Method, apparatus, and computer readable medium for latency measurement

Abstract

Embodiments of the present application provide a method and device for measuring time delay, electronic equipment and computer readable medium. The method for measuring time delay comprises: dividing a total time delay of a cloud phone into a client time delay on a physical client side, a network transmission time delay and a server time delay on a cloud phone side; and measuring the client time delay, the network transmission time delay and the server time delay respectively, wherein the way of measuring time delay comprises at least one of recording frequency measurement, log dot measurement, simulated traffic measurement and real traffic measurement.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cloud computing, and particularly relates to a time delay measurement method and device, electronic equipment and computer readable medium. BACKGROUND

[0002] A cloud phone is a virtual phone running in the cloud, which can be controlled through a physical phone or a computer terminal to realize many functions such as chatting, gaming, video watching, etc. During the use of the cloud phone, the cloud phone time delay is one of the important factors affecting the use experience.

[0003] At present, the measurement method for the cloud phone time delay is mainly used to measure the total time delay of the cloud phone, such as the time difference between the user clicking the physical client screen and the physical client screen displaying the response picture, and there is a lack of a segmented measurement method for the cloud phone time delay. SUMMARY

[0004] The purpose of the embodiments of the present application is to provide a time delay measurement method, device, electronic equipment and computer readable medium, which can overcome the problem of the lack of a segmented measurement method for the cloud phone time delay.

[0005] To solve the above technical problems, the embodiments of the present application are realized through the following aspects.

[0006] In a first aspect, the embodiments of the present application provide a time delay measurement method, comprising: dividing a total time delay of a cloud phone into a client time delay on a physical client side, a network transmission time delay and a server time delay on a cloud phone side; and respectively measuring the client time delay, the network transmission time delay and the server time delay, wherein the measurement method of the time delay comprises at least one of video recording measurement, log point measurement, simulated traffic measurement and real traffic measurement.

[0007] In a second aspect, the embodiments of the present application provide a time delay measurement device, comprising: a division module configured to divide a total time delay of a cloud phone into a client time delay on a physical client side, a network transmission time delay and a server time delay on a cloud phone side; and a measurement module configured to respectively measure the client time delay, the network transmission time delay and the server time delay, wherein the measurement method of the time delay comprises at least one of video recording measurement, log point measurement, simulated traffic measurement and real traffic measurement.

[0008] In a third aspect, the embodiments of the present application provide electronic equipment, comprising: a memory, a processor and computer executable instructions stored in the memory and executable on the processor, and when the computer executable instructions are executed by the processor, the time delay measurement method of the first aspect is realized.

[0009] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which is used to store computer executable instructions, and the computer executable instructions are executed by a processor to implement the method for measuring time delay in the first aspect.

[0010] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium, and the computer program includes program instructions, and the program instructions are executed by a computer to make the computer execute the method for measuring time delay in the first aspect.

[0011] In the embodiment of the present application, the total time delay of the cloud phone is divided into a client time delay on the side of an entity client, a network transmission time delay, and a server time delay on the side of a cloud phone; the client time delay, the network transmission time delay, and the server time delay are measured respectively, and the way of measuring the time delay includes at least one of recording frequency measurement, log dot measurement, simulated traffic measurement, and real traffic measurement, so that the cloud phone time delay can be measured in segments. BRIEF DESCRIPTION OF DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed in the embodiment or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0013] Figure 1 Fig. 1 shows a flow diagram of a method for measuring time delay provided by an embodiment of the present application;

[0014] Figure 2 Fig. 2 shows another flow diagram of a method for measuring time delay provided by an embodiment of the present application;

[0015] Figure 3 Fig. 3 shows another flow diagram of a method for measuring time delay provided by an embodiment of the present application;

[0016] Figures 4a to 4b Fig. 4 shows a schematic diagram of a method for measuring time delay provided by an embodiment of the present application;

[0017] Figure 5 Fig. 5 shows a structural schematic diagram of an apparatus for measuring time delay provided by an embodiment of the present application;

[0018] Figure 6 Fig. 6 shows a hardware structural schematic diagram of an electronic device for executing the method for measuring time delay provided by an embodiment of the present application. DETAILED DESCRIPTION

[0019] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0020] The latency measurement method provided in this application can be executed by an electronic device, such as a terminal device, a server device, or a network-side device. In other words, the method can be executed by software or hardware installed on the aforementioned devices. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The terminal device includes, but is not limited to, mobile phones, tablets, laptops, notebook computers, personal digital assistants, handheld computers, netbooks, super mobile personal computers, mobile internet devices, augmented reality devices, virtual reality devices, robots, wearable devices, aircraft, vehicle-mounted devices, shipborne devices, pedestrian terminals, smart home devices, game consoles, personal computers, ATMs, or self-service machines. The network-side device can include access network devices or core network devices, wherein the access network device can also be called a Radio Access Network (RAN) device, a Radio Access Network function, or a Radio Access Network Unit. The access network device can include a base station, a Wireless Local Area Network (WLAN) access point (AS), or a Wireless Fidelity (WiFi) node. It should be noted that this application embodiment only uses a base station in a 5G system as an example for introduction, and does not limit the specific type of base station.Core network equipment may include, but is not limited to, at least one of the following: core network node, core network function, Mobility Management Entity (MME), Access and Mobility Management Function (AMF), Session Management Function (SMF), User Plane Function (UPF), Policy Control Function (PCF), Policy and Charging Rules Function (PCRF), Edge Application Server Discovery Function (EASDF), Unified Data Management (UDM), Unified Data Repository (UDR), Home Subscriber Server (HSS), Centralized network configuration (CNC), Network Repository Function (NRF), Network Exposure Function (NEF), Local NEF (or L-NEF), and Binding Support Function. Support Function (BSF), Application Function (AF), etc. It should be noted that this application embodiment only uses core network equipment in a 5G system as an example for description, and does not limit the specific type of core network equipment.

[0021] Figure 1 A flowchart illustrating a time delay measurement method provided in an embodiment of this application is shown. As shown in the figure, the method may include the following steps S110 and S120.

[0022] Step S110: Divide the total latency of the cloud phone into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side.

[0023] Total latency for a cloud phone refers to the total latency incurred during its use. For example, it's the time difference between the moment a user clicks on the physical client's screen and the moment the physical client's screen displays the response screen, where the response screen is the screen displayed in response to the user's click. During cloud phone usage, client latency refers to the latency incurred on the physical client side, which can be a physical mobile phone, physical computer, or other terminal devices mentioned above. Network transmission latency refers to the latency incurred during network transmission. Server latency refers to the latency incurred on the cloud phone side.

[0024] In this step, based on the different locations where latency occurs, the total latency of the cloud phone is divided into three different types of latency: client latency, network transmission latency, and server latency. This division method can serve as the basis for latency segmentation measurement.

[0025] Step S120: Measure the client latency, the network transmission latency, and the server latency respectively, wherein the latency measurement method includes at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement.

[0026] Frequency recording measurement refers to recording the screen of a physical client and analyzing the recording frame by frame to obtain the response time, thereby achieving latency measurement; log point measurement refers to obtaining the latency by acquiring logs with added markers, where the logs with added markers can be operating system or application logs; simulated traffic measurement refers to measuring latency using simulated traffic; real traffic measurement refers to measuring latency using real traffic during the use of cloud phones.

[0027] This step proposes different measurement methods to measure different types of delays separately.

[0028] In this embodiment, the total latency of the cloud phone is divided into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side. The client latency, network transmission latency, and server latency are measured respectively. The latency measurement methods include at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement. This allows the total latency of the cloud phone to be divided into different types of latency, and different measurement methods are proposed for different types of latency. This enables segmented measurement of cloud phone latency, thereby addressing cloud phone latency issues more effectively and optimizing the user experience of cloud phone services.

[0029] In one possible implementation, refer to Figure 2The illustrated embodiment of this application provides another flowchart of a latency measurement method. The network transmission latency X includes a first network transmission latency X1 and a second network transmission latency X2. The first network transmission latency X1 represents the latency between the physical client side and the User Plane Function (UPF), and the second network transmission latency X2 represents the latency between the UPF and the cloud phone side. For example, X1 is the frame transmission latency between the physical client side and the UPF; X2 is the network latency between the UPF and the cloud phone side.

[0030] During uplink transmission, the network transmission latency X includes the latency from the physical client to the UPF and the latency from the UPF to the cloud phone. During downlink transmission, the network transmission latency X includes the latency from the cloud phone to the UPF and the latency from the UPF to the physical client. In other words, X1 includes the latency from the physical client to the UPF in uplink transmission and the latency from the UPF to the physical client in downlink transmission; X2 includes the latency from the UPF to the cloud phone in uplink transmission and the latency from the cloud phone to the UPF in downlink transmission. Optionally, the uplink transmission process is a command uplink transmission process; the downlink transmission process is an audio / video downlink transmission process.

[0031] In one possible implementation, measuring the network transmission delay includes: measuring the first network transmission delay X1 using simulated traffic measurement and / or real traffic measurement methods.

[0032] The first network transmission delay X1 can be measured using either a traffic measurement method, a real traffic measurement method, or a combination of simulated and real traffic measurement methods.

[0033] The first network transmission latency X1 is measured using simulated traffic measurement, including: determining the first network transmission latency X1 based on the feedback from the UPF local router's ping to the Internet packet explorer when sending simulated traffic. Simulated traffic is used to simulate the real traffic of the cloud phone, including uplink commands, downlink frame video streams, frame rates, bitrates, etc., simulating real traffic. Simulated traffic is generated by a simulated traffic generator based on the actual scenario, including game traffic, video traffic, or a set of traffic with different frame rates. When sending simulated traffic generated by the simulated traffic generator, the physical client can ping the UDF local router; based on the ping results, the first network transmission latency X1 can be determined. To measure X1, a simulated traffic generator can be deployed in the UPF. The ping operation can be based on the User Datagram Protocol (UDP). Optionally, the average service single-packet latency can be calculated by simulating UDP pings based on the transmission of single service packets and frames.

[0034] The first network transmission latency X1 is measured using both simulated and real traffic measurement methods, including: measuring the second network transmission latency X2; determining the network transmission latency X based on the ping feedback from the cloud phone side; and determining the first network transmission latency X1 based on the network transmission latency X and the second network transmission latency X2. Real traffic can be the actual traffic used by the physical client, or a real traffic generator can be constructed to generate real traffic based on the actual traffic used by the physical client. Applications for measuring real traffic are installed on both the physical client and the cloud phone side. The second network transmission latency X2 can be obtained through these applications, combined with operating system and / or application logs. For example, X2 can be measured using the SpeedCloud tool by simulating business traffic flow. Pinging the server on the cloud phone side from the physical client side yields the network transmission latency X. Based on the network transmission latency X and the second network transmission latency X2, the first network transmission latency X1 can be measured, i.e., X1 = X - X2. Optionally, evaluation metrics related to lag, latency, and clarity can also be obtained based on operating system and application logs.

[0035] In this embodiment of the application, the network transmission delay is further divided, and a measurement method for the first network transmission delay and the second network transmission delay obtained by the division is provided, which can measure the delay at different stages in the network transmission process.

[0036] Figure 3 This diagram illustrates yet another flow chart of a time delay measurement method provided in an embodiment of this application. (See reference...) Figure 3In one possible implementation, the client-side latency includes a decoding latency T4, and the server-side latency includes an encoding latency T3. The decoding latency T4 refers to the time delay caused by data decoding; the encoding latency T3 is the time delay caused by data encoding. Optionally, T4 includes the frame waiting time on the client side; T3 includes the transmission waiting time on the server side.

[0037] The client-side latency is measured, including by log-based measurement and / or simulated traffic measurement, to measure the decoding latency T4; the server-side latency is measured, including by log-based measurement and / or simulated traffic measurement, to measure the encoding latency T3. It is understood that both log-based and simulated traffic measurement methods can measure the decoding latency T4. Combining these two methods, for example, using the results of simulated traffic measurement to verify the results of log-based measurement, can improve the accuracy of decoding latency measurement. Similarly, both log-based and simulated traffic measurement methods can measure the encoding latency T3. Combining these two methods, for example, using the results of simulated traffic measurement to verify the results of log-based measurement, can improve the accuracy of encoding latency measurement.

[0038] In one possible implementation, the client-side latency includes a screen display latency T1, which represents the time between the first moment when the user clicks the physical client screen and the second moment when the physical client screen responds to the click operation. Measuring the client-side latency includes measuring the screen display latency T1 using an external camera and video recording. This screen display latency T1 is usually imperceptible to the naked eye, and users often perceive the first and second moments as the same moment, i.e., the screen responds simultaneously with the touch. However, by recording at a high frame rate, such as 90fps (frames per second), the difference between these two moments, i.e., the screen display latency T1, can be observed.

[0039] It is important to note that screen display latency differs from the total cloud phone latency in the aforementioned embodiments. Firstly, screen display latency is a component of the client-side latency, while the total cloud phone latency is the sum of client-side latency, network transmission latency, and server-side latency. Secondly, both start at the moment the user clicks the physical client screen, but the difference lies in the timing: screen display latency ends at the moment the client screen responds to the click, while the total cloud phone latency ends at the moment the client screen displays the response screen. For example, when a user uses a cloud phone to operate a role-playing game, the second moment is when a pointer (e.g., a crosshair) appears on the screen in response to the user's click; the moment the response screen appears is when the character's attack range (e.g., an aperture) appears on the screen.

[0040] In this embodiment, client latency is further subdivided, enabling a more targeted approach to address client latency issues.

[0041] In one possible implementation, the method for measuring latency further includes measuring the total latency of the cloud phone using an external camera and frequency recording. The total latency of the cloud phone is also known as screen-to-screen (G2G) latency, which is the time difference between the moment the user touches the physical client screen and the moment the physical client screen displays the response screen. The response screen is the screen displayed in response to the user's click operation. For example, in the aforementioned role-playing game example, this includes a screen showing the character's attack range.

[0042] The server-side latency includes rendering latency T2. Measuring the server-side latency includes determining the rendering latency T2 based on the total latency of the cloud phone, the client latency, the network transmission latency, and the encoding latency T3 included in the server-side latency. Rendering latency T2 refers to the latency generated by graphics or game rendering, which may include latency generated by instruction processing, rendering, content acquisition, etc. Optionally, T2 = total cloud phone latency - client latency - network transmission latency - T3. The total cloud phone latency can be expressed as G2G latency.

[0043] In this embodiment, the total latency of the cloud phone is divided into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side. The client latency, network transmission latency, and server latency are measured respectively. The latency measurement methods include at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement. This allows the total latency of the cloud phone to be divided into different types of latency, and different measurement methods are proposed for different types of latency. This enables segmented measurement of cloud phone latency, thereby addressing cloud phone latency issues more effectively and optimizing the user experience of cloud phone services.

[0044] In one possible implementation, server latency also includes server frame wait latency Y. When using simulated traffic measurement, T1 = 0; T2 = 0; T3 = 0; T4 = 0, and X + Y are measured. According to the aforementioned embodiment, X is measurable; therefore, Y can be determined. Based on the determined Y, using real traffic measurement, T2 = G2G latency - T1 - T3 - T4 - XY.

[0045] Still referencing Figure 3 In one possible implementation, taking the use of a physical mobile phone to operate a role-playing game as an example, a method for latency measurement includes the following steps:

[0046] 1) Measure the total latency (G2G latency) of the cloud phone, which is the time difference between clicking on the physical phone screen and the display of the response screen. Clicking on the physical phone screen includes touching the screen with a finger or stylus.

[0047] 2) Measure the time difference T1 between clicking the physical phone screen and displaying the click coordinates on the screen using an external camera.

[0048] 3) Measure the rendering latency T2 and frame wait latency Y.

[0049] 4) Measure the encoding delay T3.

[0050] 5) Measure the decoding delay T4.

[0051] 6) Measure the frame transmission delay X1 between the client and the UPF.

[0052] 7) Measure the network latency x2 between the UPF and the server.

[0053] The factors influencing T1 and G2G latency include terminal performance, i.e., the performance of the physical mobile phone, including but not limited to the terminal's CPU computing power, RAM, operating system, and screen refresh rate. Optionally, terminal performance can be represented by the terminal model. Factors influencing T2 include the physical distance to the cloud phone and the number of applications simultaneously running on the physical phone. Factors influencing T3 include the cloud phone's resolution and bitrate. Factors influencing T4 include the cloud phone's frame rate and decoding buffer. Factors influencing X2 include the distance between the cloud phone and the physical receiver, primarily physical distance. Factors influencing X1 include fluctuations in the wireless network. Optionally, Y represents the frame buffer queue waiting latency set for a stable frame rate; X1+X2 represents the latency caused by network fluctuations and transmission distance under stable data source conditions. Optionally, T1 can be used to characterize the physical phone's performance; T1+T2 can be used to characterize the performance of applications used on the physical phone; T1+T2+Y+T3+T4 can be used to characterize the performance of applications directly connected to the cloud phone; and T1+T2+Y+T3+T4+X can be used to characterize the performance of cloud phone applications over a wide area network.

[0054] In one possible implementation, a latency measurement method also includes using the acquired latency to evaluate and optimize cloud phone services. The cloud phone service experience can be evaluated through three dimensions: source quality, presentation quality, and interaction quality. These three dimensions influence each other. When network conditions cannot ensure optimal performance across all three dimensions, a certain Quality of Service (QoS) strategy can be used to guarantee a basic user experience. For example, reducing resolution and bitrate can ensure smooth playback; or reducing resolution and bitrate can ensure fast interaction response. In the source quality dimension, indicators affecting image quality include image bitrate, frame rate, image resolution, screen refresh rate, screen resolution, and image encoding; indicators affecting audio quality include input layer audio bitrate, number of audio channels, and audio encoding; image quality, audio quality, and audio-visual synchronization further affect audiovisual quality. In the presentation quality dimension, average stutter duration, stutter frequency, and data loss rate affect the completeness and continuity of perception. In the interaction quality dimension, operation response time affects interaction quality.

[0055] In this embodiment, key factors affecting cloud phone latency can be identified, enabling corresponding measures to be taken to reduce cloud phone runtime latency and improve the end-to-end experience. Improving the end-to-end experience includes the ability to monitor the cloud phone application end-to-end, track data within the application to visualize all experience data, accurately locate problems in the end-to-end process, and optimize latency across the entire chain in stages.

[0056] In one possible implementation, refer to Figure 4aTaking a role-playing game operated by a physical mobile phone as an example, in one latency measurement method, t1 represents the moment the physical phone screen is touched, t2 represents the moment the pointer crosshair appears on the physical phone, t3 represents the moment the pointer crosshair appears on the cloud phone, t4 represents the moment the character's attack range aperture appears on the cloud phone, t5 represents the moment the pointer crosshair on the physical phone is rendered and captured on the screen, and t6 represents the moment the character's attack range aperture appears on the cloud phone. The time difference P1 between t2 and t5 can be used to represent the processing latency of the physical phone performing the game operation; the time difference P2 between t5 and t6 can be used to represent the processing latency of the cloud phone performing the game operation. High frame rate screen recording (90fps) is used to record the process from the appearance of the pointer crosshair to the appearance of the character's attack range aperture on both the physical phone and the cloud phone. The frame showing the pointer crosshair on either the physical phone or the cloud phone is the start frame, and the frame showing the character's attack range aperture is the end frame. Video processing software is used to calculate P1 and P2. The difference between P1 and P2 is the additional latency introduced by the cloud phone. Table 1 below shows a set of actual measurements.

[0057] Table 1

[0058] Cloud phone P2 (ms) Physical phone P1 (ms) P1-P2 (ms) Mean 49.7 18.25 31.45 p90 53.9 23.1 -- p95 57.95 23.55 --

[0059] Referring to the measurements in Table 1, the cloud phone P2 has a latency of approximately 50 milliseconds (ms), while the physical phone P1 has approximately 18 ms. Using TST tools, such as TST Cloud X, the network transmission frame latency X was measured to simulate real-world traffic from the cloud phone. In the live network test, X1 at a distance of approximately 65 ms @ 95%. The above-mentioned real-world traffic measurement method includes: the server starting to send video frames (the actual sending time needs to be reduced by one frame buffer); the client receiving the last data packet of the video frame (this time differs from the actual receiving of the last packet at the network layer by 10 ms); the client sending an acknowledgment message ACK to the server; and the server receiving the ACK. In the above process, Frame TransLatency is used. The time from the server sending the video frame to receiving the ACK returned by the client is the loop latency of the entire link. X = loop latency - 33, where 33 is the time required for the server to buffer one frame.

[0060] Figure 4b The test results show the frame transmission latency X measured on the TST live network. The test environment is a 2.6G network in a certain area. During the test period, the number of users was less than 15, and the utilization rate of Physical Resource Blocks (PRBs) during busy uplink and downlink times was less than 10%. The near-point latency p95 for X1 frame transmission is approximately 30ms; the level of X1 latency 65ms@95% is RSRP-105-107dBm.

[0061] In this embodiment, the total latency of the cloud phone is divided into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side. The client latency, network transmission latency, and server latency are measured respectively. The latency measurement methods include at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement. This allows the total latency of the cloud phone to be divided into different types of latency, and different measurement methods are proposed for different types of latency. This enables segmented measurement of cloud phone latency, thereby addressing cloud phone latency issues more effectively and optimizing the user experience of cloud phone services.

[0062] Figure 5 This diagram illustrates the structure of a latency measurement device according to an embodiment of this application. The device 500 includes a partitioning module 510 and a measurement module 520. The partitioning module 510 is used to divide the total latency of the cloud phone into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side. The measurement module 520 is used to measure the client latency, the network transmission latency, and the server latency respectively. The latency measurement method includes at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement.

[0063] In one possible implementation, the network transmission delay includes a first network transmission delay and a second network transmission delay, wherein the first network transmission delay is used to represent the delay between the entity client side and the user plane function UPF, and the second network transmission delay is used to represent the delay between the UPF and the cloud phone side.

[0064] In one possible implementation, the measurement module 520 is used to measure the transmission delay of the first network in a simulated traffic measurement mode and / or a real traffic measurement mode.

[0065] In one possible implementation, the measurement module 520 is used to determine the first network transmission delay based on the feedback from the UPF local router's ping to the Internet packet explorer when sending simulated traffic.

[0066] In one possible implementation, the measurement module 520 is used to measure the second network transmission delay; determine the network transmission delay based on the ping feedback from the cloud phone side; and determine the first network transmission delay based on the network transmission delay and the second network transmission delay.

[0067] In one possible implementation, the client latency includes decoding latency, and the server latency includes encoding latency.

[0068] In one possible implementation, the measurement module 520 is used to measure the decoding latency using a log-based measurement method and / or a simulated traffic measurement method; the measurement module 520 is also used to measure the encoding latency using a log-based measurement method and / or a simulated traffic measurement method.

[0069] In one possible implementation, the client latency includes screen display latency, which represents the time between the first moment when the user clicks the physical client screen and the second moment when the physical client screen responds to the click operation; the measurement module 520 is used to measure the screen display latency by means of an external camera and frequency recording measurement.

[0070] In one possible implementation, the measurement module 520 is also used to measure the total latency of the cloud phone by means of an external camera and frequency recording measurement.

[0071] In one possible implementation, the server latency includes rendering latency, and the measurement module 520 is used to determine the rendering latency based on the total latency of the cloud phone, the client latency, the network transmission latency, and the encoding latency included in the server latency.

[0072] The device 500 provided in this application embodiment can execute the methods described in the preceding method embodiments and achieve the functions and beneficial effects of the methods described in the preceding method embodiments, which will not be repeated here.

[0073] Figure 6 This diagram illustrates the hardware structure of an electronic device executing a latency measurement method provided in an embodiment of this application. Referring to the diagram, at the hardware level, the electronic device 600 includes a processor 610, and optionally, an internal bus 620, a network interface 630, and a memory. The memory may include RAM, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk storage device. Of course, the electronic device may also include other hardware required for other services.

[0074] The processor 610, network interface 630, and memory can be interconnected via an internal bus 620. This internal bus 620 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be categorized as an address bus, data bus, control bus, etc. For ease of illustration, only a single bidirectional arrow is used in this diagram, but this does not imply that there is only one bus or one type of bus.

[0075] The memory is used to store programs. Specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory 640 and non-volatile memory 650, and provides instructions and data to the processor 610.

[0076] The processor 610 reads the corresponding computer program from the non-volatile memory 650 into the memory 640 and then runs it, forming a device for locating the target user at the logical level. The processor 610 executes the program stored in the memory, specifically performing the following: dividing the total latency of the cloud phone into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side; measuring the client latency, network transmission latency, and server latency respectively, wherein the latency measurement method includes at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement.

[0077] The above is as stated in this application. Figures 1 to 4bThe methods disclosed in the illustrated embodiments can be applied to or implemented by processor 610. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0078] The electronic device 600 can also execute the methods described in the preceding method embodiments and achieve the functions and beneficial effects of the methods described in the preceding method embodiments, which will not be repeated here.

[0079] Of course, in addition to software implementation, the electronic device of this application does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0080] This application also proposes a computer-readable storage medium storing one or more programs that, when executed by an electronic device including multiple applications, cause the electronic device to perform the following operations: dividing the total latency of the cloud phone into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side; measuring the client latency, the network transmission latency, and the server latency respectively, wherein the latency measurement method includes at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement.

[0081] The computer-readable storage medium includes read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, etc.

[0082] Furthermore, this application embodiment also provides a computer program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, implement the following process: dividing the total latency of the cloud phone into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side; measuring the client latency, the network transmission latency, and the server latency respectively, wherein the latency measurement method includes at least one of frequency recording measurement, log point measurement, simulated traffic measurement, and real traffic measurement.

[0083] In summary, the above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

[0084] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0085] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0086] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0087] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

Claims

1. A method for measuring time delay, characterized in that, include: The total latency of cloud phones is divided into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side. The client latency, the network transmission latency, and the server latency were measured respectively. The network transmission delay is measured using simulated traffic measurement and / or real traffic measurement methods. The client latency is measured using at least one of the following methods: log point measurement, simulated traffic measurement, and frequency recording measurement. The server latency is measured using log-based measurement and / or simulated traffic measurement methods.

2. The method according to claim 1, characterized in that, The network transmission delay includes a first network transmission delay and a second network transmission delay. The first network transmission delay is used to represent the delay between the physical client side and the user plane function UPF, and the second network transmission delay is used to represent the delay between the UPF and the cloud phone side.

3. The method according to claim 2, characterized in that, Measuring the network transmission latency using simulated traffic measurement methods and / or real traffic measurement methods includes: The transmission delay of the first network is measured using simulated traffic measurement and / or real traffic measurement methods.

4. The method according to claim 3, characterized in that, Measuring the transmission delay of the first network using simulated traffic measurement methods includes: When sending simulated traffic, the transmission delay of the first network is determined based on the feedback from the UPF local router's ping to the Internet packet explorer.

5. The method according to claim 3, characterized in that, The transmission delay of the first network is measured using both simulated and real traffic measurement methods, including: The transmission delay of the second network was measured; The network transmission latency is determined based on the ping feedback from the cloud phone side; The first network transmission delay is determined based on the network transmission delay and the second network transmission delay.

6. The method according to claim 1, characterized in that, The client-side latency includes decoding latency, and the server-side latency includes encoding latency.

7. The method according to claim 6, characterized in that, Measuring client latency using at least one of log-based measurement, simulated traffic measurement, and frequency recording measurement methods includes: The decoding latency is measured using log-based measurement and / or simulated traffic measurement methods. The measurement of server latency using log-based measurement and / or simulated traffic measurement methods includes: The encoded latency is measured using log point measurement and / or simulated traffic measurement methods.

8. The method according to claim 1, characterized in that, The client latency includes screen display latency, which represents the time between the first moment when the user clicks the physical client screen and the second moment when the physical client screen responds to the click operation. Measuring client latency using at least one of log-based measurement, simulated traffic measurement, and frequency recording measurement methods includes: The screen display latency was measured using an external camera and frequency recording.

9. The method according to claim 1, characterized in that, Also includes: The total latency of the cloud phone was measured using an external camera and frequency recording.

10. The method according to claim 9, characterized in that, The server latency includes rendering latency. Measuring the server latency includes: The rendering latency is determined based on the total latency of the cloud phone, the client latency, the network transmission latency, and the encoding latency included in the server latency.

11. A device for measuring time delay, characterized in that, include: The partitioning module is used to divide the total latency of the cloud phone into client latency on the physical client side, network transmission latency, and server latency on the cloud phone side. The measurement module is used to measure the client latency, the network transmission latency, and the server latency, respectively. The network transmission delay is measured using simulated traffic measurement and / or real traffic measurement methods. The client latency is measured using at least one of the following methods: log point measurement, simulated traffic measurement, and frequency recording measurement. The server latency is measured using log-based measurement and / or simulated traffic measurement methods.

12. An electronic device, characterized in that, include: A memory, a processor, and computer-executable instructions stored in the memory and executable on the processor, wherein the computer-executable instructions, when executed by the processor, implement the method for time delay measurement according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store computer-executable instructions that, when executed by a processor, implement the delay measurement method according to any one of claims 1 to 10.

14. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions that, when executed by a computer, cause the computer to perform the delay measurement method according to any one of claims 1 to 10.

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