Method for monitoring whether cloud desktop application program is in idle state or not

Abstract

The invention relates to the field of cloud desktops, in particular to a method for monitoring whether a cloud desktop application program is in an idle state, and the method comprises the steps: obtaining standard data which can be used for accurately judging whether the application program is in the idle state or not through an early-stage calibration test, and taking the standard data as a software idle judgment threshold value; and the software idle judgment threshold value is utilized to accurately capture the use dynamic state of the application program in the later monitoring process, and the idle time and the effective use time of the application software are accurately distinguished.

Description

Technical Field

[0001] The present invention relates to the field of cloud desktops, and in particular to a method for monitoring whether a cloud desktop application is in an idle state. Background Art

[0002] Cloud desktop is a virtual desktop service based on cloud computing technology. It hosts the user's desktop environment (including operating system, applications, user data, etc.) on a remote server, and synchronizes the desktop image and operation instructions to the user's terminal device in real time through network transmission, so that users can remotely access and operate their desktop environment just like using a local desktop. In other words, cloud desktop, a desktop virtualization method, is a new model to replace traditional computers. After using cloud desktop, users no longer need to buy computer hosts. The CPU, memory, hard disk and other components contained in the host are all virtualized in the back-end server. After installing the client, users access the virtual machine host on the back-end server through a unique communication protocol to achieve interactive operations, achieving the same experience as a computer.

[0003] At present, cloud desktops are now widely used by various companies in production to save a lot of costs for purchasing physical computer host accessories. However, cloud desktop applications are usually paid software that is paid by usage time. Enterprise managers have found that many staff members are often busy with work. When they open paid software on the cloud desktop to work, they easily forget to close the paid software and leave their jobs to handle other matters (the paid software is still charged by time at this time). Such a situation will cause great cost waste for the company.

[0004] Usually, there are many employees in an enterprise, and managers cannot manually check whether these paid software are idle one by one. Therefore, how to allow managers to easily determine whether cloud desktop applications are idle has always been a problem that technical personnel in this field need to solve urgently. Summary of the invention

[0005] The purpose of the present invention is to address the corresponding deficiencies in the prior art and provide a method for monitoring whether a cloud desktop application is in an idle state. Through preliminary calibration tests, a standard data that can be used to accurately determine whether an application is in an idle state is obtained as a software idle judgment threshold. The software idle judgment threshold is used to accurately capture the application usage dynamics in the subsequent monitoring process, and accurately distinguish the idle time and effective use time of the application software.

[0006] The object of the present invention is to adopt the following scheme to achieve: a method for monitoring whether a cloud desktop application is in an idle state, comprising the following steps:

[0007] 1) When the staff is not using the cloud desktop, open the application that needs to be monitored on the cloud desktop, keep the application in an idle state, calculate the average CPU occupancy rate of the application during the survival time, and use the average CPU occupancy rate as the software idle judgment threshold;

[0008] 2) Setting a monitoring cycle, when the staff uses the application to work, continuously collects the real-time CPU occupancy rate during the application's survival time according to the monitoring cycle and stores it in the database;

[0009] 3) respectively comparing the real-time CPU occupancy rates of the plurality of CPUs collected in step 2) with the software idle judgment threshold to determine whether the application is in an idle period in each monitoring cycle;

[0010] 4) Repeat step 3) until all CPU real-time occupancy rates in step 2) are compared with the software idle judgment threshold, and calculate the effective usage time of the application according to the following formula:

[0011] Effective use time = effective use times × monitoring cycle;

[0012] 5) Output report.

[0013] Preferably, in step 3), the specific method of determining whether the application is in an idle period in each monitoring cycle is as follows:

[0014] 3-1) If the real-time occupancy rate of any CPU is greater than the software idle judgment threshold, the application is not in the idle period at that moment, and the number of valid usages of the application is automatically increased;

[0015] 3-2) If the real-time occupancy rate of any CPU is less than or equal to the software idle judgment threshold, the application is in an idle period at that moment.

[0016] Preferably, the monitoring period is 5 to 6 seconds.

[0017] Preferably, in step 1), the average CPU occupancy of the application during the survival time is calculated in the following manner:

[0018] 1-1) Collect the real-time CPU occupancy rate at several moments during the life of the application;

[0019] 1-2) Calculate the average CPU usage of the application during its survival time as follows:

[0020] The sum of the CPU real-time occupancy rates collected in step 1-1) is divided by the number of times the CPU real-time occupancy rates are collected.

[0021] Preferably, a collection times threshold is set, and in step 1-1), the collection times of the real-time CPU occupancy rate is equal to the collection times threshold.

[0022] Preferably, the collection times threshold is 10,000 to 20,000 times.

[0023] Preferably, a data monitoring and collection module is provided, and the real-time CPU occupancy rate is collected in real time by the data monitoring and collection module.

[0024] Preferably, a data statistical analysis module is provided, and the report is obtained by real-time analysis by the data statistical analysis module.

[0025] Preferably, the report includes idle time of the cloud desktop application.

[0026] The beneficial effects of the present invention are as follows:

[0027] Preferably, the monitoring period is 5 to 6 seconds. An appropriate monitoring period can accurately capture the application usage dynamics without occupying too much system resources, so as to ensure the accuracy of the subsequent monitoring process.

[0028] Preferably, the collection times threshold is 10,000 to 20,000 times, so as to ensure the correct calculation of the average CPU occupancy rate of the application during the survival time in the early calibration test, and obtain a standard data that can be used to accurately determine whether the application is in an idle state. Theoretically, the higher the collection times threshold, the more accurate the standard data will be, but since the actual calibration efficiency must be taken into consideration, the collection times threshold needs to be set within an appropriate range.

[0029] The advantage of the present invention is that, through preliminary calibration tests, the present invention obtains a standard data that can be used to accurately determine whether an application is in an idle state, which is used as a software idle judgment threshold. The software idle judgment threshold is used in the subsequent monitoring process to accurately capture the application usage dynamics and accurately distinguish the idle time and effective use time of the application software.

[0030] Glossary

[0031] Effective usage time: the time that staff members normally use cloud desktop applications to work.

[0032] The survival time of an application program refers to the time period from the start time to the end time of an application program when the application program is in an active state rather than a terminated state during operation.

[0033] Start time: refers to the moment when an application enters the active state during operation.

[0034] End time: refers to the moment when an application enters the termination state during operation.

[0035] Idle period: refers to the period of time when the software is idle and not actually used after it is opened. It emphasizes that the software is in an idle state without functioning, just like an item is put aside and not used. For example: after the software is opened, there is a long period of idle time without any operation. At this time, the software can be said to be in an idle state. In the present invention, the idle period of the application is the ineffective working time of the staff.

[0036] Invalid working time: The period of time during which the staff does not perform normal work in front of the computer after opening the cloud desktop application. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of the present invention;

[0038] Figure 2 It is a schematic diagram of the principle of an embodiment of the present invention. DETAILED DESCRIPTION

[0039] like Figure 1 to Figure 2 As shown, a data monitoring and collection module and a data statistical analysis module are set in the cloud desktop to be monitored. As an embodiment, a method for monitoring whether a cloud desktop application is in an idle state includes the following steps:

[0040] 1) When the staff is not using the cloud desktop, open the application to be monitored on the cloud desktop and keep the application in an idle state. Calculate the average CPU usage of the application during the survival time in the following way and use the average CPU usage as the software idle judgment threshold:

[0041] 1-1) The collection times threshold is usually 10,000 to 20,000 times. In this embodiment, the collection times threshold is set to 10,000 times, that is, the data monitoring and collection module needs to collect the real-time CPU occupancy rate 10,000 times during the life of the application;

[0042] 1-2) The data statistics analysis module calculates the average CPU usage of the application during its survival time in the following way:

[0043] The data statistics analysis module adds up the real-time CPU occupancy rates collected by the data monitoring and collection module in step 1-1) and divides the sum by the number of collection times of the real-time CPU occupancy rates, that is:

[0044] Average CPU usage = sum of real-time CPU usage / number of collection times;

[0045] 2) The monitoring period is usually 5 to 6 seconds. In this embodiment, the monitoring period is 6 seconds, that is, when the staff uses the application to work, the data monitoring and collection module collects the real-time CPU occupancy rate of the application every 6 seconds and stores it in the database;

[0046] It is worth noting that in order to ensure long-term monitoring of cloud desktop applications, the real-time CPU usage rate is usually continuously collected during the application's survival time and compared with the software idle judgment threshold until the application is closed and in a terminated state. The standard for judging whether an application is alive is usually whether all threads of the application are alive. If any thread of the application is alive, the application is alive. Conversely, if all threads of the application are terminated, the application is in a terminated state.

[0047] 3) The data statistical analysis module compares the real-time occupancy rates of multiple CPUs collected in step 2) with the software idle judgment threshold, and determines whether the application is in an idle period in each monitoring cycle in the following manner;

[0048] 3-1) If the real-time occupancy rate of any CPU is greater than the software idle judgment threshold, the application is not in the idle period at that moment, and the number of valid usages of the application is incremented (i.e., 1 is added to the original value);

[0049] 3-2) If the real-time occupancy rate of any CPU is less than or equal to the software idle judgment threshold, the application is in an idle period at that moment;

[0050] 4) Repeat step 3) until all CPU real-time occupancy rates in step 2) are compared with the software idle judgment threshold, and calculate the effective usage time of the application according to the following formula:

[0051] Effective use time = effective use times × monitoring cycle;

[0052] Usually, this step calculates the effective use time of the application within the survival time, and the idle time of the application within the survival time can also be calculated from the survival time and the effective use time. Therefore, this embodiment can also set an alarm threshold. Once it is determined that the idle time of the application exceeds the alarm threshold (that is, the invalid working time is overtime), an idle alarm will be automatically issued to the manager to facilitate the manager to remind the staff to close the application in time (the manager can also directly close the application remotely, or the manager can force the idle account of the application to go offline) to avoid waste.

[0053] 5) The data statistical analysis module outputs a report, which at least includes the idle time of the cloud desktop application.

[0054] The cost of physical computer accessories and hosts that can smoothly run paid software such as design software and simulation software is relatively high. Enterprises use cloud desktops in production with the intention of saving the cost of purchasing these physical computers. However, since the staff did not close these paid software in time, these paid software generated a lot of idle time during work, which caused even greater waste.

[0055] Therefore, in this embodiment, a monitoring list can also be set up to enter all applications that need to be monitored in the cloud desktop into the monitoring list (usually paid software for monitoring the cloud desktop), and the above method can be used to determine whether these applications are idle for a long time. In this way, even if there are many staff members using the cloud desktop, managers can easily know the use of the cloud desktop of the entire enterprise through reports, so that managers can propose corrective measures in a timely manner, and ultimately reduce unnecessary expenses in a real sense.

[0056] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modification made to the present invention by those skilled in the art without departing from the spirit of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for monitoring whether a cloud desktop application is in an idle state, characterized in that: The following steps are involved: 1) When the staff is not using the cloud desktop, open the application that needs to be monitored on the cloud desktop, keep the application in an idle state, calculate the average CPU occupancy rate of the application during the survival time, and use the average CPU occupancy rate as the software idle judgment threshold; 2) Setting a monitoring cycle, when the staff uses the application to work, continuously collects the real-time CPU occupancy rate during the application's survival time according to the monitoring cycle and stores it in the database; 3) respectively comparing the real-time CPU occupancy rates of the plurality of CPUs collected in step 2) with the software idle judgment threshold to determine whether the application is in an idle period in each monitoring cycle; 4) Repeat step 3) until all CPU real-time occupancy rates in step 2) are compared with the software idle judgment threshold, and calculate the effective usage time of the application according to the following formula: Effective use time = effective use times × monitoring cycle; 5) Output report.

2. The method for monitoring whether a cloud desktop application is in an idle state according to claim 1, characterized in that: In step 3), the specific method of determining whether the application is in an idle period in each monitoring cycle is as follows: 3-1) If the real-time occupancy rate of any CPU is greater than the software idle judgment threshold, the application is not in the idle period at that moment, and the number of valid usages of the application is automatically increased; 3-2) If the real-time occupancy rate of any CPU is less than or equal to the software idle judgment threshold, the application is in an idle period at that moment.

3. The method for monitoring whether a cloud desktop application is in an idle state according to claim 1, characterized in that: The monitoring period is 5 to 6 seconds.

4. The method for monitoring whether a cloud desktop application is in an idle state according to claim 1, characterized in that: In step 1), the average CPU usage of the application during its survival time is calculated as follows: 1-1) Collect the real-time CPU occupancy rate at several moments during the life of the application; 1-2) Calculate the average CPU usage of the application during its survival time as follows: The sum of the CPU real-time occupancy rates collected in step 1-1) is divided by the number of times the CPU real-time occupancy rates are collected.

5. The method for monitoring whether a cloud desktop application is in an idle state according to claim 4, characterized in that: A collection times threshold is set. In step 1-1), the collection times of the real-time CPU occupancy rate is equal to the collection times threshold.

6. The method for monitoring whether a cloud desktop application is in an idle state according to claim 5, characterized in that: The collection times threshold is 10,000 to 20,000 times.

7. The method for monitoring whether a cloud desktop application is in an idle state according to claim 1, characterized in that: A data monitoring and collection module is set up, and the real-time CPU occupancy rate is collected in real time by the data monitoring and collection module.

8. The method for monitoring whether a cloud desktop application is in an idle state according to claim 1, characterized in that: A data statistics analysis module is provided, and the report is obtained by real-time analysis by the data statistics analysis module.

9. The method for monitoring whether a cloud desktop application is in an idle state according to claim 1 or 8, characterized in that: The report includes idle time of the cloud desktop application.

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