Method and device for dynamically adjusting capacity of cloud video conference system

Abstract

The invention provides a method and a device for dynamically adjusting the capacity of a cloud video conference system. The method comprises the following steps of: acquiring terminal connection number and terminal bandwidth data borne by each site server in the cloud video conference system; analyzing the terminal connection number and the terminal bandwidth data to obtain internal and external network concurrent data of each site server within a specified time range; comparing the internal and external network concurrent data of each site server in a specified time range with a predefined concurrent data threshold range, and adjusting the capacity of the cloud video conference system according to a comparison result; according to the invention, the granularity of cloud video conference concurrent resource statistics can be refined, the internal and external network conference concurrent data of the server can be automatically counted, a reasonable system capacity management scheme is obtained, and the resource utilization rate and the system capacity management efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cloud computing, and in particular, to a method and device for dynamically adjusting the capacity of a cloud video conferencing system. Background Art

[0002] The existing statistical dimension of the resource usage of enterprise cloud video conferencing systems is mainly at the overall system concurrency level. For the capacity management of systems with a distributed deployment architecture, the granularity is relatively rough, and it is time-consuming and laborious to manage the system capacity manually, making it difficult to adapt to the dynamically changing system resource requirements in a timely manner.

[0003] Therefore, there is an urgent need for a new method for managing the capacity of cloud video conferencing systems to solve the above problems. Summary of the Invention

[0004] An embodiment of the present invention provides a method for dynamically adjusting the capacity of a cloud video conferencing system, which improves the resource utilization rate and the efficiency of system capacity management. The method for dynamically adjusting the capacity of the cloud video conferencing system includes:

[0005] Collecting the number of terminal connections and terminal bandwidth data carried by each site server in the cloud video conferencing system; each site server includes a media server, a recording server, and a fusion media server;

[0006] Analyzing the number of terminal connections and terminal bandwidth data to obtain the internal and external network concurrency data of each site server within a specified time range; the internal and external network concurrency data includes participation concurrency data and recording concurrency data;

[0007] Comparing the internal and external network concurrency data of each site server within a specified time range with a predefined concurrency data threshold range, and adjusting the capacity of the cloud video conferencing system according to the comparison result; the concurrency data threshold range includes: a warning threshold, an expansion threshold, and a reduction threshold.

[0008] An embodiment of the present invention also provides a device for dynamically adjusting the capacity of a cloud video conferencing system, which improves the resource utilization rate and the efficiency of system capacity management. The device for dynamically adjusting the capacity of the cloud video conferencing system includes:

[0009] A data collection module, configured to collect the number of terminal connections and terminal bandwidth data carried by each site server in the cloud video conferencing system; each site server includes a media server, a recording server, and a fusion media server;

[0010] A data statistics module, configured to analyze the number of terminal connections and terminal bandwidth data to obtain the internal and external network concurrency data of each site server within a specified time range; the internal and external network concurrency data includes participation concurrency data and recording concurrency data;

[0011] A data analysis module, which is used to compare the concurrent data of the internal and external networks of each site server within a specified time range with a predefined concurrent data threshold range, and adjust the capacity of the cloud video conferencing system according to the comparison result; the concurrent data threshold range includes: a warning threshold, an expansion threshold, and a reduction threshold.

[0012] An embodiment of the present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method for dynamically adjusting the capacity of the cloud video conferencing system is implemented.

[0013] An embodiment of the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method for dynamically adjusting the capacity of the cloud video conferencing system is implemented.

[0014] An embodiment of the present invention also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the above-mentioned method for dynamically adjusting the capacity of the cloud video conferencing system is implemented.

[0015] The method and device for dynamically adjusting the capacity of the cloud video conferencing system according to the embodiments of the present invention include: collecting the number of terminal connections and terminal bandwidth data carried by each site server in the cloud video conferencing system; analyzing the number of terminal connections and terminal bandwidth data to obtain the concurrent data of the internal and external networks of each site server within a specified time range; comparing the concurrent data of the internal and external networks of each site server within a specified time range with a predefined concurrent data threshold range, and adjusting the capacity of the cloud video conferencing system according to the comparison result. The embodiments of the present invention can refine the granularity of cloud video conferencing concurrent resource statistics, automatically count the concurrent data of internal and external network meetings of the server, obtain a reasonable system capacity management plan, and improve the resource utilization rate and system capacity management efficiency. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings:

[0017] Figure 1 It is an example diagram of the method for dynamically adjusting the capacity of the cloud video conferencing system in the embodiments of the present invention;

[0018] Figure 2 It is a specific example diagram of data analysis in the embodiments of the present invention;

[0019] Figure 3 This is a specific example diagram for comparing concurrent data between the internal and external networks in an embodiment of the present invention;

[0020] Figure 4 This is a structural example diagram of a device for dynamically adjusting the capacity of a cloud video conferencing system in an embodiment of the present invention;

[0021] Figure 5 This is a schematic diagram of the structure of a computer device in an embodiment of the present invention. Detailed implementation manners

[0022] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0023] The inventor's research found that the prior art focuses on expanding and shrinking the server cluster from the overall concurrent level of the enterprise. For example:

[0024] Obtain the current number of audio and video call channels of the server cluster, the number of audio and video call channels supported by the cluster, and historical meeting data; then, compare the current number of audio and video call channels of the server cluster with the supported number of audio and video call channels and historical meeting data respectively; if the current number of audio and video call channels is not less than a preset multiple of the supported number of audio and video call channels, or the supported number of audio and video call channels is less than the historical meeting data, expand the server cluster.

[0025] It can be seen that the solution in the prior art has a relatively rough granularity for the server resource management of an enterprise cloud video conferencing system adopting a distributed and hybrid cloud deployment architecture, which is not conducive to the enterprise to achieve refined resource management.

[0026] Therefore, according to the defects existing in the prior art, the inventor proposed a method for dynamically adjusting the capacity of a cloud video conferencing system in an embodiment of the present invention, aiming to refine the granularity of conference concurrent resource statistics, automatically count the internal and external network conference concurrent data based on the site dimension, and automatically analyze the system capacity optimization plan in combination with historical statistical data, so as to achieve refined management of system resources and adapt to the dynamically changing system resource requirements.

[0027] Figure 1 This is an example diagram of a method for dynamically adjusting the capacity of a cloud video conferencing system in an embodiment of the present invention. As Figure 1 shown, the method includes:

[0028] Step 101: Collect the terminal connection numbers and terminal bandwidth data borne by each site server in the cloud video conferencing system; each site server includes a media server, a recording server, and a converged media server;

[0029] Step 102: Analyze the terminal connection numbers and terminal bandwidth data to obtain the internal and external network concurrency data of each site server within a specified time range; the internal and external network concurrency data includes participation concurrency data and recording concurrency data;

[0030] Step 103: Compare the internal and external network concurrency data of each site server within a specified time range with a predefined concurrency data threshold range, and adjust the capacity of the cloud video conferencing system according to the comparison result; the concurrency data threshold range includes: a warning threshold, an expansion threshold, and a contraction threshold.

[0031] In the embodiment, collecting the terminal connection numbers and terminal bandwidth data borne by each site server in the cloud video conferencing system may include: collecting the terminal connection numbers and terminal bandwidth data of the terminals with conference call behaviors borne by each site server in the cloud video conferencing system.

[0032] For example, within the statistical time, real-time collect the terminal connection numbers borne by each media server, recording server, and converged server, and the terminal bandwidth data of each terminal borne by each media server, record the terminals with relevant conference call behaviors on the servers deployed at each site, and count the number of such terminals and the bandwidth data of each terminal.

[0033] In the embodiment, analyzing the terminal connection numbers and terminal bandwidth data to obtain the internal and external network concurrency data of each site server within a specified time range may include:

[0034] Previously, label the site servers according to the region where the site servers are located, and the label is used to determine that the category of the site server is an internal network server or an external network server;

[0035] Within a specified time range, at fixed time intervals, sum up the concurrency data of each site server labeled as an internal network server at the same moment to obtain the internal network concurrency data at that moment;

[0036] Within a specified time range, at fixed time intervals, sum up the concurrency data of each site server labeled as an external network server at the same moment to obtain the external network concurrency data at that moment.

[0037] For example, Figure 2 This is a specific example diagram of data analysis in the embodiment of the present invention, such as Figure 2As shown, tags are pre-assigned according to the regions where each site server is located, such as an intranet recording server and an extranet recording server; the concurrent data on the intranet recording server and the extranet recording server are collected respectively at fixed time intervals T; where T can be determined according to actual requirements; the concurrent data at the same moment for the same type of server are summed up to obtain the concurrent data at this moment, and further determine the concurrent data of each site server within a specified time range; in specific implementation, the maximum value of the concurrent data of each site server can be used as the subsequent threshold for comparison.

[0038] In the embodiment, the concurrent data of the intranet and the extranet may further include the H.323 participation concurrent data.

[0039] In the embodiment, Figure 3 This is a specific example diagram for comparing the concurrent data of the intranet and the extranet in the embodiment of the present invention. As Figure 3 shown, compare the concurrent data of the intranet and the extranet of each site server within a specified time range with the predefined concurrent data threshold range, and according to the comparison result, adjust the capacity of the cloud video conferencing system, which may include:

[0040] Step 301: At a predetermined period, compare the maximum value of the concurrent data of the intranet and the extranet of each site server within a specified time range with the warning threshold, the expansion threshold, and the reduction threshold;

[0041] Step 302: If the maximum value of the concurrent data of the intranet and the extranet of each site server within a specified time range reaches the warning threshold for multiple consecutive periods, issue a warning;

[0042] Step 303: If the maximum value of the concurrent data of the intranet and the extranet of each site server within a specified time range reaches the expansion threshold for multiple consecutive periods, expand the cloud video conferencing system according to the difference between the maximum value of the concurrent data and the expansion threshold;

[0043] Step 304: If the maximum value of the concurrent data of the intranet and the extranet of each site server within a specified time range reaches the reduction threshold for multiple consecutive periods, reduce the cloud video conferencing system according to the difference between the maximum value of the concurrent data and the reduction threshold.

[0044] In specific implementation, the concurrent data threshold range may include a warning threshold, an expansion threshold, and a reduction threshold. If the maximum value of the concurrent data of the intranet and the extranet reaches the warning threshold, a warning of insufficient memory or free memory is given to the maintenance personnel. If the maximum value of the concurrent data of the intranet and the extranet reaches the expansion threshold or the reduction threshold, the cloud video conferencing system is expanded or reduced.

[0045] For example, in the case of system expansion: If for N consecutive cycles, the maximum value of the concurrent data of the internal and external networks of each site server within the specified time range is higher than the expansion threshold, it is determined that the server cannot meet the requirements of the existing concurrent data at this time, and it is necessary to expand the CPU memory or the number of servers.

[0046] During specific implementation, it is possible to first determine whether the expansion of the CPU memory of the site server can meet the requirements of the concurrent data; the CPU memory of the server that needs to be expanded is calculated by subtracting the expansion threshold from the maximum value of the concurrent data of the internal and external networks. In actual calculations, it is usually calculated according to the number of terminals that a server CPU with 2 cores and 8G of memory can support.

[0047] If the expansion of the CPU memory alone cannot meet the requirements of the concurrent data, then the number of site servers is expanded; the number of servers that need to be expanded is calculated according to the following formula:

[0048]

[0049] For the case of system contraction: If for N consecutive cycles, the maximum value of the concurrent data of the internal and external networks of each site server within the specified time range is lower than the contraction threshold, it is determined that the server can meet the requirements of the existing concurrent data at this time, but there is a large waste of memory resources, and it is necessary to contract the CPU memory or the number of servers.

[0050] During specific implementation, it is possible to first determine whether the contraction of the CPU memory of the site server can meet the requirements of the concurrent data; the CPU memory of the server that needs to be contracted is calculated by subtracting the maximum value of the concurrent data of the internal and external networks from the contraction threshold. In actual calculations, it is usually calculated according to the number of terminals that a server CPU with 2 cores and 8G of memory can support.

[0051] If there is still a waste of memory resources after only contracting the CPU memory, then the number of site servers is contracted, and multiple terminals are migrated to the same server for operation.

[0052] In the embodiment, the range of the concurrent data threshold is predefined according to the CPU memory usage rate of each site server in the cloud video conferencing system.

[0053] In the embodiment of the present invention, a device for dynamically adjusting the capacity of a cloud video conferencing system is also provided, as described in the following embodiments. Since the principle of solving problems by this device is similar to that of the method for dynamically adjusting the capacity of a cloud video conferencing system, the implementation of this device can refer to the implementation of the method for dynamically adjusting the capacity of a cloud video conferencing system, and the repeated parts will not be described again.

[0054] Figure 4 For the structural schematic diagram of the device for dynamically adjusting the capacity of the cloud video conferencing system in the embodiment of the present invention, as Figure 4 shown, the device includes:

[0055] A data acquisition module 401, configured to acquire the number of terminal connections and terminal bandwidth data borne by each site server in the cloud video conferencing system; each site server includes a media server, a recording server, and a converged media server;

[0056] A data statistics module 402, configured to analyze the number of terminal connections and terminal bandwidth data to obtain the internal and external network concurrent data of each site server within a specified time range; the internal and external network concurrent data includes conference participation concurrent data and recording concurrent data;

[0057] A data analysis module 403, configured to compare the internal and external network concurrent data of each site server within a specified time range with a predefined concurrent data threshold range, and adjust the capacity of the cloud video conferencing system according to the comparison result; the concurrent data threshold range includes: a warning threshold, an expansion threshold, and a reduction threshold.

[0058] In one embodiment, the data acquisition module 401 is specifically configured to acquire the number of terminal connections and terminal bandwidth data of terminals with conference call behaviors borne by each site server in the cloud video conferencing system;

[0059] In one embodiment, the data statistics module 402 is specifically configured to pre-label the site server according to the area where the site server is located, and the label is used to determine that the category of the site server is an internal network server or an external network server;

[0060] Within a specified time range, at fixed time intervals, sum the concurrent data of each site server labeled as an internal network server at the same moment to obtain the internal network concurrent data at that moment;

[0061] Within a specified time range, at fixed time intervals, sum the concurrent data of each site server labeled as an external network server at the same moment to obtain the external network concurrent data at that moment.

[0062] In one embodiment, the internal and external network concurrent data further includes H.323 conference participation concurrent data.

[0063] In one embodiment, the data analysis module 403 is specifically configured to, at a predetermined period, compare the maximum value of the internal and external network concurrent data of each site server within a specified time range with a predefined concurrent data minimum threshold and a concurrent data maximum threshold;

[0064] At a predetermined period, compare the maximum value of the internal and external network concurrent data of each site server within a specified time range with the warning threshold, the expansion threshold, and the reduction threshold;

[0065] If the maximum value of the internal and external network concurrent data of each site server within a specified time range reaches the warning threshold for multiple consecutive periods, a warning is issued;

[0066] If for multiple consecutive cycles, the maximum value of the concurrent data of the internal and external networks of each site server within the specified time range reaches the expansion threshold, then the cloud video conferencing system is expanded according to the difference between the maximum value of the concurrent data of the internal and external networks and the expansion threshold.

[0067] If for multiple consecutive cycles, the maximum value of the concurrent data of the internal and external networks of each site server within the specified time range reaches the contraction threshold, then the cloud video conferencing system is contracted according to the difference between the maximum value of the concurrent data of the internal and external networks and the contraction threshold.

[0068] In one embodiment, the range of the concurrent data threshold is predefined according to the CPU memory usage rate of each site server in the cloud video conferencing system.

[0069] Based on the foregoing inventive concept, as Figure 5 shown, the present invention also provides a computer device 500, including a memory 510, a processor 520, and a computer program 530 stored on the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 530, the foregoing method for dynamically adjusting the capacity of the cloud video conferencing system is implemented.

[0070] An embodiment of the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the foregoing method for dynamically adjusting the capacity of the cloud video conferencing system is implemented.

[0071] An embodiment of the present invention also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the foregoing method for dynamically adjusting the capacity of the cloud video conferencing system is implemented.

[0072] The method and device for dynamically adjusting the capacity of the cloud video conferencing system according to the embodiments of the present invention include: collecting the number of terminal connections and terminal bandwidth data borne by each site server in the cloud video conferencing system; analyzing the number of terminal connections and terminal bandwidth data to obtain the concurrent data of the internal and external networks of each site server within the specified time range; comparing the concurrent data of the internal and external networks of each site server within the specified time range with the predefined range of concurrent data thresholds, and adjusting the capacity of the cloud video conferencing system according to the comparison result. The embodiments of the present invention can refine the granularity of cloud video conferencing concurrent resource statistics, automatically count the concurrent data of the internal and external networks of the server, obtain a reasonable system capacity management plan, and improve the resource utilization rate and system capacity management efficiency.

[0073] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) that contain computer-usable program code.

[0074] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0075] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implement the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0077] The specific embodiments described above further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for dynamically adjusting the capacity of a cloud video conferencing system, characterized in that, Including: Collecting the terminal connection numbers and terminal bandwidth data borne by each site server in the cloud video conferencing system; Each site server includes a media server, a recording server, and a converged media server; Analyzing the terminal connection numbers and terminal bandwidth data to obtain the internal and external network concurrency data of each site server within a specified time range; The internal and external network concurrency data includes conference participation concurrency data and recording concurrency data; Comparing the internal and external network concurrency data of each site server within a specified time range with a predefined concurrency data threshold range, and adjusting the capacity of the cloud video conferencing system according to the comparison result; The concurrency data threshold range includes: a warning threshold, an expansion threshold, and a reduction threshold.

2. The method according to claim 1, characterized in that, Collecting the terminal connection numbers and terminal bandwidth data borne by each site server in the cloud video conferencing system, including: Collecting the terminal connection numbers and terminal bandwidth data of the terminals with conference call behaviors borne by each site server in the cloud video conferencing system.

3. The method according to claim 1, wherein Analyzing the terminal connection numbers and terminal bandwidth data to obtain the internal and external network concurrency data of each site server within a specified time range, including: Pre-tagging the site servers according to the regions where the site servers are located, and the tags are used to determine that the category of the site server is an internal network server or an external network server; Within a specified time range, at fixed time intervals, summing the concurrency data of each site server tagged as an internal network server at the same moment to obtain the internal network concurrency data at that moment; Within a specified time range, at fixed time intervals, summing the concurrency data of each site server tagged as an external network server at the same moment to obtain the external network concurrency data at that moment.

4. The method according to claim 1, wherein The internal and external network concurrency data also includes H.323 conference participation concurrency data.

5. The method according to claim 1, wherein Comparing the internal and external network concurrency data of each site server within a specified time range with a predefined concurrency data threshold range, and adjusting the capacity of the cloud video conferencing system according to the comparison result, including: At a predetermined period, comparing the maximum value of the internal and external network concurrency data of each site server within a specified time range with the warning threshold, the expansion threshold, and the reduction threshold; If the maximum value of the internal and external network concurrency data of each site server within a specified time range reaches the warning threshold for consecutive multiple periods, a warning is issued; If the maximum value of the internal and external network concurrency data of each site server within a specified time range reaches the expansion threshold for consecutive multiple periods, the cloud video conferencing system is expanded according to the difference between the maximum value of the internal and external network concurrency data and the expansion threshold; If the maximum value of the internal and external network concurrency data of each site server within a specified time range reaches the reduction threshold for consecutive multiple periods, the cloud video conferencing system is reduced according to the difference between the maximum value of the internal and external network concurrency data and the reduction threshold.

6. The method according to claim 1, wherein The concurrency data threshold range is predefined according to the CPU memory usage rate of each site server in the cloud video conferencing system.

7. A device for dynamically adjusting the capacity of a cloud video conferencing system, characterized in that, Including: A data collection module for collecting the terminal connection numbers and terminal bandwidth data borne by each site server in the cloud video conferencing system; Each site server includes a media server, a recording server, and a converged media server; A data statistics module for analyzing the terminal connection numbers and terminal bandwidth data to obtain the internal and external network concurrency data of each site server within a specified time range; The concurrent data of the internal and external networks includes the concurrent data of participants and the concurrent data of recording. The data analysis module is used to compare the concurrent data of the internal and external networks of each site server within a specified time range with the predefined concurrent data threshold range, and adjust the capacity of the cloud video conferencing system according to the comparison result. The concurrent data threshold range includes: warning threshold, capacity expansion threshold, and capacity reduction threshold.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the method described in any one of claims 1-6 is implemented.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the method described in any one of claims 1-6 is implemented.

10. A computer program product, characterized in that, The computer program product includes a computer program, and when the computer program is executed by the processor, the method described in any one of claims 1-6 is implemented.

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