CN114237896A - Distributed node resource dynamic scheduling method and device - Google Patents
Distributed node resource dynamic scheduling method and device Download PDFInfo
- Publication number
- CN114237896A CN114237896A CN202111559888.9A CN202111559888A CN114237896A CN 114237896 A CN114237896 A CN 114237896A CN 202111559888 A CN202111559888 A CN 202111559888A CN 114237896 A CN114237896 A CN 114237896A
- Authority
- CN
- China
- Prior art keywords
- node
- distributed node
- resource domain
- distributed
- domain access
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- 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
- G06F9/505—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 load
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The embodiment of the application provides a method and a device for dynamically scheduling distributed node resources, which can be used in the field of finance, and the method comprises the following steps: acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access right and a running state resource domain access right; performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determining load time sequence data of each distributed node; determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy; the method and the device can effectively reduce the overhead of the redundant resources of the distributed system and improve the resource utilization rate of the distributed system.
Description
Technical Field
The application relates to the field of distributed technology, can also be used in the field of finance, and particularly relates to a distributed node resource dynamic scheduling method and device.
Background
With the popularization of the internet and the rapid growth of internet users, a distributed service system has become a mainstream architecture. Along with various major or business activities, the flow of a distributed system often has wave crests and wave troughs, for example, the flow is relatively average at ordinary times, the load pressure on system resources is small, and the flow is increased rapidly when activities such as major activities are met, at the moment, the load pressure of the system is large, for example, the timing task time of batch execution consumes the system resources when the task is executed, and the system resources are idle when the non-timing task time is executed; the distributed service system needs to maintain a redundant machine system resource throughout the year to deal with the consumption of flow resources such as burst or timing tasks.
Therefore, how to reduce the overhead of redundant system resources and improve the utilization rate of the system resources is a technical problem to be solved in the field.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a distributed node resource dynamic scheduling method and device, which can effectively reduce the overhead of distributed system redundant resources and improve the resource utilization rate of the distributed system.
In order to solve at least one of the above problems, the present application provides the following technical solutions:
in a first aspect, the present application provides a method for dynamically scheduling distributed node resources, including:
acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access right and a running state resource domain access right;
performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determining load time sequence data of each distributed node;
and determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
Further, before the acquiring application basic environment data and node service environment data in each distributed node according to a set time period, the method includes:
and determining corresponding keep-alive state resource domain access authority and running state resource domain access authority according to the maximum pre-estimated resource occupation scale and the minimum pre-estimated resource occupation scale of the application contained in each distributed node.
Further, the determining an operation state scheduling policy of each distributed node according to a numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access right and the operation state resource domain access right according to the operation state scheduling policy includes:
if the load time sequence data does not exceed the preset threshold, only configuring a keep-alive state resource domain access right for the distributed node in a set system resource domain, and adjusting a traffic load parameter of an upstream node to which the distributed node belongs, so that normal load traffic sent to the distributed node by the upstream node is reduced to be heartbeat traffic.
Further, the determining an operation state scheduling policy of each distributed node according to a numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access right and the operation state resource domain access right according to the operation state scheduling policy includes:
if the load time sequence data exceeds the preset threshold, only configuring an operating state resource domain access right for the distributed node in a set system resource domain, and adjusting a traffic load parameter of an upstream node to which the distributed node belongs, so that the heartbeat traffic sent by the upstream node to the distributed node is increased to be normal load traffic.
Further, the determining the operation state scheduling policy of each distributed node further includes:
if the service attribute of the service flow received by each distributed node belongs to a specific service attribute, configuring a running state resource domain access authority for the distributed node in a set system resource domain;
and if the service attribute of the service flow received by each distributed node belongs to the conventional service attribute, configuring the access authority of the keep-alive state resource domain for the distributed node in the set system resource domain.
Further, the performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension to determine load time sequence data of each distributed node includes:
and performing time sequence aggregation processing on the collected CPU occupation amount, the waiting queue length and the current node response time of each distributed node according to a set time dimension to obtain the corresponding CPU utilization rate, the thread pool availability rate, the node response success rate and the node response average time length.
In a second aspect, the present application provides a distributed node resource dynamic scheduling apparatus, including:
the node environment monitoring module is used for acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access authority and a running state resource domain access authority;
the node load determining module is used for performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension and determining load time sequence data of each distributed node;
and the node resource domain scheduling module is used for determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold value, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
In a third aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the steps of the distributed node resource dynamic scheduling method.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method for dynamically scheduling distributed node resources.
In a fifth aspect, the present application provides a computer program product comprising a computer program/instructions which, when executed by a processor, implement the steps of the method for dynamically scheduling distributed node resources.
According to the technical scheme, the application basic environment data and the node service environment data of each distributed node acquired in a set time period are subjected to time sequence aggregation processing according to a set time dimension, load time sequence data of each distributed node is determined, a corresponding running state scheduling strategy of each distributed node is determined, and the keep-alive state resource domain access right and the running state resource domain access right of each distributed node are configured according to the running state scheduling strategy, so that the redundant resource overhead of a distributed system can be effectively reduced, and the resource utilization rate of the distributed system is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a distributed node resource dynamic scheduling method in an embodiment of the present application;
fig. 2 is a second flowchart illustrating a method for dynamically scheduling distributed node resources according to an embodiment of the present application;
fig. 3 is a structural diagram of a distributed node resource dynamic scheduling apparatus in an embodiment of the present application;
fig. 4 is a schematic diagram of resource domains occupied by distributed nodes in an embodiment of the present application;
FIG. 5 is a schematic diagram of upstream node traffic distribution in an embodiment of the present application;
FIG. 6 is a diagram illustrating an overall system for dynamically scheduling resources according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In consideration of the problem that a distributed service system needs to maintain a redundant machine system resource throughout the year to deal with consumption of flow resources such as burst or timing tasks in the prior art, the application provides a distributed node resource dynamic scheduling method and a distributed node resource dynamic scheduling device.
In order to effectively reduce the overhead of redundant resources of a distributed system and improve the resource utilization rate of the distributed system, the present application provides an embodiment of a distributed node resource dynamic scheduling method, and referring to fig. 1, the distributed node resource dynamic scheduling method specifically includes the following contents:
step S101: acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access right and a running state resource domain access right.
It can be understood that, during the operation of the distributed service cluster, each distributed node occupies a certain resource domain, and a part of idle resource domains needs to be reserved for temporary capacity expansion of different services in the conventional capacity expansion situation in the prior art, which may cause resource waste, as shown in the left half schematic diagram of fig. 4.
Optionally, the method sets an access right of a keep-alive state resource domain and an access right of an operation state resource domain for each distributed node in the distributed service cluster, that is, a set resource domain in a system resource domain is set to be capable of performing access switching according to the access right of the keep-alive state resource domain and the access right of the operation state resource domain, that is, when the distributed node has the access right of the keep-alive state resource domain, the distributed node can access a small part of resource domains in the system resource domain, so that the distributed node can be in the keep-alive state with the lowest operation resource requirement; when the distributed node has the access right of the resource domain in the running state, the distributed node may access a majority of resource domains in the system resource domain, so that the distributed node can be in the running state according to the maximum running resource requirement, which is equivalent to performing capacity expansion of the resource domain on the distributed node, and the distributed node can effectively cope with the situation of traffic surge, see the right half schematic diagram of fig. 4.
Optionally, the application basic environment data and the node service environment data in each distributed node may be acquired according to a set time period, the set time period may be set manually, for example, every minute, and the acquisition operation may be implemented by an existing monitoring system, for example, by reporting the application basic environment data and the node service environment data to the monitoring system through a micro service exposed to the outside by a node.
Optionally, the application basic environment data is a basic operation environment of the application in the distributed node, such as CPU occupation amount, and the node service environment data is, for example, a waiting queue length, a current node response time, and the like.
Step S102: and performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determining load time sequence data of each distributed node.
Optionally, the application basic environment data and the node service environment data of each distributed node collected by the application basic environment data collection method may be subjected to time sequence aggregation processing periodically, that is, the data is converted into time sequence data based on a set time dimension (for example, every day), that is, the load time sequence data.
For example, the load time series data CPU utilization rate may be obtained according to the CPU occupancy in the set time dimension, and the load time series data thread pool availability rate, the node response success rate, and the node response average duration may be obtained according to the waiting queue length and the current node response time in the set time dimension, for example.
Step S103: and determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
Optionally, after the load time sequence data is determined, the load time sequence data may be compared with a preset threshold to determine whether the load time sequence data meets the switching condition of the resource domain.
In another possible embodiment of the present application, after the load time series data is determined, the load time series data may be subjected to comprehensive scoring, and a numerical comparison is performed according to a score and a score threshold to determine whether a switching condition of a resource domain is satisfied.
Optionally, if the load time series data does not exceed the preset threshold, that is, the traffic is not increased suddenly in the production environment at this time, in order to reduce system resource redundancy, the present application may only configure the access right of the keep-alive state resource domain for the distributed node in the set system resource domain, that is, the distributed node may access the small part of the idle resource domain set in the system resource domain to maintain normal operation of the distributed node, and at the same time, the present application may adjust the traffic load parameter of the upstream node to which the distributed node belongs, so that the normal load traffic sent by the upstream node to the distributed node is reduced to the heartbeat traffic, for example, referring to fig. 5, the upstream node only sends about 1% of the heartbeat traffic to the downstream distributed node, so as to ensure that the downstream node is alive.
Optionally, if the load time series data exceeds the preset threshold, that is, the flow is suddenly increased in the production environment at this time, in order to perform capacity expansion on the distributed node in time and ensure stable operation of the system, the present application may only configure an operation state resource domain access right for the distributed node in a set system resource domain, that is, the distributed node may access a majority of resource domains set in the system resource domain to perform capacity expansion, and adjust a flow load parameter of an upstream node to which the distributed node belongs, so that the heartbeat flow sent by the upstream node to the distributed node is increased to a normal load flow.
As can be seen from the above description, the distributed node resource dynamic scheduling method provided in this embodiment of the present application can perform time sequence aggregation processing on application basic environment data and node service environment data of each distributed node acquired in a set time period according to a set time dimension, determine load time sequence data of each distributed node, determine a corresponding operation state scheduling policy of each distributed node, and configure a keep-alive state resource domain access right and an operation state resource domain access right of each distributed node according to the operation state scheduling policy, thereby effectively reducing redundant resource overhead of a distributed system and improving resource utilization rate of the distributed system.
In order to flexibly cope with the traffic change of the production environment, in an embodiment of the distributed node resource dynamic scheduling method of the present application, before the step S101, the following may be specifically included:
and determining corresponding keep-alive state resource domain access authority and running state resource domain access authority according to the maximum pre-estimated resource occupation scale and the minimum pre-estimated resource occupation scale of the application contained in each distributed node.
Optionally, the application sets an access right of the keep-alive state resource domain and an access right of the running state resource domain for each distributed node in the distributed service cluster, that is, the set resource domain in the system resource domain is set to be capable of performing access switching according to the access right of the keep-alive state resource domain and the access right of the running state resource domain, and the resource domain amount corresponding to the access right of the keep-alive state resource domain and the access right of the running state resource domain can be determined by the maximum pre-estimated resource occupation scale and the minimum pre-estimated resource occupation scale of the application included in the distributed node.
In order to reduce the occupation of system redundant resources when the production environment has a small flow, in an embodiment of the distributed node resource dynamic scheduling method of the present application, the step S103 may further specifically include the following contents:
if the load time sequence data does not exceed the preset threshold, only configuring a keep-alive state resource domain access right for the distributed node in a set system resource domain, and adjusting a traffic load parameter of an upstream node to which the distributed node belongs, so that normal load traffic sent to the distributed node by the upstream node is reduced to be heartbeat traffic.
Optionally, if the load time series data does not exceed the preset threshold, that is, the traffic is not increased suddenly in the production environment at this time, in order to reduce system resource redundancy, the present application may only configure the keep-alive state resource domain access right for the distributed node in the set system resource domain, that is, the distributed node may access the small part of the idle resource domain set in the system resource domain to maintain its normal operation, and at the same time, the present application may adjust the traffic load parameter of the upstream node to which the distributed node belongs, so that the normal load traffic sent by the upstream node to the distributed node is reduced to the heartbeat traffic, for example, the upstream node only sends about 1% of the heartbeat traffic to the downstream distributed node, which is used to ensure that the downstream node is alive.
In order to timely expand the capacity in a large flow rate of the production environment, in an embodiment of the distributed node resource dynamic scheduling method of the present application, the step S103 may further specifically include the following contents:
if the load time sequence data exceeds the preset threshold, only configuring an operating state resource domain access right for the distributed node in a set system resource domain, and adjusting a traffic load parameter of an upstream node to which the distributed node belongs, so that the heartbeat traffic sent by the upstream node to the distributed node is increased to be normal load traffic.
Optionally, if the load time series data exceeds the preset threshold, that is, the flow is suddenly increased in the production environment at this time, in order to perform capacity expansion on the distributed node in time and ensure stable operation of the system, the present application may only configure an operation state resource domain access right for the distributed node in a set system resource domain, that is, the distributed node may access a majority of resource domains set in the system resource domain to perform capacity expansion, and adjust a flow load parameter of an upstream node to which the distributed node belongs, so that the heartbeat flow sent by the upstream node to the distributed node is increased to a normal load flow.
In order to perform node resource scheduling in combination with the service attribute of the traffic, in an embodiment of the distributed node resource dynamic scheduling method of the present application, referring to fig. 2, the step S103 may further specifically include the following contents:
step S201: and if the service attribute of the service flow received by each distributed node belongs to the specific service attribute, configuring the operating state resource domain access authority for the distributed node in a set system resource domain.
Step S202: and if the service attribute of the service flow received by each distributed node belongs to the conventional service attribute, configuring the access authority of the keep-alive state resource domain for the distributed node in the set system resource domain.
Optionally, in addition to determining whether the traffic surge occurs according to the sequence data during the load of the distributed nodes, the present application may further determine whether resource domain expansion is required according to the service attribute of the service traffic received by each distributed node, for example, when the service attribute belongs to a specific service attribute (e.g., a specific business activity), only the distributed node configures an access right of the running resource domain in a set system resource domain, that is, the distributed node may access a majority of resource domains set in the system resource domain to perform expansion.
In order to accurately analyze the current node working environment, in an embodiment of the distributed node resource dynamic scheduling method of the present application, the step S102 may further include the following steps:
and performing time sequence aggregation processing on the collected CPU occupation amount, the waiting queue length and the current node response time of each distributed node according to a set time dimension to obtain the corresponding CPU utilization rate, the thread pool availability rate, the node response success rate and the node response average time length.
Optionally, the application basic environment data and the node service environment data of each distributed node collected by the application basic environment data collection method may be subjected to time sequence aggregation processing periodically, that is, the data is converted into time sequence data based on a set time dimension (for example, every day), that is, the load time sequence data.
For example, the load time series data CPU utilization rate may be obtained according to the CPU occupancy in the set time dimension, and the load time series data thread pool availability rate, the node response success rate, and the node response average duration may be obtained according to the waiting queue length and the current node response time in the set time dimension, for example.
In order to effectively reduce the overhead of redundant resources of a distributed system and improve the resource utilization rate of the distributed system, the present application provides an embodiment of a distributed node resource dynamic scheduling apparatus for implementing all or part of the contents of the distributed node resource dynamic scheduling method, and referring to fig. 3, the distributed node resource dynamic scheduling apparatus specifically includes the following contents:
the node environment monitoring module 10 is configured to collect application basic environment data and node service environment data in each distributed node according to a set time period, where each distributed node has a keep-alive resource domain access right and a run-state resource domain access right.
And the node load determining module 20 is configured to perform time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determine load time sequence data of each distributed node.
And the node resource domain scheduling module 30 is configured to determine an operation state scheduling policy of each distributed node according to a numerical comparison relationship between the load time sequence data and a preset threshold, and configure the keep-alive state resource domain access right and the operation state resource domain access right according to the operation state scheduling policy.
As can be seen from the above description, the distributed node resource dynamic scheduling apparatus provided in this embodiment of the present application can perform time sequence aggregation processing on application basic environment data and node service environment data of each distributed node acquired in a set time period according to a set time dimension, determine load time sequence data of each distributed node, and determine a corresponding operation state scheduling policy of each distributed node, so as to configure a keep-alive state resource domain access right and an operation state resource domain access right of each distributed node according to the operation state scheduling policy, thereby effectively reducing redundant resource overhead of a distributed system, and improving resource utilization rate of the distributed system.
To further illustrate the present solution, the present application further provides a specific application example of implementing the distributed node resource dynamic scheduling method by using the distributed node resource dynamic scheduling apparatus, and refer to fig. 6, which specifically includes the following contents:
during the operation process of the distributed node, rpc requests (remote calling requests) are carried out on transactions through the distributed service framework according to the operation parameters, and meanwhile, monitoring data are reported to the monitoring system periodically.
Specifically, in the embodiment, when the distributed node runs, the application program and the basic distributed service framework thereof run in the same process, the microservice is exposed to the outside, and in the running process, the running status of the current microservice process is sent to the monitoring system at intervals of every minute (allocable). The reported content is divided into basic environment data (CPU, etc.) and current node service environment data (current response time, waiting queue length, etc.).
After the data are reported to the monitoring system, the monitoring system collects the data transmitted by each distributed node periodically, aggregates the data into time sequence data according to the time dimension, such as the success rate of each node per minute, the response time, the availability rate of a thread pool, a cpu, a memory and the like, and then pushes the time sequence data to a control console, and the control console performs comprehensive scoring of multiple dimensions according to the monitoring data of each node.
And after the control console system finishes scoring, readjusting the number of the keep-alive state and running state running nodes of each application of each node for the provider node according to the score of each node. The updated parameters are issued in real time through the configuration center, and after the service framework of the service receives the updated strategy, the framework routing and operation strategy are dynamically updated in real time.
And sending only heartbeat which is about 1% of the original flow to the nodes in the keep-alive state, maintaining the heartbeat, and simultaneously enabling the corresponding provider node frames to enter a dormant state, only keeping heartbeat connection and running with the lowest resources. And for the node in the running state, the load flow is normal and the node works normally.
According to the method, dynamic self-adaptive rapid capacity expansion can be performed on some nodes with high accidental load pressure according to the real-time operation condition of the production environment, so that the nodes in the keep-alive state can be rapidly switched to the operation state, and the overall availability of the system is guaranteed. Meanwhile, compared with the traditional capacity expansion scheme, the method reduces the waste of reserved idle resources, reduces the system starting time, can be activated to the running state in real time because the system is in the cold running state in the keep-alive state, and improves the speed by multiple and increase compared with the normal starting.
In terms of hardware, in order to effectively reduce the overhead of redundant resources of a distributed system and improve the resource utilization rate of the distributed system, the present application provides an embodiment of an electronic device for implementing all or part of the contents in the method for dynamically scheduling distributed node resources, where the electronic device specifically includes the following contents:
a processor (processor), a memory (memory), a communication Interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between the distributed node resource dynamic scheduling device and relevant equipment such as a core service system, a user terminal, a relevant database and the like; the logic controller may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the logic controller may refer to an embodiment of the distributed node resource dynamic scheduling method and an embodiment of the distributed node resource dynamic scheduling apparatus in the embodiment for implementation, and the contents thereof are incorporated herein, and repeated details are not repeated.
It is understood that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), an in-vehicle device, a smart wearable device, and the like. Wherein, intelligence wearing equipment can include intelligent glasses, intelligent wrist-watch, intelligent bracelet etc..
In practical applications, part of the distributed node resource dynamic scheduling method may be executed on the electronic device side as described in the above, or all operations may be completed in the client device. The selection may be specifically performed according to the processing capability of the client device, the limitation of the user usage scenario, and the like. This is not a limitation of the present application. The client device may further include a processor if all operations are performed in the client device.
The client device may have a communication module (i.e., a communication unit), and may be communicatively connected to a remote server to implement data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, the server may also include a server on an intermediate platform, for example, a server on a third-party server platform that is communicatively linked to the task scheduling center server. The server may include a single computer device, or may include a server cluster formed by a plurality of servers, or a server structure of a distributed apparatus.
Fig. 7 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 7, the electronic device 9600 can include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 7 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
In one embodiment, the distributed node resource dynamic scheduling method function may be integrated into the central processor 9100. The central processor 9100 may be configured to control as follows:
step S101: acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access right and a running state resource domain access right.
Step S102: and performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determining load time sequence data of each distributed node.
Step S103: and determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
As can be seen from the above description, according to the electronic device provided in the embodiment of the present application, time sequence aggregation processing is performed on application basic environment data and node service environment data of each distributed node acquired in a set time period according to a set time dimension, load time sequence data of each distributed node is determined, and a corresponding operation state scheduling policy of each distributed node is determined, so as to configure a keep-alive state resource domain access right and an operation state resource domain access right of each distributed node according to the operation state scheduling policy, thereby effectively reducing redundant resource overhead of a distributed system and improving resource utilization rate of the distributed system.
In another embodiment, the distributed node resource dynamic scheduling apparatus may be configured separately from the central processor 9100, for example, the distributed node resource dynamic scheduling apparatus may be configured as a chip connected to the central processor 9100, and the function of the distributed node resource dynamic scheduling method may be implemented by the control of the central processor.
As shown in fig. 7, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 also does not necessarily include all of the components shown in fig. 7; further, the electronic device 9600 may further include components not shown in fig. 7, which may be referred to in the art.
As shown in fig. 7, a central processor 9100, sometimes referred to as a controller or operational control, can include a microprocessor or other processor device and/or logic device, which central processor 9100 receives input and controls the operation of the various components of the electronic device 9600.
The memory 9140 can be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to realize information storage or processing, or the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. Power supply 9170 is used to provide power to electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but is not limited thereto.
The memory 9140 can be a solid state memory, e.g., Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 9140 could also be some other type of device. Memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 being used for storing application programs and function programs or for executing a flow of operations of the electronic device 9600 by the central processor 9100.
The memory 9140 can also include a data store 9143, the data store 9143 being used to store data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, contact book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing ordinary telecommunications functions. The audio processor 9130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100, thereby enabling recording locally through the microphone 9132 and enabling locally stored sounds to be played through the speaker 9131.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps in the distributed node resource dynamic scheduling method whose execution subject is the server or the client in the foregoing embodiment, where the computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the computer program implements all the steps in the distributed node resource dynamic scheduling method whose execution subject is the server or the client in the foregoing embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
step S101: acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access right and a running state resource domain access right.
Step S102: and performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determining load time sequence data of each distributed node.
Step S103: and determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
As can be seen from the above description, in the computer-readable storage medium provided in this embodiment of the present application, time sequence aggregation processing is performed on application basic environment data and node service environment data of each distributed node acquired in a set time period according to a set time dimension, load time sequence data of each distributed node is determined, and an operating state scheduling policy of each corresponding distributed node is determined, so as to configure a keep-alive state resource domain access right and an operating state resource domain access right of each distributed node according to the operating state scheduling policy, thereby effectively reducing redundant resource overhead of a distributed system and improving resource utilization rate of the distributed system.
Embodiments of the present application further provide a computer program product capable of implementing all steps in the distributed node resource dynamic scheduling method in which an execution subject in the foregoing embodiments is a server or a client, where the computer program/instruction is executed by a processor to implement the steps of the distributed node resource dynamic scheduling method, for example, the computer program/instruction implements the following steps:
step S101: acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access right and a running state resource domain access right.
Step S102: and performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determining load time sequence data of each distributed node.
Step S103: and determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
As can be seen from the above description, in the computer program product provided in this embodiment of the present application, time sequence aggregation processing is performed on application basic environment data and node service environment data of each distributed node acquired in a set time period according to a set time dimension, load time sequence data of each distributed node is determined, and an operation state scheduling policy of each corresponding distributed node is determined, so as to configure a keep-alive state resource domain access right and an operation state resource domain access right of each distributed node according to the operation state scheduling policy, thereby effectively reducing redundant resource overhead of a distributed system and improving resource utilization rate of the distributed system.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principle and the implementation mode of the invention are explained by applying specific embodiments in the invention, and the description of the embodiments is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A distributed node resource dynamic scheduling method is characterized in that the method comprises the following steps:
acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access right and a running state resource domain access right;
performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension, and determining load time sequence data of each distributed node;
and determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
2. The method according to claim 1, wherein before collecting application basic environment data and node service environment data in each distributed node according to a set time period, the method comprises:
and determining corresponding keep-alive state resource domain access authority and running state resource domain access authority according to the maximum pre-estimated resource occupation scale and the minimum pre-estimated resource occupation scale of the application contained in each distributed node.
3. The method for dynamically scheduling distributed node resources according to claim 1, wherein the determining an operation state scheduling policy of each distributed node according to a numerical comparison relationship between the load timing sequence data and a preset threshold, and configuring the keep-alive state resource domain access right and the operation state resource domain access right according to the operation state scheduling policy comprises:
if the load time sequence data does not exceed the preset threshold, only configuring a keep-alive state resource domain access right for the distributed node in a set system resource domain, and adjusting a traffic load parameter of an upstream node to which the distributed node belongs, so that normal load traffic sent to the distributed node by the upstream node is reduced to be heartbeat traffic.
4. The method for dynamically scheduling distributed node resources according to claim 1, wherein the determining an operation state scheduling policy of each distributed node according to a numerical comparison relationship between the load timing sequence data and a preset threshold, and configuring the keep-alive state resource domain access right and the operation state resource domain access right according to the operation state scheduling policy comprises:
if the load time sequence data exceeds the preset threshold, only configuring an operating state resource domain access right for the distributed node in a set system resource domain, and adjusting a traffic load parameter of an upstream node to which the distributed node belongs, so that the heartbeat traffic sent by the upstream node to the distributed node is increased to be normal load traffic.
5. The method according to claim 1, wherein the determining the operation state scheduling policy of each distributed node further comprises:
if the service attribute of the service flow received by each distributed node belongs to a specific service attribute, configuring a running state resource domain access authority for the distributed node in a set system resource domain;
and if the service attribute of the service flow received by each distributed node belongs to the conventional service attribute, configuring the access authority of the keep-alive state resource domain for the distributed node in the set system resource domain.
6. The method according to claim 1, wherein the performing a time sequence aggregation process on the application basic environment data and the node service environment data according to a set time dimension to determine load time sequence data of each distributed node includes:
and performing time sequence aggregation processing on the collected CPU occupation amount, the waiting queue length and the current node response time of each distributed node according to a set time dimension to obtain the corresponding CPU utilization rate, the thread pool availability rate, the node response success rate and the node response average time length.
7. A distributed node resource dynamic scheduling device, comprising:
the node environment monitoring module is used for acquiring application basic environment data and node service environment data in each distributed node according to a set time period, wherein each distributed node has a keep-alive state resource domain access authority and a running state resource domain access authority;
the node load determining module is used for performing time sequence aggregation processing on the application basic environment data and the node service environment data according to a set time dimension and determining load time sequence data of each distributed node;
and the node resource domain scheduling module is used for determining an operation state scheduling strategy of each distributed node according to the numerical comparison relationship between the load time sequence data and a preset threshold value, and configuring the keep-alive state resource domain access authority and the operation state resource domain access authority according to the operation state scheduling strategy.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the distributed node resource dynamic scheduling method of any one of claims 1 to 6 when executing the program.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for dynamic scheduling of distributed node resources of any one of claims 1 to 6.
10. A computer program product comprising computer program/instructions, characterized in that the computer program/instructions, when executed by a processor, implement the steps of the distributed node resource dynamic scheduling method of any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111559888.9A CN114237896A (en) | 2021-12-20 | 2021-12-20 | Distributed node resource dynamic scheduling method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111559888.9A CN114237896A (en) | 2021-12-20 | 2021-12-20 | Distributed node resource dynamic scheduling method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114237896A true CN114237896A (en) | 2022-03-25 |
Family
ID=80758934
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111559888.9A Pending CN114237896A (en) | 2021-12-20 | 2021-12-20 | Distributed node resource dynamic scheduling method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114237896A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115098247A (en) * | 2022-06-06 | 2022-09-23 | 支付宝(杭州)信息技术有限公司 | Resource allocation method and device |
| CN117744129A (en) * | 2023-09-18 | 2024-03-22 | 苏州天安慧网络运营有限公司 | Intelligent operation and maintenance method and system based on CIM |
-
2021
- 2021-12-20 CN CN202111559888.9A patent/CN114237896A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115098247A (en) * | 2022-06-06 | 2022-09-23 | 支付宝(杭州)信息技术有限公司 | Resource allocation method and device |
| CN117744129A (en) * | 2023-09-18 | 2024-03-22 | 苏州天安慧网络运营有限公司 | Intelligent operation and maintenance method and system based on CIM |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107018175B (en) | Scheduling method and device of mobile cloud computing platform | |
| US9338642B2 (en) | Method and apparatus for processing application program, and mobile terminal therefor | |
| CN108540568B (en) | Computing capacity sharing method and intelligent equipment | |
| WO2020259354A1 (en) | Queue adjustment method, apparatus and device, and computer-readable storage medium | |
| CN113032233A (en) | Distributed service cluster runtime parameter adaptive processing method, device and system | |
| CN113055479A (en) | Self-adaptive processing method, device and system for distributed service cluster load | |
| CN114237896A (en) | Distributed node resource dynamic scheduling method and device | |
| CN111796935B (en) | Consumption instance distribution method and system for calling log information | |
| CN109032805A (en) | A kind of scalable appearance method, apparatus of elasticity, server and storage medium | |
| CN111782473A (en) | Distributed log data processing method, device and system | |
| CN111913792A (en) | Service processing method and device | |
| US20140141793A1 (en) | System and method to manage qos in a bandwidth-constrained network (cellular) by sending tower-initiated policy changes to individual phones | |
| CN106162577A (en) | A kind of information push method, and message pushing equipment | |
| CN103781025A (en) | Instant message state update system, instant message state update system and instant message server | |
| CN112396511A (en) | Distributed wind control variable data processing method, device and system | |
| CN109308219B (en) | Task processing method and device and distributed computer system | |
| CN115914375A (en) | Disaster tolerance processing method and device for distributed message platform | |
| WO2017142773A1 (en) | User presence prediction driven device management | |
| CN117076195A (en) | Parameter adjusting method and device, storage medium and electronic device | |
| CN114116220B (en) | GPU sharing control method, GPU sharing control device and storage medium | |
| CN114003388A (en) | Method and device for determining task parameters of big data computing engine | |
| CN112905358A (en) | Software distribution method, device and system of distributed system | |
| CN112035324A (en) | Batch job execution condition monitoring method and device | |
| CN111737297A (en) | Method and device for processing link aggregation call information | |
| CN113342501B (en) | System fault processing method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |