Method and apparatus for processing frame synchronization data

1 . A method for processing frame synchronization data, comprising:

predicting, by a computing device, a congestion value of a next downlink data frame based on a congestion condition of received downlink data frames, wherein the predicting the congestion value comprises:

determining a congestion value of each of the received downlink data frames according to a difference value between a receiving time interval of two consecutive downlink data frames and a fixed transmitting interval of the received downlink data frames; and

predicting the congestion value of the next downlink data frame based on the congestion value of a current downlink data frame of the received downlink data frames and a current cumulative congestion value of the current downlink data frame; predicting a downlink network congestion trend based on the congestion value of the next downlink data frame;

adjusting a report time interval of uplink data frames based on the downlink network congestion trend; and

transmitting the uplink data frames to a server based on the adjusted report time interval.

2 . The method according to claim 1 , wherein the predicting the congestion value of the next downlink data frame comprises:

performing exponential smoothing processing on the congestion value of the current downlink data frame and the current cumulative congestion value of the current downlink data frame; and

predicting the congestion value of the next downlink data frame based on a weight of the congestion value of the current downlink data frame and a weight of the current cumulative congestion value of the current downlink data frame, the weight of the congestion value of the current downlink data frame being greater than the weight of the cumulative congestion value of the current downlink data frame.

3 . The method according to claim 1 , wherein the predicting the downlink network congestion trend based on the congestion value comprises:

calculating a slope regression coefficient based on a congestion value sequence of the received downlink data frames;

predicting, based on a determination that the slope regression coefficient is greater than 0, that the downlink network congestion is in an uptrend; and

predicting, based on a determination that the slope regression coefficient is less than 0, that the downlink network congestion is in a down trend.

4 . The method according to claim 1 , further comprising:

detecting network quality of downlink transmission of the received downlink data frames, wherein the predicting the downlink network congestion trend comprises predicting, based on a determination that a result of the network quality indicates that the computing device is in a weak network environment, the downlink network congestion trend.

5 . The method according to claim 1 , wherein the adjusting comprises:

adjusting, based on the downlink network congestion trend, a transmitting frequency of the uplink data frames, wherein the transmitting frequency is decreased based on a determination that the downlink network congestion is in an uptrend, and the transmitting frequency is increased based on a determination that the downlink network congestion is in a down trend, and wherein the adjusting the report time interval of uplink data frames comprises determining the report time interval of the uplink data frames based on the adjusted transmitting frequency.

6 . The method according to claim 1 , wherein the downlink network congestion trend is in direct proportion to the report time interval.

7 . An apparatus for processing frame synchronization data, the apparatus comprising circuitry configured to:

predict a congestion value of a next downlink data frame based on a congestion condition of received downlink data frames, wherein predicting the congestion value comprises:

determining a congestion value of each of the received downlink data frames according to a difference value between a receiving time interval of two consecutive downlink data frames and a fixed transmitting interval of the received downlink data frames; and

predicting the congestion value of the next downlink data frame based on the congestion value of a current downlink data frame of the received downlink data frames and a current cumulative congestion value of the current downlink data frame;

predict a downlink network congestion trend based on the congestion value of the next downlink data frame;

adjust a report time interval of uplink data frames based on the downlink network congestion trend; and

transmit the uplink data frames to a server based on the adjusted report time interval.

8 . The apparatus according to claim 7 , wherein the circuitry is configured to predict the congestion value of the next downlink data frame by:

performing exponential smoothing processing on the congestion value of the current downlink data frame and the current cumulative congestion value of the current downlink data frame; and

predicting the congestion value of the next downlink data frame based on a weight of the congestion value of the current downlink data frame and a weight of the current cumulative congestion value of the current downlink data frame, the weight of the congestion value of the current downlink data frame being greater than the weight of the cumulative congestion value of the current downlink data frame.

9 . The apparatus according to claim 7 , wherein the circuitry is configured to predict the downlink network congestion trend based on the congestion value by:

calculating a slope regression coefficient based on a congestion value sequence of the received downlink data frames;

predicting, based on a determination that the slope regression coefficient is greater than 0, that the downlink network congestion is in an uptrend; and

predicting, based on a determination that the slope regression coefficient is less than 0, that the downlink network congestion is in a down trend.

10 . The apparatus according to claim 7 , wherein the circuitry is configured to:

detect network quality of downlink transmission of the received downlink data frame; and

predict the downlink network congestion trend by predicting, based on a determination that a result of the network quality indicates that the apparatus is in a weak network environment, the downlink network congestion trend.

11 . The apparatus according to claim 7 , wherein the circuitry is configured to adjust the report time interval by: adjusting, based on the downlink network congestion trend, a transmitting frequency of the uplink data frames, wherein the transmitting frequency is decreased based on a determination that the downlink network congestion is in an uptrend, and the transmitting frequency is increased based on a determination that the downlink network congestion is in a down trend, and wherein the circuitry is configured to adjust the report time interval of uplink data frames by determining the report time interval of the uplink data frames based on the adjusted transmitting frequency.

12 . The apparatus according to claim 7 , wherein the downlink network congestion trend is in direct proportion to the report time interval.

13 . A non-transitory computer-readable storage medium storing instructions, when executed, cause:

predicting, by a computing device, a congestion value of a next downlink data frame based on a congestion condition of received downlink data frames, wherein the predicting the congestion value comprises:

determining a congestion value of each of the received downlink data frames according to a difference value between a receiving time interval of two consecutive downlink data frames and a fixed transmitting interval of the received downlink data frames; and

predicting the congestion value of the next downlink data frame based on the congestion value of a current downlink data frame of the received downlink data frames and a current cumulative congestion value of the current downlink data frame;

predicting a downlink network congestion trend based on the congestion value of the next downlink data frame;

adjusting a report time interval of uplink data frames based on the downlink network congestion trend; and

transmitting the uplink data frames to a server based on the adjusted report time interval.

14 . The non-transitory computer-readable storage medium according to claim 13 , wherein the instructions, when executed, cause the predicting the congestion value of the next downlink data frame by causing:

performing exponential smoothing processing on the congestion value of the current downlink data frame and the current cumulative congestion value of the current downlink data frame; and

predicting the congestion value of the next downlink data frame based on a weight of the congestion value of the current downlink data frame and a weight of the current cumulative congestion value of the current downlink data frame, the weight of the congestion value of the current downlink data frame being greater than the weight of the cumulative congestion value of the current downlink data frame.

15 . The non-transitory computer-readable storage medium according to claim 13 , wherein the instructions, when executed, cause the predicting the downlink network congestion trend based on the congestion value by causing:

calculating a slope regression coefficient based on a congestion value sequence of the received downlink data frames;

predicting, based on a determination that the slope regression coefficient is greater than 0, that the downlink network congestion is in an uptrend; and

predicting, based on a determination that the slope regression coefficient is less than 0, that the downlink network congestion is in a down trend.

16 . The non-transitory computer-readable storage medium according to claim 13 , wherein the instructions, when executed, further cause:

detecting network quality of downlink transmission of the received downlink data frames, and

wherein the instructions, when executed, cause the predicting the downlink network congestion trend by causing predicting, based on a determination that a result of the network quality indicates that a computing device is in a weak network environment, the downlink network congestion trend.

17 . The non-transitory computer-readable storage medium according to claim 13 , wherein the downlink network congestion trend is in direct proportion to the report time interval.