CN117349037B - Method, device, computer equipment and storage medium for eliminating interference in off-line application - Google Patents

Method, device, computer equipment and storage medium for eliminating interference in off-line application Download PDF

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Publication number
CN117349037B
CN117349037B CN202311660743.7A CN202311660743A CN117349037B CN 117349037 B CN117349037 B CN 117349037B CN 202311660743 A CN202311660743 A CN 202311660743A CN 117349037 B CN117349037 B CN 117349037B
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application
interfered
cpu
utilization rate
interference
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CN117349037A (en
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徐敏贤
宋盛叶
叶可江
高瑞鸿
须成忠
张佐玮
曾凡松
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Shenzhen Institute of Advanced Technology of CAS
Alibaba Cloud Computing Ltd
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Shenzhen Institute of Advanced Technology of CAS
Alibaba Cloud Computing Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/5038—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the execution order of a plurality of tasks, e.g. taking priority or time dependency constraints into consideration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/60—Software deployment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • G06F9/45533—Hypervisors; Virtual machine monitors
    • G06F9/45558—Hypervisor-specific management and integration aspects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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  • Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Memory System Of A Hierarchy Structure (AREA)

Abstract

The application relates to an off-line application interference elimination method, an off-line application interference elimination device, computer equipment and a storage medium. The method comprises the following steps: acquiring multi-level index data in a system and acquiring interfered application; judging the interference type of the interfered application according to the multi-level index data, screening out N offline applications with highest cache utilization rate if the interference type is a cache miss type, and performing static suppression on the cache utilization rate of the N offline applications with the highest cache utilization rate; if the CPU is in a contention class, N offline applications with highest CPU utilization rate and highest memory utilization rate in the system are acquired, a corresponding CPU suppression strategy is calculated by combining the priority level of the interfered application and the multi-level index data by utilizing an interference elimination algorithm, and the CPU utilization amounts of the N offline applications are dynamically suppressed according to the CPU suppression strategy. The application can improve the fitting degree of the interference elimination strategy and the actual situation, protect the success degree of interference elimination and maximize the throughput rate of off-line application.

Description

Method, device, computer equipment and storage medium for eliminating interference in off-line application
Technical Field
The application belongs to the technical field of cloud deployment, and particularly relates to a method and a device for eliminating interference in off-line application, computer equipment and a storage medium.
Background
In the conventional cloud-native application deployment mode, each application is typically deployed independently on a dedicated virtual machine or container, however, with the development of cloud computing technology and virtual container technology, the problem of low resource utilization also arises in the environment where the cloud-native application is deployed. The resource isolation of the bottom layer of the container is weaker than that of the traditional virtual machine, and interference caused by various resource contentions is unavoidable in mixed application. In addition, as the application scale increases, the number of virtual machines or containers increases rapidly, resulting in increased complexity of management and maintenance, and the application mix technology is emerging and rapidly developing.
The interference caused by resource contention under the cloud native application mix has a great influence on performance, the traditional interference elimination strategy generally adopts an adaptive process CPU resource limiting method, however, under the condition of coping with a mix cluster with complex and various workloads, the priorities of various applications are different under the condition of the cloud native environment mix, the CPU resource limiting method is difficult to cope with a mix scene with various types, the on-line performance of LS (on-line application) is seriously influenced, so that the user experience is influenced, even the SLO (service level objective) cannot be achieved, a series of indexes and thresholds are defined for measuring the requirements of various aspects such as response time, reliability and availability of services, and the scheduling time and resource consumption spent by the subsequent scheduling allocation CPUTIME for continuing the operation of the applications are still great when the resources required by the interference application are great and the operation is continuously limited.
Disclosure of Invention
The present application provides a method, apparatus, computer device and storage medium for off-line interference cancellation, which aims to solve at least one of the above technical problems in the prior art to a certain extent.
In order to solve the problems, the application provides the following technical scheme:
An offline application interference cancellation method, comprising:
Acquiring multi-level index data in a system and acquiring interfered application;
Judging the interference type of the interfered application according to the multi-level index data, if the interference type is a cache miss type, screening N offline applications with highest cache utilization rate from the system, and performing static compression on the cache utilization rate of the N offline applications with the highest cache utilization rate according to a set compression rate; in the case of a CPU contending class,
And acquiring the priority level of the interfered application, acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in the system, calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing the CPU utilization amount of the N offline applications according to the CPU suppression strategy.
The technical scheme adopted by the embodiment of the application further comprises the following steps: the multi-level index data in the acquisition system specifically comprises the following steps:
Acquiring multi-level index data of a system by using a performance detection tool, judging whether the system is interfered, and acquiring interfered application if the system is interfered; the multi-level index data at least comprises CPU utilization rate, CPI, cache utilization rate and memory utilization rate.
The technical scheme adopted by the embodiment of the application further comprises the following steps: the method for judging the interference type of the interfered application according to the multi-level index data comprises the following specific steps:
If the CPU utilization rate is obviously reduced and the reduction ratio reaches a first ratio threshold value or more, and the cache utilization rate is obviously increased and the rising ratio reaches the first ratio threshold value or more, judging that the interference type of the interfered application is a cache miss type;
And if the CPI has a peak and the stable rising proportion reaches a second proportion threshold value or more, judging that the interference type of the interfered application is CPU contention type.
The technical scheme adopted by the embodiment of the application further comprises the following steps: the method comprises the steps of screening N offline applications with highest cache utilization rate from the system, and performing static compression on the cache utilization rate of the N offline applications with highest cache utilization rate according to a set compression rate, wherein the method specifically comprises the following steps:
assume that the N value is 3, and the cache utilization rates of 3 interfered applications are in turn The suppression ratios for the 3 interfered applications are in turn:
The technical scheme adopted by the embodiment of the application further comprises the following steps: after the acquiring the priority level of the interfered application, the method further comprises:
And marking the interfered application with the priority level higher than the set threshold as an LSE application, wherein the LSE application represents an exclusive online application which needs to be processed in time.
The technical scheme adopted by the embodiment of the application further comprises the following steps: the method comprises the steps of calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing CPU utilization amounts of the N offline applications according to the CPU suppression strategy, wherein the method comprises the following specific steps:
Acquiring a normal CPI index and a current abnormal CPI index when the system is not interfered;
acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in a system;
comparing the normal CPI index with the abnormal CPI index, judging whether a counter is 2, if the counter is 2, performing static compression on the CPU utilization amounts of the N offline applications according to the set compression proportion; otherwise, judging whether the interfered application is an LSE application or not, if so, performing static compression on CPU utilization amounts of the N offline applications according to the set compression proportion; otherwise the first set of parameters is selected,
Acquiring the priority level of the interfered application, and calculating CPU utilization rate thresholds acceptable by the N offline applications according to the priority level, the current abnormal CPI index and the CPU utilization rate of the interfered application;
Calculating respective corresponding compression level indexes of N offline applications according to the CPU utilization rate threshold, the current abnormal CPI index and the normal CPI index, and dynamically compressing the CPU utilization amounts of the N offline applications according to the compression level indexes;
Judging whether system interference is eliminated, if so, resetting the counter to zero, and ending the interference elimination algorithm; otherwise, let the counter count+1 and re-execute the interference cancellation algorithm.
The technical scheme adopted by the embodiment of the application further comprises the following steps: the calculation formula of the CPU utilization threshold limit (CPU) is as follows:
[
Wherein the method comprises the steps of For the total CPU utilization in the current system,/>To the amount of CPU utilization for the interfered application,A total amount of CPU that is allocatable in the system;
The compression level index The calculation formula is as follows:
wherein app1, app2, app3 represent N offline applications with highest CPU utilization and memory utilization respectively, 、、/>The compression level index of the CPU compression process for the interfered offline applications app1, app2, app3,Representing normal CPI index,/>Representing the current abnormal CPI index,/>R (app 1), r (app 2), r (app 3) are the CPU utilization of the interfered offline applications app1, app2, app3, respectively,The cumulative distribution function of the normal distribution is finally calculated according to (1-/>) The CPU utilization of the offline applications app1, app2, app3 is dynamically throttled until interference is eliminated.
The embodiment of the application adopts another technical scheme that: an apparatus for off-line application interference cancellation, comprising:
And a data acquisition module: the method comprises the steps of acquiring multi-level index data in a system and acquiring interfered application;
and an interference type judging module: the interference type is used for judging the interference type of the interfered application according to the multi-level index data, and the interference type comprises a cache miss type and a CPU contention type;
A first interference cancellation module: when the interference type is a cache miss type, screening N offline applications with highest cache utilization rate from the system, and performing static suppression on the cache utilization rate of the offline applications with the highest cache utilization rate according to a set suppression rate;
A second interference cancellation module: and when the interference type is CPU contention type, acquiring the priority level of the interfered application, acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in the system, calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing the CPU utilization quantity of the N offline applications according to the CPU suppression strategy.
The embodiment of the application adopts the following technical scheme: a computer device comprising a processor, a memory coupled to the processor, wherein,
The memory stores program instructions for implementing the off-line application interference cancellation method;
the processor is configured to execute the program instructions stored by the memory to control the application of the interference cancellation method offline.
The embodiment of the application adopts the following technical scheme: a storage medium storing program instructions executable by a processor for performing the on-line application interference cancellation method.
Compared with the prior art, the embodiment of the application has the beneficial effects that: according to the method, the device, the computer equipment and the storage medium for eliminating the interference in the off-line application, the use condition of the cloud primary environment resource and the real-time analysis of the environment are combined, when the interference is detected, the priority level and CPI of the application are considered into a CPU suppression policy, and the CPU suppression policy is dynamically calculated based on the priority level of the application so as to achieve the purpose of eliminating the interference. Compared with the prior art, the embodiment of the application has at least the following beneficial effects:
1. The dynamic compression strategy is used for compressing the offline application instead of the static compression strategy, so that the fitting degree of the interference elimination strategy and the actual situation can be improved, the success degree of interference elimination is protected, and the throughput rate of the offline application is maximized.
2. The priority level of the online application is introduced during interference elimination, the online applications with different priority levels are subjected to interference elimination in different modes, the suppression level can be increased, so that the interference is eliminated at the fastest speed, the normal operation of the real-time application is ensured, the highest efficiency of the real-time application is ensured, and the rescheduling expenditure is reduced.
3. CPI is introduced when interference elimination is carried out on general-level online application, static compression indexes are changed into dynamic indexes capable of being changed dynamically, the dynamic indexes are more consistent with actual interference conditions, more accurate processing can be carried out on the interference conditions in a deeper way, and when the offline application is compressed, the CPU utilization amount of the offline application can be protected according to different maximum possibility of the interference conditions, so that the throughput of the offline application is maintained as much as possible while the interference is solved, the resources of the whole system are more fully utilized, and the utilization rate of a welcome mixing part is improved.
Drawings
FIG. 1 is a flow chart of an embodiment of the application for off-line application of an interference cancellation method;
FIG. 2 is a schematic diagram of an implementation of an interference cancellation algorithm according to an embodiment of the present application;
Fig. 3 is a schematic structural diagram of an interference cancellation device applied offline according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a computer device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a storage medium according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terms "first," "second," "third," and the like in this disclosure are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first", "a second", and "a third" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise. All directional indications (such as up, down, left, right, front, back … …) in the embodiments of the present application are merely used to explain the relative positional relationship, movement, etc. between the components in a particular gesture (as shown in the drawings), and if the particular gesture changes, the directional indication changes accordingly. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or computer apparatus that comprises a list of steps or elements is not limited to the list of steps or elements but may, in the alternative, include steps or elements not expressly listed or inherent to such process, method, article, or computer apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
Referring to fig. 1, a flowchart of an interference cancellation method applied offline is shown in an embodiment of the present application. The method for eliminating the interference in the off-line application of the second embodiment of the application comprises the following steps:
s100: collecting multi-level index data of the system by using a performance detection tool, judging whether the system has interference, and executing S110 if the system has interference;
In this step, the performance detection tools used include, but are not limited to, perf (acronym for performance), and the collected multi-level index data includes, but is not limited to, CPU utilization, CPI (Cycle Per Instructions, instruction cycle number), cache miss rate, cache utilization, memory utilization, dTLB-load-misses (data page table miss rate), ilb-load-misses (instruction page table miss rate), block_bio_bound (memory rebound rate in the linux system), block_bio_complete (I/O operation completion rate in the linux system), and the like.
S110: acquiring the interfered application, judging the interference type of the interfered application according to the multi-level index data, and executing S120 if the type is the cache miss type; if the CPU contends for the class, S130 is executed;
In this step, the interference type determination method specifically includes: if the CPU utilization rate is obviously reduced and the reduction ratio reaches a first ratio threshold value or more, the cache utilization rate is obviously increased and the rising ratio reaches the first ratio threshold value or more, judging that the interference type of the interfered application is a cache miss type; if the CPI has a peak and the steadily increasing proportion reaches a second proportion threshold value or above, the interference type of the interfered application is judged to be CPU contention type. The first proportion threshold is 20%, the second proportion threshold is 50%, and the specific proportion value can be set according to an actual application scene.
S120, screening N offline applications with highest cache utilization rate from the system, and performing static compression on the cache utilization rate of the N offline applications with highest cache utilization rate according to the set compression rate;
In this step, it is assumed that the N value is 3, that is, 3 interfered applications with highest cache utilization rate are screened from the system, and the cache utilization rates of the 3 interfered applications are sequentially The suppression ratios set for the 3 interfered applications are in turn:
（1）
（2）
（3）
And respectively carrying out static suppression on the buffer utilization rates of the 3 interfered applications according to the calculated suppression rate, and eliminating system interference.
S130: acquiring the priority level of the interfered application, and marking the interfered application with the priority level higher than a set threshold value as an LSE application which needs to be processed in time;
In the embodiment of the application, when the CPU contention-type interference of the system is detected, the interfered application with the priority level higher than the set threshold is marked as the LSE application, and the utilization rate of the offline application is standardized so as to map the data of different indexes to the similar scale, thereby avoiding unreasonable influence of certain index data on the result. The set threshold is 100, and the specific value can be set according to the actual application scenario.
S140: calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and the multi-level index data through an interference elimination algorithm, and dynamically suppressing the CPU utilization amount of the offline application according to the CPU suppression strategy until system interference is eliminated;
in this step, please refer to fig. 2, which is a schematic diagram illustrating an execution process of the interference cancellation algorithm according to an embodiment of the present application. The specific implementation process of the interference cancellation algorithm comprises the following steps:
S141: acquiring a normal CPI index and a current abnormal CPI index when the system is not interfered;
S142: acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in a system, and arranging the N offline applications into apps 1,2 and 3 from high to low according to the CPU utilization rate;
s143: comparing the normal CPI index with the abnormal CPI index, judging whether the counter count is 2, and executing S144 if the counter count is 2; otherwise, executing S145;
And if the system interference problem is not solved by the two interference elimination algorithms, the N offline applications are destroyed by direct marketing in the third interference elimination algorithm, so that the performance of the online applications is ensured and the resource consumption for eliminating the interference is reduced.
S144: static pressing is carried out on CPU utilization amounts of the N offline applications according to the set pressing proportion;
Wherein, the pressing proportion is 50%, which can be set according to the actual application scene;
s145: judging whether the interfered application is an LSE application or not, and executing S144 if the interfered application is the LSE application; otherwise, executing S146;
The LSE application is an online application which reserves resources to obtain better certainty, and in order to protect the priority scheduling of the LSE application, a static pressing strategy is directly adopted in the embodiment of the application.
S146: acquiring the priority level of the interfered application, and calculating CPU utilization rate thresholds acceptable by N offline applications according to the priority level, the current abnormal CPI index and the CPU utilization rate of the interfered application;
the calculation formula of the CPU utilization threshold limit (CPU) is as follows:
[（4）
Wherein, therein For the total CPU utilization in the current system,/>CPU utilization for disturbed applications,/>For the total amount of CPU that can be allocated in the system, the CPU utilization threshold can be used to calculate the throttle level index for N offline applications.
S147: calculating respective corresponding compression level indexes of N offline applications according to the CPU utilization threshold, the current abnormal CPI index and the normal CPI index, and dynamically compressing CPU utilization of the N offline applications according to the compression level indexes;
Wherein, the compression level index The calculation formula is as follows:
（5）
（6）
（7）
wherein, 、/>、/>Compression level index for CPU compression processing of offline applications app1, app2, app3,/>, respectivelyRepresenting normal CPI index,/>Representing the current abnormal CPI index,/>R (app 1), r (app 2), r (app 3) are the CPU utilization of the offline applications app1, app2, app3, respectively,The cumulative distribution function of the normal distribution is finally calculated according to (1-/>) The CPU utilization of the offline applications app1, app2, app3 is dynamically throttled until interference is eliminated.
S148: judging whether the system interference is eliminated, if so, executing S149; otherwise, executing S150;
s149: resetting the counter to zero, and ending the interference elimination algorithm;
s150: let the counter count+1 and re-execute S141.
Based on the above, the method for eliminating the interference in the offline application combines the use condition of the cloud primary environment resource with the real-time analysis of the environment, considers the priority level and CPI of the application into the CPU suppression policy when the interference is detected, and dynamically calculates the CPU suppression policy based on the priority level of the application so as to achieve the purpose of eliminating the interference. Compared with the prior art, the embodiment of the application has at least the following beneficial effects:
1. The dynamic compression strategy is used for compressing the offline application instead of the static compression strategy, so that the fitting degree of the interference elimination strategy and the actual situation can be improved, the success degree of interference elimination is protected, and the throughput rate of the offline application is maximized.
2. The priority level of the online application is introduced during interference elimination, the online applications with different priority levels are subjected to interference elimination in different modes, the suppression level can be increased, so that the interference is eliminated at the fastest speed, the normal operation of the real-time application is ensured, the highest efficiency of the real-time application is ensured, and the rescheduling expenditure is reduced.
3. CPI is introduced when interference elimination is carried out on general-level online application, static compression indexes are changed into dynamic indexes capable of being changed dynamically, the dynamic indexes are more consistent with actual interference conditions, more accurate processing can be carried out on the interference conditions in a deeper way, and when the offline application is compressed, the CPU utilization amount of the offline application can be protected according to different maximum possibility of the interference conditions, so that the throughput of the offline application is maintained as much as possible while the interference is solved, the resources of the whole system are more fully utilized, and the utilization rate of a welcome mixing part is improved.
Fig. 3 is a schematic structural diagram of an interference cancellation device applied offline according to an embodiment of the application. The device 40 for off-line application interference cancellation according to the embodiment of the present application includes:
data acquisition module 41: the method comprises the steps of acquiring multi-level index data in a system and acquiring interfered application;
Interference type judgment module 42: the interference type is used for judging the interference type of the interfered application according to the multi-level index data, and the interference type comprises a cache miss type and a CPU contention type;
The first interference cancellation module 43: when the interference type is a cache miss type, screening N offline applications with highest cache utilization rate from the system, and performing static suppression on the cache utilization rate of the offline applications with the highest cache utilization rate according to a set suppression rate;
The second interference cancellation module 44: and when the interference type is CPU contention type, acquiring the priority level of the interfered application, acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in the system, calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing the CPU utilization quantity of the N offline applications according to the CPU suppression strategy.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein.
The device provided by the embodiment of the present application may be applied to the foregoing method embodiment, and details refer to the description of the foregoing method embodiment, which is not repeated herein.
Fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the application. The computer device 50 includes:
a memory 51 storing executable program instructions;
a processor 52 connected to the memory 51;
The processor 52 is configured to call the executable program instructions stored in the memory 51 and perform the steps of: acquiring multi-level index data in a system and acquiring interfered application; judging the interference type of the interfered application according to the multi-level index data, if the interference type is a cache miss type, screening N offline applications with highest cache utilization rate from the system, and performing static compression on the cache utilization rate of the N offline applications with the highest cache utilization rate according to a set compression rate; if the CPU is in a contention class, acquiring the priority level of the interfered application, acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in the system, calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing the CPU utilization quantity of the N offline applications according to the CPU suppression strategy.
The processor 52 may also be referred to as a CPU (Central Processing Unit ). The processor 52 may be an integrated circuit chip having signal processing capabilities. Processor 52 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Fig. 5 is a schematic structural diagram of a storage medium according to an embodiment of the application. The storage medium of the embodiment of the present application stores program instructions 61 capable of implementing the steps of: acquiring multi-level index data in a system and acquiring interfered application; judging the interference type of the interfered application according to the multi-level index data, if the interference type is a cache miss type, screening N offline applications with highest cache utilization rate from the system, and performing static compression on the cache utilization rate of the N offline applications with the highest cache utilization rate according to a set compression rate; if the CPU is in a contention class, acquiring the priority level of the interfered application, acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in the system, calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing the CPU utilization quantity of the N offline applications according to the CPU suppression strategy. The program instructions 61 may be stored in the storage media mentioned above in the form of a software product, and include several instructions for making a computer device (which may be a personal computer, a server, or a network computer device, etc.) or a processor (processor) execute all or part of the steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program instructions, or a terminal computer device such as a computer, a server, a mobile phone, a tablet, or the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the system embodiments described above are merely illustrative, e.g., the partitioning of elements is merely a logical functional partitioning, and there may be additional partitioning in actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not implemented. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units. The foregoing is only the embodiments of the present application, and therefore, the patent scope of the application is not limited thereto, and all equivalent structures or equivalent processes using the descriptions of the present application and the accompanying drawings, or direct or indirect application in other related technical fields, are included in the scope of the application.

Claims (4)

1. An offline application interference cancellation method, comprising:
Acquiring multi-level index data in a system and acquiring interfered application;
Judging the interference type of the interfered application according to the multi-level index data, if the interference type is a cache miss type, screening N offline applications with highest cache utilization rate from the system, and performing static compression on the cache utilization rate of the N offline applications with the highest cache utilization rate according to a set compression rate, wherein N=3; in the case of a CPU contending class,
Acquiring the priority level of the interfered application, acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in a system, calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing the CPU utilization amount of the N offline applications according to the CPU suppression strategy; wherein:
the method for judging the interference type of the interfered application according to the multi-level index data comprises the following specific steps:
If the CPU utilization rate is obviously reduced and the reduction ratio reaches a first ratio threshold value or more, and the cache utilization rate is obviously increased and the rising ratio reaches the first ratio threshold value or more, judging that the interference type of the interfered application is a cache miss type;
If the CPI has a peak and the stable rising proportion reaches a second proportion threshold value or more, judging that the interference type of the interfered application is a CPU contention type;
The method comprises the steps of screening N offline applications with highest cache utilization rate from the system, and performing static compression on the cache utilization rate of the N offline applications with highest cache utilization rate according to a set compression rate, wherein N=3 specifically comprises the following steps:
the buffer utilization rate of 3 interfered applications is in turn as follows The suppression ratios for the 3 interfered applications are in turn:
；
after the acquiring the priority level of the interfered application, the method further comprises:
marking the interfered application with the priority level higher than a set threshold as an LSE application, wherein the LSE application represents an exclusive online application which needs to be processed in time;
the method comprises the steps of calculating a corresponding CPU suppression strategy by combining the priority level of the interfered application and multi-level index data by using an interference elimination algorithm, and dynamically suppressing CPU utilization amounts of the N offline applications according to the CPU suppression strategy, wherein the method comprises the following specific steps:
Acquiring a normal CPI index and a current abnormal CPI index when the system is not interfered;
acquiring N offline applications with highest CPU utilization rate and highest memory utilization rate in a system;
Comparing the normal CPI index with the abnormal CPI index, judging whether a counter is 2, and if the counter is 2, performing static compression on CPU utilization amounts of the N offline applications according to a set compression ratio; otherwise, judging whether the interfered application is an LSE application or not, if so, performing static compression on CPU utilization amounts of the N offline applications according to the set compression proportion; otherwise the first set of parameters is selected,
Acquiring the priority level of the interfered application, and calculating CPU utilization rate thresholds acceptable by the N offline applications according to the priority level, the current abnormal CPI index and the CPU utilization rate of the interfered application;
Calculating respective corresponding compression level indexes of N offline applications according to the CPU utilization rate threshold, the current abnormal CPI index and the normal CPI index, and dynamically compressing the CPU utilization amounts of the N offline applications according to the compression level indexes;
judging whether system interference is eliminated, if so, resetting the counter to zero, and ending the interference elimination algorithm; otherwise, the counter count is increased by 1, and the interference elimination algorithm is re-executed;
the calculation formula of the CPU utilization threshold limit (CPU) is as follows:
Wherein the method comprises the steps of For the total CPU utilization in the current system,/>CPU utilization for disturbed applications,/>A total amount of CPU that is allocatable in the system;
the compression level index calculation formula is as follows:
wherein app1, app2, app3 represent 3 offline applications with highest CPU utilization and memory utilization respectively, 、/>、Compression level index for CPU compression processing of interfered offline applications app1, app2, app3,/>, respectivelyRepresenting normal CPI index,/>Representing the current abnormal CPI index,/>R (app 1), r (app 2), r (app 3) are the CPU utilization of the interfered offline applications app1, app2, app3, respectively,As a cumulative distribution function of normal distribution, finally according to (1-/>)、(1-/>)、(1-/>) The CPU utilization of the offline applications app1, app2, app3 are dynamically suppressed, respectively, until interference cancellation.
2. The method for eliminating interference in offline application according to claim 1, wherein the multi-level index data in the acquisition system is specifically:
Acquiring multi-level index data of a system by using a performance detection tool, judging whether the system is interfered, and acquiring interfered application if the system is interfered; the multi-level index data at least comprises CPU utilization rate, CPI, cache utilization rate and memory utilization rate.
3. A computer device comprising a processor, a memory coupled to the processor, wherein,
The memory storing program instructions for implementing the method for off-line application of interference cancellation according to any one of claims 1-2;
the processor is configured to execute the program instructions stored by the memory to control the application of the interference cancellation method offline.
4. A storage medium storing program instructions executable by a processor for performing the method of applying interference cancellation offline according to any one of claims 1 to 2.
CN202311660743.7A 2023-12-06 2023-12-06 Method, device, computer equipment and storage medium for eliminating interference in off-line application Active CN117349037B (en)

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023035750A1 (en) * 2021-09-08 2023-03-16 中国电信股份有限公司 Method and apparatus for interference optimization, storage medium, and electronic device
CN117032977A (en) * 2023-08-18 2023-11-10 中国科学院深圳先进技术研究院 Mixed part application resource allocation method and device, computer equipment and storage medium

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023035750A1 (en) * 2021-09-08 2023-03-16 中国电信股份有限公司 Method and apparatus for interference optimization, storage medium, and electronic device
CN117032977A (en) * 2023-08-18 2023-11-10 中国科学院深圳先进技术研究院 Mixed part application resource allocation method and device, computer equipment and storage medium

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