CN114706667A - Streaming media forwarding method based on heterogeneous computation - Google Patents
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Abstract
The embodiment of the invention discloses a streaming media forwarding method based on heterogeneous computation, and relates to the technical field of streaming media transmission. The method comprises the following steps: according to the multiple test cases, parallel detection is carried out on the machines and the streaming media acquisition equipment in the target high-speed network, and the states of each machine and the streaming media acquisition equipment are obtained; judging whether the computing power of a preset heterogeneous computer is sufficient or not according to the states of each machine and the streaming media acquisition equipment; and if the computing power of the heterogeneous computer is sufficient, forwarding the stream acquired by the machine and the streaming media acquisition equipment in the target high-speed network through the heterogeneous computer. The invention can automatically judge whether the computing power of the heterogeneous computer is sufficient or not, and can prompt the heterogeneous computer with higher replacement performance when the computing power is insufficient, thereby effectively improving the utilization efficiency of hardware in the whole network and improving the transmission performance of the streaming media.
Description
Technical Field
The invention belongs to the technical field of streaming media transmission, and particularly relates to a streaming media forwarding method based on heterogeneous computation.
Background
A cluster is a group of mutually independent computers interconnected by a high-speed network, which form a group and are managed in a single system mode. When a client interacts with a cluster, such as an independent server, the configuration of the cluster can effectively improve the availability, scalability, and computational performance of the overall system. In order to improve the transmission efficiency of the streaming media, the streaming media is often combined with a trunking system, so that the trunking system performs calculation and forwarding of the streaming media. However, there are hardware and software heterogeneities of the computers that make up the cluster, such as: the hardware has a mainframe, a minicomputer, a workstation, a PC and the like, and the operating system has Unix, Windows NT, Linux and the like, so that when streaming media data is forwarded, resources of the computer cannot be used in a good balance manner, and finally, the hardware has low calculation efficiency and utilization rate, and the calculation and forwarding efficiency of the streaming media is influenced.
Disclosure of Invention
In view of this, embodiments of the present invention provide a streaming media forwarding method based on heterogeneous computing, which is used to solve the problem that the existing streaming media forwarding method based on heterogeneous computing is not high in hardware computing efficiency and usage rate, and affects the computing and forwarding efficiency of streaming media. The invention can automatically judge whether the computing power of the heterogeneous computer is sufficient or not, and prompt the replacement of the heterogeneous computer when the computing power is insufficient, thereby effectively improving the utilization efficiency of hardware in the whole network and improving the performance of the whole system.
The embodiment of the invention provides a streaming media forwarding method based on heterogeneous computing, which comprises the following steps:
according to the multiple test cases, parallel detection is carried out on the machines and the streaming media acquisition equipment in the target high-speed network, and the states of each machine and the streaming media acquisition equipment are obtained;
judging whether the computing power of a preset heterogeneous computer is sufficient or not according to the states of each machine and the streaming media acquisition equipment;
and if the computing power of the heterogeneous computer is sufficient, forwarding the stream acquired by the machine and the streaming media acquisition equipment in the target high-speed network through the heterogeneous computer.
In an optional embodiment, after determining whether the computing power of the preset heterogeneous computer is sufficient, the method further includes:
if the computing power of the heterogeneous computer is insufficient, prompting to replace a preset heterogeneous computer with a heterogeneous computer with higher performance;
and when the notification of the replacement of the heterogeneous computer is received, returning to execute the step of carrying out parallel detection on the machine and the streaming media acquisition equipment in the target high-speed network according to the plurality of test cases.
In an optional embodiment, after determining that the computing power of the heterogeneous computer is sufficient, before forwarding, by the heterogeneous computer, the stream collected by the machine and the streaming media collection device in the target high-speed network, the method further includes:
determining task scheduling priority of each machine and the streaming media acquisition equipment according to the state of each machine and the streaming media acquisition equipment in the target high-speed network;
the forwarding, by the heterogeneous computer, the stream collected by the machine and the streaming media collection device in the target high-speed network includes:
and performing task scheduling on the machines and the streaming media acquisition equipment in the target high-speed network according to the task scheduling priority of each machine and the streaming media acquisition equipment, and forwarding the streams acquired by the machines and the streaming media acquisition equipment in the target high-speed network through the heterogeneous computer.
In an optional embodiment, the parallel detection of the machines and the streaming media collection devices in the target high-speed network according to the multiple test cases to obtain the states of each of the machines and the streaming media collection devices includes:
executing each test case for the first time in parallel through each machine and the streaming media acquisition equipment in the target high-speed network, and recording the time consumed by each machine and the streaming media acquisition equipment for executing each test case for the first time;
calculating the state grade value of each machine or streaming media acquisition equipment according to a first formula;
wherein the first formula is:
in the first formula, CiThe method comprises the steps of representing a state grade value of the ith machine or the streaming media acquisition equipment, wherein the smaller the grade value is, the higher the state grade of the corresponding machine or the streaming media acquisition equipment is represented; t isi(a) Representing the time consumed by the ith machine or streaming media acquisition equipment for executing the a-th test case for the first time; a is 1,2, …, n; n represents the number of the test cases;
indicates that the value of a is substituted into brackets from 1 to n to obtain Ti(a) Maximum value of (d);
the value of i is substituted into the parenthesis from 1 to m to obtain the maximum value in the parenthesis; i-1, 2, …, m; m is the total number of machines and streaming media acquisition equipment in the target high-speed network;
the judging whether the computing power of the preset heterogeneous computer is sufficient according to the states of each machine and the streaming media acquisition equipment comprises the following steps:
sorting the currently calculated state grade values of each machine and the streaming media acquisition equipment in the target high-speed network according to a descending order to obtain a first sorting result;
calculating an average value of all state rank values in the first ranking result;
screening out machines or streaming media acquisition equipment corresponding to the state grade values larger than the average value in the first sequencing result as secondary test equipment;
executing all the test cases in parallel through the screened secondary test equipment, and recording the time consumed by each secondary test equipment for executing all the test cases for the second time;
calculating a preset judgment value of insufficient computing power of the heterogeneous computer according to a second formula;
judging whether a judgment value which is calculated at present and has insufficient computing power of the heterogeneous computer is equal to a preset value or not;
if the judgment value of the insufficient computing power of the currently computed heterogeneous computer is equal to the preset value, determining that the preset computing power of the heterogeneous computer is insufficient, otherwise, determining that the preset computing power of the heterogeneous computer is sufficient;
wherein the second formula is:
in the second formula, E represents a judgment value that the computing power of the heterogeneous computer is insufficient; t is a unit ofb(2_ a) represents the time consumed by the b-th secondary test equipment for executing the a-th test case for the second time; t is a unit ofb(a) The time consumed by the b-th secondary test equipment for executing the a-th test case for the first time is represented; b is 1,2, …, B; b represents the total number of secondary test devices screened out.
In an optional embodiment, the task scheduling, according to the task scheduling priority of each machine and the streaming media collecting device, the performing task scheduling on the machine and the streaming media collecting device in the target high-speed network includes:
calculating a ranking array of each machine or streaming media acquisition equipment in the target high-speed network according to a third formula;
arranging the machines and the streaming media acquisition equipment in the target high-speed network in a sequence from small to large according to a first element value in the ranking array to obtain a second ordering result which is used as a task scheduling priority of each machine and the streaming media acquisition equipment in the target high-speed network;
according to the task scheduling priority of each machine and the streaming media acquisition equipment, performing task scheduling on the machines and the streaming media acquisition equipment in the target high-speed network;
wherein the third formula is:
in the third formula, Y (i) represents a ranking array of the ith machine and the streaming media acquisition equipment; k represents an integer variable with the value range of 1-i, n-i-; u () represents a non-negative check function, and if the value in parentheses is a non-negative number, the function value is 1, whereas if not, the function value is 0.
In an optional embodiment, if the first element value in the ranking array of at least two of the machines in the target high-speed network and the streaming media capturing device and/or the streaming media capturing device is the same, after obtaining the second ranking result, the method further includes:
and for the machines and the streaming media collection equipment with the same value of the first element in the ranking array, reordering the second ordering result part according to the sequence from small to large of the value of the second element in the ranking array to obtain a third ordering result, and taking the third ordering result as the task scheduling priority of each machine and the streaming media collection equipment in the target high-speed network.
In an optional embodiment, the preset value is 1.
The invention provides a streaming media forwarding method based on heterogeneous computation, which comprises the steps of firstly carrying out parallel detection on machines and streaming media acquisition equipment in a target high-speed network according to a plurality of test cases to obtain the state of each machine and each streaming media acquisition equipment, then obtaining whether the computation power of a heterogeneous computer is sufficient according to the state, and enabling the heterogeneous computer to carry out computation forwarding on streaming media when the computation power of the heterogeneous computer is sufficient. The invention can effectively improve the utilization efficiency of hardware in the whole network (namely the cluster) and improve the performance of the whole system.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of an embodiment of a streaming media forwarding method based on heterogeneous computing according to an embodiment of the present invention;
fig. 2 is a flowchart of an embodiment of a streaming media forwarding method based on heterogeneous computing according to the present invention;
FIG. 3 is a flowchart of one implementation of S202;
fig. 4 is a flowchart of an implementation method of S204.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of an embodiment of a streaming media forwarding method based on heterogeneous computing according to an embodiment of the present invention. Referring to fig. 1, the method includes the following steps S101-S105:
s101: and carrying out parallel detection on the machines and the streaming media acquisition equipment in the target high-speed network according to the plurality of test cases to obtain the states of each machine and each streaming media acquisition equipment.
In this embodiment, a plurality of test cases are used to perform parallel detection on the machines and the streaming media acquisition devices in the entire high-speed network to obtain detection results, where the detection results may include time consumed by the machines and the streaming media acquisition devices to execute the test cases, and the time consumed may sufficiently reflect the performance of the machines and the streaming media acquisition devices, and the better the performance is, the shorter the time consumed is, and vice versa.
S102: and judging whether the computing power of a preset heterogeneous computer is sufficient or not according to the states of each machine and the streaming media acquisition equipment, if so, executing S103, and otherwise, executing S104.
In this embodiment, the state of each machine and the streaming media acquisition device in the heterogeneous cluster, that is, the result information of the test case executed, may objectively reflect whether the computing power of the heterogeneous computer in the heterogeneous cluster is sufficient.
S103: and forwarding the stream acquired by the machine and the streaming media acquisition equipment in the target high-speed network through the heterogeneous computer.
S104: and prompting to replace the preset heterogeneous computer with a heterogeneous computer with higher performance.
In this embodiment, when it is determined that the computational power of the heterogeneous computers in the heterogeneous cluster system (i.e., there is a difference in hardware and/or OS) is insufficient, a system maintenance worker is prompted to use the heterogeneous computer with a higher performance to replace the existing heterogeneous computer, so that the performance of the computing and forwarding streaming media of the heterogeneous cluster is effectively improved.
S105: and returning to execute S101 after the heterogeneous computer is replaced.
In this embodiment, after the heterogeneous computer is replaced, the machines and the streaming media acquisition devices in the target high-speed network are detected in parallel by using a plurality of test cases, and whether the computing power of the heterogeneous computer in the heterogeneous cluster is sufficient or not is judged after a detection result is obtained, so that the performance of the whole heterogeneous cluster is in a better state after the heterogeneous computer is replaced, and the requirement for computing and forwarding the streaming media can be completely met.
The embodiment of the invention provides a streaming media forwarding method based on heterogeneous computation, which comprises the steps of firstly carrying out parallel detection on machines and streaming media acquisition equipment in a target high-speed network according to a plurality of test cases to obtain the state of each machine and the streaming media acquisition equipment, then judging whether the computation power of a heterogeneous computer is sufficient according to the state, and enabling the heterogeneous computer to carry out computation forwarding on streaming media when the computation power of the heterogeneous computer is sufficient; and when the calculated power is insufficient, prompting to replace the heterogeneous computer. The invention can automatically judge whether the computation power of the heterogeneous computer in the heterogeneous cluster is sufficient or not, and prompt the replacement of the heterogeneous computation when the computation power is insufficient, thereby effectively improving the utilization efficiency of hardware in the whole network (namely the cluster) and improving the overall performance.
Fig. 2 is a flowchart of an embodiment of a streaming media forwarding method based on heterogeneous computing according to the present invention. Referring to fig. 2, the method includes the following steps S201 to S206:
s201: and carrying out parallel detection on the machines and the streaming media acquisition equipment in the target high-speed network according to the plurality of test cases to obtain the states of each machine and each streaming media acquisition equipment.
As an alternative embodiment, step S201 includes:
s2011: and executing the test cases in parallel for the first time through each machine and the streaming media acquisition equipment in the target high-speed network, and recording the time consumed by each machine and the streaming media acquisition equipment for executing the test cases for the first time.
S2012: and calculating the state grade value of each machine or streaming media acquisition equipment according to a first formula.
Preferably, the first formula is:
in the first formula, CiThe method comprises the steps of representing a state grade value of the ith machine or the streaming media acquisition equipment, wherein the smaller the grade value is, the higher the state grade of the corresponding machine or the streaming media acquisition equipment is represented; t isi(a) Representing the time consumed by the ith machine or streaming media acquisition equipment for executing the a-th test case for the first time; a is 1,2, …, n; n represents the number of the test cases;
indicates that the value of a is substituted into brackets from 1 to n to obtain Ti(a) Maximum value of (d);
the value of i is substituted into the bracket from 1 to m to obtain the maximum value in the bracket; i is 1,2, …, m; m is the sum of the machines and the streaming media acquisition equipment in the target high-speed networkAnd (4) counting.
In the embodiment, the machines and the streaming media acquisition equipment in the whole high-speed network are detected in parallel according to a plurality of test cases to obtain detection results, then the state grade of each machine or the streaming media acquisition equipment can be obtained according to the first formula, the working capacity and the state of each machine or the streaming media acquisition equipment can be accurately analyzed through a plurality of tests, and subsequent automatic task scheduling is facilitated.
S202: and judging whether the computing power of a preset heterogeneous computer is sufficient or not according to the states of each machine and the streaming media acquisition equipment, if so, executing S203, and otherwise, executing S205.
S203: and determining the task scheduling priority of each machine and the streaming media acquisition equipment according to the state of each machine and the streaming media acquisition equipment in the target high-speed network.
S204: and performing task scheduling on the machines and the streaming media acquisition equipment in the target high-speed network according to the task scheduling priority of each machine and the streaming media acquisition equipment, and forwarding the streams acquired by the machines and the streaming media acquisition equipment in the target high-speed network through the heterogeneous computer.
S205: and prompting to replace the preset heterogeneous computer with a heterogeneous computer with higher performance.
S206: and returning to execute S201 after the heterogeneous computer is replaced.
As an alternative embodiment, as shown in fig. 3, step S202 may include the following steps S301 to S308:
s301: and sequencing the currently calculated state grade values of each machine and the streaming media acquisition equipment in the target high-speed network from small to large to obtain a first sequencing result.
In this example, according to CiThe corresponding machines or the streaming media collection devices are arranged from small to large, the arranged position value is the state grade value of each machine or the streaming media collection device, and the smaller the grade value is, the higher the grade is.
S302: calculating an average of all state rank values in the first ranking result.
S303: and screening out the machines or the streaming media acquisition equipment corresponding to the state grade values larger than the average value in the first sequencing result as secondary test equipment.
In this embodiment, the machine or the streaming media acquisition device corresponding to the state rank value greater than the average value in the first sequencing result is used as a secondary test device, that is, the machine and the streaming media acquisition device with a lower state rank are used as the secondary test devices, which facilitates subsequent parallel detection again, and further facilitates determining whether performance of the machine and the streaming media acquisition device is not high due to insufficient computational power of the heterogeneous computer.
S304: and executing all the test cases in parallel through the screened secondary test equipment, and recording the time consumed by each secondary test equipment for executing all the test cases for the second time.
S305: and calculating a preset judgment value that the computing power of the heterogeneous computer is insufficient according to a second formula.
Preferably, the second formula is:
in the second formula, E represents a judgment value that the computing power of the heterogeneous computer is insufficient; t is a unit ofb(2_ a) represents the time consumed by the b-th secondary test equipment for executing the a-th test case for the second time; t isb(a) The time consumed by the b-th secondary test equipment for executing the a-th test case for the first time is represented; b is 1,2, …, B; b represents the total number of secondary test devices screened out.
In this embodiment, the processor and the streaming media acquisition device with the lower state grade are subjected to parallel detection to determine whether the result is caused by insufficient computing power of the heterogeneous computer, so that the insufficient computing power of the heterogeneous computer is detected in time, and the heterogeneous computer with the insufficient computing power is replaced in time.
S306: and judging whether the judgment value of insufficient computing power of the currently computed heterogeneous computer is equal to a preset value or not, if so, executing S307, and otherwise, executing S308.
In this embodiment, the preset value is 1, that is: if E is equal to 1, the calculation power of the heterogeneous computer is insufficient, and the heterogeneous computer with higher performance needs to be replaced; if E is 0, the calculation power of the heterogeneous computer is sufficient, the heterogeneous computer with higher performance does not need to be replaced, and the whole judgment process has the advantages of simplicity and high efficiency.
S307: and determining that the computing power of the preset heterogeneous computer is insufficient.
S308: and determining that the computing power of the preset heterogeneous computer is sufficient.
As an alternative embodiment, as shown in fig. 4, step S204 may include the following steps S401 to S404:
s401: and calculating the ranking array of each machine or streaming media acquisition equipment in the target high-speed network according to a third formula.
Preferably, the third formula is:
in the third formula, Y (i) represents a ranking array of the ith machine or streaming media acquisition device; k represents an integer variable with the value range of 1-i, n-i-; u () represents a non-negative check function, and if the value in parentheses is a non-negative number, the function value is 1, whereas if not, the function value is 0.
In this embodiment, the smaller the value of the first element of y (i) is, the better the performance of the ith machine or the streaming media acquisition device is, the task may be preferentially executed by the ith machine or the streaming media acquisition device, and the efficiency of executing the task is ensured.
S402: and arranging the machines and the streaming media acquisition equipment in the target high-speed network according to the sequence of the first element value in the ranking array from small to large to obtain a second ordering result.
It should be noted that, if the first element value in the ranking array of at least two machines and/or streaming media collection devices in the target high-speed network is the same, step S403 needs to be executed after step S402, but if the first element values in the ranking array of any two machines and/or streaming media collection devices in the target high-speed network are not the same, step S403 does not need to be executed, the second ranking result is used as the task scheduling priority of each machine and streaming media collection device in the target high-speed network, and then S404 is directly executed by skipping.
S403: and for the machines and the streaming media collection equipment with the same value of the first element in the ranking array, reordering the second ordering result part according to the sequence from small to large of the value of the second element in the ranking array to obtain a third ordering result, and taking the third ordering result as the task scheduling priority of each machine and the streaming media collection equipment in the target high-speed network.
S404: and according to the task scheduling priority of each machine and each stream media acquisition device, performing task scheduling on the machines and the stream media acquisition devices in the target high-speed network, and forwarding the streams acquired by the machines and the stream media acquisition devices in the target high-speed network through the heterogeneous computer.
In the embodiment, the priority of task scheduling of the machines and the streaming media acquisition equipment in the high-speed network is obtained according to the state grade of each machine and the streaming media acquisition equipment, so that tasks are reasonably distributed, the utilization efficiency of hardware in the whole network is improved, and the overall performance is improved.
The embodiment of the invention provides a streaming media forwarding method based on heterogeneous computation, which comprises the steps of firstly carrying out parallel detection on machines and streaming media acquisition equipment in a target high-speed network according to a plurality of test cases to obtain the state of each machine and the state of each streaming media acquisition equipment, then obtaining whether the computing power of a heterogeneous computer is sufficient or not according to the state, and prompting to replace the heterogeneous computer when the computing power of the heterogeneous computer is insufficient; and when the calculation power is sufficient, the priority of task scheduling of the machines and the streaming media acquisition equipment in the high-speed network is obtained according to the state grade of each machine and the streaming media acquisition equipment, and then the tasks are reasonably distributed. The invention can automatically judge whether the computing power of the heterogeneous computers in the heterogeneous cluster is sufficient, prompt the replacement of heterogeneous computing when the computing power is insufficient, and reasonably distribute tasks when the computing power is sufficient, thereby effectively improving the utilization efficiency of hardware in the whole network (namely the cluster) and improving the overall performance.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations. The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A streaming media forwarding method based on heterogeneous computing is characterized by comprising the following steps:
according to the multiple test cases, parallel detection is carried out on the machines and the streaming media acquisition equipment in the target high-speed network, and the states of each machine and the streaming media acquisition equipment are obtained;
judging whether the computing power of a preset heterogeneous computer is sufficient or not according to the states of each machine and the streaming media acquisition equipment;
and if the computing power of the heterogeneous computer is sufficient, forwarding the stream acquired by the machine and the streaming media acquisition equipment in the target high-speed network through the heterogeneous computer.
2. The streaming media forwarding method based on heterogeneous computation of claim 1, after determining whether the computation power of the preset heterogeneous computer is sufficient, further comprising:
if the computing power of the heterogeneous computer is insufficient, prompting to replace a preset heterogeneous computer with a heterogeneous computer with higher performance;
and when the notification of the replacement of the heterogeneous computer is received, returning to execute the step of carrying out parallel detection on the machine and the streaming media acquisition equipment in the target high-speed network according to the plurality of test cases.
3. The streaming media forwarding method based on heterogeneous computing of claim 2, wherein after the computing power of the heterogeneous computer is determined to be sufficient, before forwarding, by the heterogeneous computer, the stream collected by the machine and the streaming media collection device in the target high-speed network, the method further comprises:
determining task scheduling priority of each machine and streaming media acquisition equipment according to the state of each machine and streaming media acquisition equipment in the target high-speed network;
the forwarding, by the heterogeneous computer, the stream collected by the machine and the streaming media collection device in the target high-speed network includes:
and performing task scheduling on the machines and the streaming media acquisition equipment in the target high-speed network according to the task scheduling priority of each machine and the streaming media acquisition equipment, and forwarding the streams acquired by the machines and the streaming media acquisition equipment in the target high-speed network through the heterogeneous computer.
4. The streaming media forwarding method based on heterogeneous computing according to claim 2, wherein the parallel detection of the machines and the streaming media collection devices in the target high-speed network according to the multiple test cases to obtain the states of each machine and each streaming media collection device comprises:
executing each test case for the first time in parallel through each machine and the streaming media acquisition equipment in the target high-speed network, and recording the time consumed by each machine and the streaming media acquisition equipment for executing each test case for the first time;
calculating the state grade value of each machine or streaming media acquisition equipment according to a first formula;
wherein the first formula is:
in the first formula, CiThe method comprises the steps of representing a state grade value of the ith machine or the streaming media acquisition equipment, wherein the smaller the grade value is, the higher the state grade of the corresponding machine or the streaming media acquisition equipment is represented; t isi(a) Representing the time consumed by the ith machine or streaming media acquisition equipment for executing the a-th test case for the first time; a is 1,2, …, n; n represents the testThe number of cases;
indicates that the value of a is substituted into brackets from 1 to n to obtain Ti(a) Maximum value of (d);
the value of i is substituted into the parenthesis from 1 to m to obtain the maximum value in the parenthesis; i is 1,2, …, m; m is the total number of machines and streaming media acquisition equipment in the target high-speed network;
the judging whether the computing power of the preset heterogeneous computer is sufficient according to the states of each machine and the streaming media acquisition equipment comprises the following steps:
sorting the currently calculated state grade values of each machine and the streaming media acquisition equipment in the target high-speed network according to a descending order to obtain a first sorting result;
calculating an average value of all state rank values in the first ranking result;
screening out machines or streaming media acquisition equipment corresponding to the state grade values larger than the average value in the first sequencing result as secondary test equipment;
executing all test cases in parallel through the screened secondary test equipment, and recording the time consumed by each secondary test equipment for executing all test cases for the second time;
calculating a preset judgment value of insufficient computing power of the heterogeneous computer according to a second formula;
judging whether a judgment value of insufficient computing power of the currently computed heterogeneous computer is equal to a preset value or not;
if the judgment value of the insufficient computing power of the currently computed heterogeneous computer is equal to the preset value, determining that the preset computing power of the heterogeneous computer is insufficient, otherwise, determining that the preset computing power of the heterogeneous computer is sufficient;
wherein the second formula is:
in the second formula, E represents a judgment value that the computing power of the heterogeneous computer is insufficient; t isb(2_ a) represents the time consumed by the b-th secondary test equipment for executing the a-th test case for the second time; t isb(a) The time consumed by the b-th secondary test equipment for executing the a-th test case for the first time is represented; b is 1,2, …, B; b represents the total number of secondary test devices screened out.
5. The streaming media forwarding method based on heterogeneous computing according to claim 4, wherein the task scheduling for the machine and the streaming media collection device in the target high-speed network according to the task scheduling priority of each machine and the streaming media collection device comprises:
calculating a ranking array of each machine or streaming media acquisition equipment in the target high-speed network according to a third formula;
arranging the machines and the streaming media acquisition equipment in the target high-speed network in a sequence from small to large according to a first element value in the ranking array to obtain a second ordering result which is used as a task scheduling priority of each machine and the streaming media acquisition equipment in the target high-speed network;
according to the task scheduling priority of each machine and the streaming media acquisition equipment, performing task scheduling on the machines and the streaming media acquisition equipment in the target high-speed network;
wherein the third formula is:
in the third formula, Y (i) represents a ranking array of the ith machine or streaming media acquisition device; k represents an integer variable with the value range of [1-i, n-i ]; u () represents a non-negative check function, and if the value in parentheses is a non-negative number, the function value is 1, whereas if not, the function value is 0.
6. The streaming media forwarding method based on heterogeneous computing according to claim 5, wherein if the first element value in the ranking array of at least two of the machines in the target high-speed network and the streaming media capturing device and/or the streaming media capturing device is the same, after obtaining the second ranking result, the method further comprises:
and for the machines and the streaming media collection equipment with the same value of the first element in the ranking array, reordering the second ordering result part according to the sequence from small to large of the value of the second element in the ranking array to obtain a third ordering result, and taking the third ordering result as the task scheduling priority of each machine and the streaming media collection equipment in the target high-speed network.
7. The streaming media forwarding method based on heterogeneous computation of any of claims 4-6, wherein the preset value is 1.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6981180B1 (en) * | 2000-03-16 | 2005-12-27 | Akamai Technologies, Inc. | Method and apparatus for testing request-response service using live connection traffic |
| US7315826B1 (en) * | 1999-05-27 | 2008-01-01 | Accenture, Llp | Comparatively analyzing vendors of components required for a web-based architecture |
| CN101674492A (en) * | 2008-09-09 | 2010-03-17 | 中兴通讯股份有限公司 | Method and device for testing performance of stream media server |
| US8392631B1 (en) * | 2008-10-02 | 2013-03-05 | Apple Inc. | Methods and apparatus for transmitting data streams via a heterogeneous network |
| US20150195182A1 (en) * | 2014-01-09 | 2015-07-09 | Citrix Systems, Inc | Systems and methods for cloud-based probing and diagnostics |
| US20170083423A1 (en) * | 2015-09-18 | 2017-03-23 | Echostar Technologies L.L.C. | Automated testing for content receivers |
| CN110301143A (en) * | 2016-12-30 | 2019-10-01 | 英特尔公司 | Method and apparatus for radio communication |
| CN110809904A (en) * | 2017-07-01 | 2020-02-18 | 英特尔公司 | Method and apparatus for vehicle radio communication |
| CN111143028A (en) * | 2019-12-13 | 2020-05-12 | 深圳微品致远信息科技有限公司 | LXC container-based SaaS platform implementation method and system |
| CN111311776A (en) * | 2020-02-06 | 2020-06-19 | 深圳联想懂的通信有限公司 | Intelligent inspection system and method based on Internet of things |
| CN112703457A (en) * | 2018-05-07 | 2021-04-23 | 强力物联网投资组合2016有限公司 | Method and system for data collection, learning and machine signal streaming for analysis and maintenance using industrial internet of things |
| CN113612794A (en) * | 2021-08-17 | 2021-11-05 | 深圳市邻友通科技发展有限公司 | Stream media data encryption transmission method and device, computer equipment and storage medium |
| CN113806073A (en) * | 2021-08-11 | 2021-12-17 | 中标慧安信息技术股份有限公司 | Computing power distribution scheduling method and system for edge computing platform |
| CN114020605A (en) * | 2021-10-22 | 2022-02-08 | 卓望数码技术（深圳）有限公司 | Automatic test case design method, system and computer readable storage medium |
| CN114138454A (en) * | 2021-10-19 | 2022-03-04 | 中标慧安信息技术股份有限公司 | Fair distribution method and system for computing power of edge computing platform |
-
2022
- 2022-03-24 CN CN202210296864.7A patent/CN114706667B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7315826B1 (en) * | 1999-05-27 | 2008-01-01 | Accenture, Llp | Comparatively analyzing vendors of components required for a web-based architecture |
| US6981180B1 (en) * | 2000-03-16 | 2005-12-27 | Akamai Technologies, Inc. | Method and apparatus for testing request-response service using live connection traffic |
| CN101674492A (en) * | 2008-09-09 | 2010-03-17 | 中兴通讯股份有限公司 | Method and device for testing performance of stream media server |
| US8392631B1 (en) * | 2008-10-02 | 2013-03-05 | Apple Inc. | Methods and apparatus for transmitting data streams via a heterogeneous network |
| US20150195182A1 (en) * | 2014-01-09 | 2015-07-09 | Citrix Systems, Inc | Systems and methods for cloud-based probing and diagnostics |
| US20170083423A1 (en) * | 2015-09-18 | 2017-03-23 | Echostar Technologies L.L.C. | Automated testing for content receivers |
| CN110301143A (en) * | 2016-12-30 | 2019-10-01 | 英特尔公司 | Method and apparatus for radio communication |
| CN110809904A (en) * | 2017-07-01 | 2020-02-18 | 英特尔公司 | Method and apparatus for vehicle radio communication |
| CN112703457A (en) * | 2018-05-07 | 2021-04-23 | 强力物联网投资组合2016有限公司 | Method and system for data collection, learning and machine signal streaming for analysis and maintenance using industrial internet of things |
| CN111143028A (en) * | 2019-12-13 | 2020-05-12 | 深圳微品致远信息科技有限公司 | LXC container-based SaaS platform implementation method and system |
| CN111311776A (en) * | 2020-02-06 | 2020-06-19 | 深圳联想懂的通信有限公司 | Intelligent inspection system and method based on Internet of things |
| CN113806073A (en) * | 2021-08-11 | 2021-12-17 | 中标慧安信息技术股份有限公司 | Computing power distribution scheduling method and system for edge computing platform |
| CN113612794A (en) * | 2021-08-17 | 2021-11-05 | 深圳市邻友通科技发展有限公司 | Stream media data encryption transmission method and device, computer equipment and storage medium |
| CN114138454A (en) * | 2021-10-19 | 2022-03-04 | 中标慧安信息技术股份有限公司 | Fair distribution method and system for computing power of edge computing platform |
| CN114020605A (en) * | 2021-10-22 | 2022-02-08 | 卓望数码技术（深圳）有限公司 | Automatic test case design method, system and computer readable storage medium |
Non-Patent Citations (3)
| Title |
|---|
| YONG LIU ET AL.: "《Design and Implementation of Performance Testing Utility for RTSP Streaming Media Server》", 《 2010 FIRST INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING, SIGNAL PROCESSING AND APPLICATIONS》 * |
| 白杨等: "国家高性能计算环境资源评价规范研究", 《科研信息化技术与应用》 * |
| 黄海等: "IMS实时计费系统集群的负载均衡研究", 《高技术通讯》 * |
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