current time window is greater than the threshold of the wireless signal intensity in the time window, the time window meets the transmission requirement, if the predicted value of the wireless signal intensity in the current time window is less than the threshold of the wireless signal intensity in the time window, the time window does not meet the transmission requirement, and the progressive threshold can be set by adopting the following formula:
thrnow＝(1-α)*argmax{r∈hnow}+α*thrprev
where thr represents the threshold and α represents the forgetting factor, set to 0.125 by default. For each new time window, thr is updated to meet the needs of the current time window.
Accordingly, the capacity of the time window that meets the transmission requirement can be obtained, and the capacity of the time window is expressed as:
C(hi)＝hi*E[D(ri)]
wherein h isiTime window representing compliance with transmission requirements, riRepresents hiRadio signal strength in a time window meeting transmission requirementsPredicted value of (a), E [ D (r)i)]Is expressed in the wireless signal strength riNetwork throughput of.
And step 13, carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement.
This step determines the order in which applications access the wireless network within a time window that meets the transmission requirements. Specifically, the prioritizing the wait queues of the applications within the time window meeting the sending requirement may include:
step 131, obtaining application parameters of each application program, wherein the application parameters include waiting time of each application program in a waiting queue, correlation between each application program and a user, and blocking deadline of each application program
In this step, the initialization application parameters of each application are first obtained, and since different applications have different requirements for accessing the wireless network, the priority ranking of each application in the waiting queue needs to be determined according to the application parameters of each application.
The waiting time refers to the waiting time of a certain application program in the waiting queue, and if the waiting time of the application program is longer, the priority of the application program in the waiting queue is higher. The relevance of each application program to the user refers to the frequency of the application program used by the user every day, and if the frequency of the application program used is higher, the priority of the application program in the waiting queue is correspondingly higher. The blocking deadline of each application program comprises a maximum waiting time and a maximum retransmission time of one application program, wherein the maximum waiting time is generally set to 120S, the time for the retransmission time of one application program to reach the maximum retransmission time is about 7200S, and the blocking deadline can be updated correspondingly according to different use frequencies of the application programs.
In addition, for the application program with high priority, the use right of the application program to the wireless network should be controlled so as to reserve the use space for other application programs. The residual value corresponds to the proportion of the data which is not transmitted at present to the single transmission data. The average of the sizes of the single transmissions is an accurate estimate by analysis, and thus the statistics can be used to estimate the size of the residual.
And 132, performing priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement according to the application parameters of the application programs.
When the terminal equipment runs, the application parameters of each application program are correspondingly updated, whether each application program reaches the blocking deadline or not is detected, if the application program does not reach the blocking deadline, the priority of the application program is updated, and if the application program reaches the blocking deadline, the priority of the application program is set to be the highest priority. And after the priority level of each application program in the waiting queue is calculated, controlling the authority of each application program for accessing the wireless network according to the priority ranking result.
And step 14, responding to the request of each application program in the waiting queue for using the wireless signal according to the priority sorting result.
In this step, the terminal device responds to the request for using the wireless signal by each application in the waiting queue according to the result of the prioritization, and generally responds to the request for using the wireless signal by each application according to the result of the prioritization until the waiting queue is empty, but when the data transmitted by each application at a time is larger than the capacity of the time window meeting the transmission requirement, the data to be transmitted by each application needs to be cut. Specifically, the responding to the request of each application program in the waiting queue for using the wireless signal according to the priority sorting result may include the following steps:
step 141, determining whether the transmission data of each application program in the time window meeting the sending requirement is smaller than the capacity of the time window meeting the sending requirement, if yes, executing step 142, and if not, executing step 143.
When responding to a request of each application program for accessing a wireless signal, it is necessary to first judge whether the data to be transmitted exceeds the capacity of the time window meeting the transmission requirement, and determine whether the transmitted data needs to be cut according to the judgment result.
Step 142, responding to the request of each application program in the waiting queue to use the wireless signal.
Referring to fig. 3, fig. 3 is a schematic diagram illustrating the capacity of the time window corresponding to the transmission data and the sending requirement of each application according to the first embodiment of the present invention, please refer to fig. 3a, in fig. 3a, there are three different applications' transmission data, and when the data required to be transmitted by the three different applications is smaller than the time window t corresponding to the sending requirement0In response to a request for wireless signal utilization by each application in the wait queue.
Step 143, cutting the transmission data of each application program in the time window meeting the sending requirement into first transmission data and second transmission data, wherein the first transmission data is transmitted in the time window meeting the sending requirement, and the second transmission data is transmitted in the next time window meeting the sending requirement.
When the data to be transmitted by the three different application programs is more than or equal to the time window t meeting the sending requirement0The transmission data of the first application (see fig. 3c) or the transmission data of the last application (see fig. 3b) in the waiting queue is cut into the first transmission data and the second transmission data, wherein the first transmission data is in the time window t meeting the sending requirement0The second transmission data is transmitted in the next symbolTime window t for combined transmission requirements1The transmission is performed. "cut" is mainly to use "keep-alive" (keep-alive) mechanism of TCP to keep alive the network connection of the first transmission data and the second transmission data with the wireless signal, for example: the data which are needed to be transmitted by each application program at a time are divided into first transmission data and second transmission data, and the second transmission data are transmitted before the death time of the application program is reached after the first transmission data are transmitted in the time window which is in accordance with the sending requirement at present. The death time may be 120S, that is, the second transmission data may be transmitted at 119S.
Preferably, the terminal power saving method based on wireless signal strength prediction may further include:
and step 15, detecting the application program running in the terminal in real time.
In the actual operation process of the terminal device, some sudden situations are often encountered, for example: a new application is using the wireless network but the wireless network signal is poor or the wireless network is disabled, and it is necessary to respond to a request from the application running in real time to use the wireless signal.
Specifically, taking a mobile phone as an example, an application program detecting that the terminal is running in real time can detect screen and keyboard locks by registering a message broadcaster in the background using a message (message) mechanism in Android, and when a user uses the mobile phone, the user unlocks the two locks, so that the application program running in real time can be detected in real time.
And step 16, when the real-time running application program is detected, responding to the request of the real-time running application program for using the wireless signal.
When the real-time running application program is detected, the priority level of the real-time running application program in the waiting queue is set to be the highest level, so that the request of the real-time running application program for using the wireless signal can be preferably responded.
According to the terminal energy-saving method for predicting the wireless signal strength provided by the first embodiment of the invention, the strength of the wireless signal is predicted by using the non-parametric prediction model, and the high-quality wireless signal is used for network connection, so that the strategy of wireless network communication can be reasonably planned, the utilization efficiency of the high-quality wireless signal is improved, the energy consumption of the wireless signal is reduced, and the energy use of the terminal is optimized.
Second embodiment
Fig. 4 is a block diagram of a power saving apparatus for a terminal based on wireless signal strength prediction according to a second embodiment of the present invention, which can be used in a personal computer or a handheld device, such as a smart phone or a tablet computer, to optimize the power usage of the terminal, as shown in fig. 4, the power saving apparatus for a terminal based on wireless signal strength prediction includes a prediction module 21, a window selection module 22, a priority module 23 and a first response module 24,
the prediction module 21 is configured to obtain a predicted value of the wireless signal strength in a current time window, the window selection module 22 is configured to select a time window meeting the transmission requirement according to the predicted value of the wireless signal strength in the current time window, the priority module 23 is configured to perform priority ranking on a waiting queue of each application program in the time window meeting the transmission requirement, and the first response module 24 is configured to respond to a request for using a wireless signal by each application program in the waiting queue according to a result of the priority ranking.
The prediction module 21 may include an acquisition unit 211, a calculation unit 212, and a prediction unit 213.
The collecting unit 211 is configured to collect strength values of the wireless signals in the historical time window, the calculating unit 212 is configured to calculate a distribution function of the wireless signal strength in the current time window according to the collected strength values of the wireless signals in the historical time window, and the predicting unit 213 is configured to obtain a predicted value of the wireless signal strength in the current time window by using edge probability distribution according to the distribution function of the wireless signal strength in the current time window.
The priority module 23 may include an obtaining unit 231 and a sorting unit 232.
The obtaining unit 231 is configured to obtain application parameters of each application, where the application parameters include a waiting time of each application in a waiting queue, a correlation between each application and a user, and a blocking deadline of each application, and the updating and sorting unit 232 is configured to perform priority sorting on the waiting queue of each application within the time window meeting the sending requirement according to the application parameters of each application.
The first response module 24 may include a judging unit 241, a response unit 242, and a cutting unit 243.
The determining unit 241 is configured to determine whether transmission data of each application within the time window meeting the sending requirement is smaller than the capacity of the time window meeting the sending requirement, the responding unit 242 is configured to respond to a request of each application in the waiting queue for using a wireless signal according to the priority ranking result when the transmission data of each application within the time window meeting the sending requirement is smaller than the capacity of the time window meeting the sending requirement, the clipping unit 243 is configured to clip the transmission data of each application within the time window meeting the sending requirement into first transmission data and second transmission data when the transmission data of each application within the time window meeting the sending requirement is larger than the capacity of the time window meeting the sending requirement, where the first transmission data is transmitted within the time window meeting the sending requirement, and the second transmission data is transmitted in the next time window which meets the sending requirement.
Preferably, the terminal power saving device based on wireless signal strength prediction may further include a detection module 25 and a second response module 26.
The detecting module 25 is configured to detect a real-time running application in the terminal, and the second responding module 26 is configured to respond to a request of the real-time running application to use a wireless signal when the real-time running application is detected.
Next, a description is given to an operation flow of the terminal energy saving device based on wireless signal strength prediction according to this embodiment, as shown in fig. 5, fig. 5 is an operation schematic diagram of intelligent wireless network control according to a second embodiment of the present invention.
The method comprises the steps that a prediction module predicts that the predicted value of the wireless signal strength in a current time window is-70 dbm, a window selection module judges whether the time window meets a sending requirement or not through a real-time updated threshold, a priority module carries out priority sequencing on a waiting queue of each application program in the time window meeting the sending requirement, the application program can be a browser, a chat tool, a shopping tool or a antivirus tool and the like, the sequence of each application program accessing a wireless network is determined through a first response module according to the priority sequencing of each application program in the waiting queue, and the request of each application program in the waiting queue for using the wireless signals is responded, so that the application program can utilize high-quality wireless signals to carry out network connection.
In the terminal energy saving device based on wireless signal strength prediction according to the second embodiment of the present invention, the prediction module predicts the strength of the wireless signal in the current time window, the window selection module selects the time window meeting the transmission requirement, the priority module performs priority ordering on the waiting queue of each application program, and the first response module responds to the request of each application program in the waiting queue to use the wireless signal, so that network connection can be performed by using a high-quality wireless signal, the utilization efficiency of the wireless signal is improved, and the energy consumption of the wireless signal is reduced.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed over a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a memory device and executed by a computing device, or they may be separately fabricated into various integrated circuit modules, or multiple modules or steps thereof may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A terminal energy saving method based on wireless signal strength prediction is characterized by comprising the following steps:
obtaining a predicted value of the wireless signal strength in the current time window;
selecting a time window which meets the sending requirement according to the predicted value of the wireless signal strength in the current time window;
carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement;
responding to the request of each application program in the waiting queue for using the wireless signal according to the priority ranking result;
wherein the obtaining the predicted value of the wireless signal strength in the current time window comprises:
collecting the strength value of the wireless signal in a historical time window;
calculating a distribution function of the wireless signal intensity in the current time window according to the acquired wireless signal intensity value in the historical time window;
and obtaining a predicted value of the wireless signal intensity in the current time window by utilizing edge probability distribution according to the distribution function of the wireless signal intensity in the current time window.
2. The method of claim 1, wherein prioritizing the wait queues for applications within the time window that meets the transmission requirement comprises:
acquiring application parameters of each application program, wherein the application parameters comprise the waiting time of each application program in a waiting queue, the correlation between each application program and a user and the blocking deadline of each application program;
and carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement according to the application parameters of the application programs.
3. The method of claim 1, wherein responding to requests for wireless signals by applications in the wait queue based on the prioritization results comprises:
judging whether the transmission data of each application program in the time window meeting the sending requirement is smaller than the capacity of the time window meeting the sending requirement,
if yes, responding to the request of each application program in the waiting queue for using the wireless signal according to the priority sorting result;
and if not, cutting the transmission data of each application program in the time window meeting the sending requirement into first transmission data and second transmission data, wherein the first transmission data is transmitted in the time window meeting the sending requirement, and the second transmission data is transmitted in the next time window meeting the sending requirement.
4. The method of claim 1, further comprising:
detecting an application program running in real time in the terminal;
when a real-time running application is detected, a request for the real-time running application to use the wireless signal is responded.
5. A terminal power saving device based on wireless signal strength prediction, the device comprising:
the prediction module is used for obtaining a predicted value of the wireless signal strength in the current time window;
the window selection module is used for selecting a time window which meets the sending requirement according to the predicted value of the wireless signal strength in the current time window;
the priority module is used for carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement;
a first response module, configured to respond to a request for each application in the waiting queue to use a wireless signal according to the priority ranking result;
wherein the prediction module comprises:
the acquisition unit is used for acquiring the strength value of the wireless signal in the historical time window;
the calculating unit is used for calculating a distribution function of the wireless signal strength in the current time window according to the acquired strength value of the wireless signal in the historical time window;
and the prediction unit is used for obtaining a predicted value of the wireless signal strength in the current time window by utilizing the marginal probability distribution according to the distribution function of the wireless signal strength in the current time window.
6. The apparatus of claim 5, wherein the priority module comprises:
the device comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring application parameters of each application program, and the application parameters comprise the waiting time of each application program in a waiting queue, the correlation between each application program and a user and the blocking deadline of each application program;
and the sequencing unit is used for carrying out priority sequencing on the waiting queues of the application programs in the time window which meets the sending requirement according to the application parameters of the application programs.
7. The apparatus of claim 5, wherein the first response module comprises:
the judging unit is used for judging whether the transmission data of each application program in the time window meeting the sending requirement is smaller than the capacity of the time window meeting the sending requirement;
a response unit, configured to respond to a request for each application program in the waiting queue to use a wireless signal according to the priority ranking result when transmission data of each application program in a time window meeting a sending requirement is smaller than a capacity of the time window meeting the sending requirement;
and the cutting unit is used for cutting the transmission data of each application program in the time window meeting the sending requirement into first transmission data and second transmission data when the transmission data of each application program in the time window meeting the sending requirement is larger than the capacity of the time window meeting the sending requirement, wherein the first transmission data is transmitted in the time window meeting the sending requirement, and the second transmission data is transmitted in the next time window meeting the sending requirement.
8. The apparatus of claim 5, further comprising:
the detection module is used for detecting the application program running in the terminal in real time;
and the second response module is used for responding to the request of the real-time running application program for using the wireless signal when the real-time running application program is detected.
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| JP2017162311A (en) * | 2016-03-10 | 2017-09-14 | 富士通株式会社 | Smart device, priority processing method and priority processing program |
| CN111858021B (en) * | 2019-08-26 | 2021-09-03 | 马上消费金融股份有限公司 | Transaction channel selection method, online transaction method and related device |
| CN113839725B (en) * | 2020-06-24 | 2023-05-09 | 华为技术有限公司 | Method and device for predicting wireless signal propagation |
| CN114666742B (en) * | 2020-12-22 | 2023-04-18 | Oppo广东移动通信有限公司 | Bluetooth data packet broadcasting method, device, terminal and storage medium |
| CN115426712A (en) * | 2022-08-25 | 2022-12-02 | 浙江工业大学 | Wifi accurate robust indoor positioning method based on deep learning |
| CN116302009B (en) * | 2023-05-19 | 2023-08-08 | 微网优联科技(成都)有限公司 | Software updating method and device based on wireless router |
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| US8135443B2 (en) * | 2006-08-31 | 2012-03-13 | Qualcomm Incorporated | Portable device with priority based power savings control and method thereof |
| CN102780536B (en) * | 2012-07-26 | 2015-04-08 | 中国科学院信息工程研究所 | Method for predicating signal strength |
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