CN117149395A - IDC machine room resource management method and system - Google Patents
IDC machine room resource management method and system Download PDFInfo
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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
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
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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
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Abstract
The invention discloses a method and a system for managing resources of an IDC machine room, which are characterized in that the resource utilization rate of different objects in the IDC machine room is obtained based on a probe technology, a three-dimensional visual interaction model of the IDC machine room resources is constructed according to a WebGL technology and the resource utilization rate, the effect of monitoring the IDC resource consumption condition in real time can be realized, and meanwhile, when the three-dimensional visual interaction model of the IDC machine room resources receives task information, the resource dynamic scheduling of the different objects is carried out according to a multi-attribute decision algorithm, so that the resource dynamic allocation can be effectively realized, and the defects that the IDC resource consumption condition cannot be mastered in real time and the IDC resource consumption condition cannot be dynamically allocated in the prior art can be effectively solved.
Description
Technical Field
The invention relates to the technical field of IDC machine room resources, in particular to an IDC machine room resource management method and system.
Background
With the promotion of the strategy of 'digital China', 'enterprise cloud' and the rapid expansion of the scale of IDC; the rise of 5G and Internet of things applications, the edge computing has induced a great deal of demand for small IDCs. The information collection of the traditional data center is generated by operation and maintenance personnel on entity equipment, the IDC resource consumption condition cannot be mastered in real time, dynamic allocation is not carried out when resources conflict, and equipment of large centralized IDC and small dispersed IDC is difficult to manage simultaneously.
Disclosure of Invention
In view of the above, the invention provides a method and a system for managing resources in an IDC machine room, which can solve the defects that the IDC resource consumption condition cannot be mastered in real time and the IDC resource cannot be dynamically allocated in the prior art.
The technical scheme of the invention is realized as follows:
the IDC machine room resource management method specifically comprises the following steps:
acquiring resource utilization rates of different objects in the IDC machine room based on a probe technology;
constructing an IDC machine room resource three-dimensional visual interaction model according to the WebGL technology and the resource utilization rate;
when the IDC machine room resource three-dimensional visual interaction model receives task information, dynamic scheduling of resources of different objects is carried out according to a multi-attribute decision algorithm, so that management of IDC machine room resources is realized.
As a further alternative of the IDC room resource management method, the acquiring resource usage data of different objects in the IDC room based on the probe technology specifically includes:
real-time monitoring is carried out on the use conditions of different objects in the IDC machine room in one or more nodes to obtain resource use data of the different objects in the IDC machine room;
correspondingly storing the resource use data of different objects in the IDC machine room and the generation time of the resource use data into a resource use database;
and carrying out statistical analysis on the resource usage data in the resource usage database to obtain the resource usage rate of different objects in the IDC machine room.
As a further alternative of the IDC room resource management method, the constructing an IDC room resource three-dimensional visual interaction model according to WebGL technology and resource utilization rate specifically includes:
constructing a data service layer, which is used for carrying out data docking with a database and a field monitoring device and accessing into a 3D cloud platform engine;
an application service layer is constructed and used for presetting scene objects for different objects in the IDC machine room according to the WebGL technology, mounting functional scripts of the corresponding scene objects and accessing a 3D cloud platform engine;
and constructing a three-dimensional interaction layer, wherein the three-dimensional interaction layer is used for acquiring model data of the 3D cloud platform engine, distributing a three-dimensional visual scene to the three-dimensional man-machine interaction interface and/or receiving task information fed back by the three-dimensional man-machine interaction interface.
As a further alternative of the IDC room resource management method, the constructing an IDC room resource three-dimensional visual interaction model further includes constructing a simplified scene object layer, where the simplified scene object layer is used for simplifying a scene object, and specifically includes:
counting the types of scene objects, and setting different weights w according to different scene objects;
setting a vision distance threshold L;
acquiring a bounding sphere z of the shape of a scene object by a bounding box method;
acquiring a radius r and a viewing distance d of the surrounding sphere z;
calculating the ratio x of the radius r and the sight distance d;
and judging whether the scene object needs to be simplified or not according to the weight w multiplied by the ratio x and the threshold L.
As a further alternative of the IDC room resource management method, the dynamic scheduling of resources of different objects according to a multi-attribute decision algorithm specifically includes:
acquiring evaluation attributes of task information and establishing an attribute matrix;
ordering each attribute according to the attribute matrix to obtain the maximum value and the minimum value of each attribute;
performing dimensionless treatment on the attribute according to the maximum value and the minimum value to obtain a decision matrix;
calculating the decision matrix by using a dispersion maximization calculation method to obtain an attribute weight normalization vector which maximizes the dispersion of the whole attribute set;
calculating a multi-attribute comprehensive evaluation value of each task by using the attribute weight normalized vector to obtain the priority of the task;
and carrying out dynamic scheduling on resources of different objects according to the priority of the task.
An IDC machine room resource management system, comprising:
the on-site monitoring device is used for acquiring the resource utilization rate of different objects in the IDC machine room based on a probe technology;
the construction module is used for constructing an IDC machine room resource three-dimensional visual interaction model according to the WebGL technology and the resource utilization rate;
and the dynamic scheduling module is used for carrying out dynamic scheduling on resources of different objects according to a multi-attribute decision algorithm when the three-dimensional visual interaction model of the resources of the IDC machine room receives the task information, so that the management of the resources of the IDC machine room is realized.
As a further alternative to the IDC room resource management system, the on-site monitoring device includes:
the real-time monitoring module is used for monitoring the use conditions of different objects in the IDC machine room in one or more nodes in real time to obtain resource use data of the different objects in the IDC machine room;
the storage module is used for correspondingly storing the resource use data of different objects in the IDC machine room and the generation time of the resource use data into the resource use database;
and the statistical analysis module is used for carrying out statistical analysis on the resource use data in the resource use database to obtain the resource use rates of different objects in the IDC machine room.
As a further alternative of the IDC room resource management system, the building module includes:
the first construction module is used for constructing a data service layer, wherein the data service layer is used for carrying out data docking with the database and the on-site monitoring device and accessing into the 3D cloud platform engine;
the second construction module is used for constructing an application service layer, wherein the application service layer is used for presetting scene objects for different objects in the IDC machine room according to the WebGL technology, mounting functional scripts of the corresponding scene objects and accessing the 3D cloud platform engine;
the third construction module is used for constructing a three-dimensional interaction layer, and the three-dimensional interaction layer is used for acquiring model data of the 3D cloud platform engine, distributing a three-dimensional visual scene to the three-dimensional man-machine interaction interface and/or receiving task information fed back by the three-dimensional man-machine interaction interface.
As a further alternative of the IDC room resource management system, the building module further includes a fourth building module, configured to build a simplified scene object layer, where the simplified scene object layer includes:
the first setting module is used for counting the types of scene objects and setting different weights w according to different scene objects;
the second setting module is used for setting a sight distance threshold L;
the first acquisition module is used for acquiring a bounding sphere z of the shape of the scene object by a bounding box method;
the second acquisition module is used for acquiring the radius r and the sight distance d of the surrounding sphere z;
the first calculation module is used for calculating the ratio x of the radius r and the sight distance d;
the judging module is used for judging whether the scene object needs to be simplified or not according to the weight w multiplied by the ratio x and the threshold L.
As a further alternative of the IDC room resource management system, the dynamic scheduling module includes:
the third acquisition module is used for acquiring the evaluation attribute of the task information and establishing an attribute matrix;
the sorting module is used for sorting each attribute according to the attribute matrix to obtain the maximum value and the minimum value of each attribute;
the dimensionless processing module is used for carrying out dimensionless processing on the attribute according to the maximum value and the minimum value to obtain a decision matrix;
the second calculation module is used for calculating the decision matrix by using a dispersion maximization calculation method to obtain an attribute weight normalization vector which maximizes the dispersion of the whole attribute set;
the third calculation module is used for calculating the multi-attribute comprehensive evaluation value of each task by using the attribute weight normalized vector to obtain the priority of the task;
and the execution module is used for carrying out dynamic scheduling on the resources of different objects according to the priority of the task.
The beneficial effects of the invention are as follows: the resource utilization rate of different objects in the IDC machine room is obtained based on the probe technology, the three-dimensional visual interaction model of the IDC machine room resource is constructed according to the WebGL technology and the resource utilization rate, the effect of monitoring the IDC resource consumption condition in real time can be achieved, and meanwhile, when the three-dimensional visual interaction model of the IDC machine room resource receives task information, dynamic scheduling of the resources of different objects is carried out according to the multi-attribute decision algorithm, so that dynamic allocation of the resources can be effectively achieved, and the defects that the IDC resource consumption condition cannot be mastered in real time and the dynamic allocation cannot be achieved in the prior art are effectively overcome.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for managing resources in an IDC machine room according to the present invention;
fig. 2 is a schematic diagram of the components of an IDC room resource management system according to the present invention.
Detailed Description
The following description of the technical solutions in the embodiments of the present invention will be clear and complete, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, a method for managing resources in an IDC machine room specifically includes:
acquiring resource utilization rates of different objects in the IDC machine room based on a probe technology;
constructing an IDC machine room resource three-dimensional visual interaction model according to the WebGL technology and the resource utilization rate;
when the IDC machine room resource three-dimensional visual interaction model receives task information, dynamic scheduling of resources of different objects is carried out according to a multi-attribute decision algorithm, so that management of IDC machine room resources is realized.
In this embodiment, the resource utilization rate of different objects in the IDC machine room is obtained based on the probe technology, and the three-dimensional visual interaction model of IDC machine room resources is constructed according to the WebGL technology and the resource utilization rate, so that the effect of monitoring IDC resource consumption conditions in real time can be achieved.
Preferably, the acquiring the resource usage data of different objects in the IDC machine room based on the probe technology specifically includes:
real-time monitoring is carried out on the use conditions of different objects in the IDC machine room in one or more nodes to obtain resource use data of the different objects in the IDC machine room;
correspondingly storing the resource use data of different objects in the IDC machine room and the generation time of the resource use data into a resource use database;
and carrying out statistical analysis on the resource usage data in the resource usage database to obtain the resource usage rate of different objects in the IDC machine room.
In this embodiment, the use conditions of resources such as an elastic cloud server, a cloud hard disk, an elastic IP, a bandwidth, a database and the like in one or more nodes are monitored in real time to obtain resource use data; correspondingly storing the generation time of the resource use data into a resource use database; the resource utilization data in the resource utilization database is subjected to statistical analysis to obtain the resource utilization rate of different objects in the IDC machine room, and the conditions of unreasonable resource utilization and the like can be effectively solved by knowing the distribution and utilization conditions of the resources, so that the condition that the resource utilization rate is too low, a server is in an empty load condition, a large amount of resource waste is caused, the energy consumption is increased, the condition that the resource utilization rate is too high, the server is in a saturated working state, the user experience is seriously influenced, and the usability is reduced.
Preferably, the constructing the three-dimensional visual interaction model of the IDC machine room resources according to the WebGL technology and the resource utilization rate specifically includes:
constructing a data service layer, which is used for carrying out data docking with a database and a field monitoring device and accessing into a 3D cloud platform engine;
an application service layer is constructed and used for presetting scene objects for different objects in the IDC machine room according to the WebGL technology, mounting functional scripts of the corresponding scene objects and accessing a 3D cloud platform engine;
and constructing a three-dimensional interaction layer, wherein the three-dimensional interaction layer is used for acquiring model data of the 3D cloud platform engine, distributing a three-dimensional visual scene to the three-dimensional man-machine interaction interface and/or receiving task information fed back by the three-dimensional man-machine interaction interface.
Preferably, the constructing the three-dimensional visual interaction model of IDC room resources further includes constructing a simplified scene object layer, where the simplified scene object layer is used for simplifying a scene object, and specifically includes:
counting the types of scene objects, and setting different weights w according to different scene objects;
setting a vision distance threshold L;
acquiring a bounding sphere z of the shape of a scene object by a bounding box method;
acquiring a radius r and a viewing distance d of the surrounding sphere z;
calculating the ratio x of the radius r and the sight distance d;
and judging whether the scene object needs to be simplified or not according to the weight w multiplied by the ratio x and the threshold L.
In this embodiment, according to the above steps, a reference value for hierarchical simplification of different objects in a scene is calculated through a formula, and when the reference value is greater than zero, the target object is geometrically simplified in real time, otherwise, normal rendering processing is performed;
in the above formula, z [ i ]. R is the radius of the smallest bounding sphere of the object model, (xz [ i ], yz [ i ], zz [ i ]) is the spherical center coordinate of the smallest bounding sphere, and (xvw, yvw, zvw) is the three-dimensional coordinate of the viewpoint. The LOD display optimization based on the object distance is realized in the WebGL by calculating the distance from the center of the surrounding sphere of the scene model to the viewpoint, setting a flag for the JSON object according to the distance, setting the flag to true when the distance is larger than a threshold value, namely simplifying the geometric unit of the JSON object, otherwise setting the flag to false, so that the performance can be effectively improved, and the visual effect experience is not influenced.
It should be noted that, LOD display optimization based on object distance is to establish different levels of refinement effects according to different scene objects to achieve the purpose of optimization, different types of objects have different importance degrees in a 3D scene, geometric compaction is performed on different models according to a certain criterion, thus occupation of overall resources of the system is reduced, weights w are set for different types of objects according to the line of sight and importance degrees of the scene objects, and the weights are used as influence coefficients of LOD model compaction algorithm scheduling.
The core of the LOD optimization algorithm based on the object distance is to calculate the sight distance D of the object, set a distance threshold L, simplify the geometric unit of the object if the sight distance exceeds the threshold, and the visual huge difference can not appear in the 3D scene due to the dyeing of the 3D scene as long as the threshold is set reasonably, and the rendering effect and the performance are improved in a balanced way due to the effect of scene simplification.
Preferably, the performing the dynamic scheduling of the resources of the different objects according to the multi-attribute decision algorithm specifically includes:
acquiring evaluation attributes of task information and establishing an attribute matrix;
ordering each attribute according to the attribute matrix to obtain the maximum value and the minimum value of each attribute;
performing dimensionless treatment on the attribute according to the maximum value and the minimum value to obtain a decision matrix;
calculating the decision matrix by using a dispersion maximization calculation method to obtain an attribute weight normalization vector which maximizes the dispersion of the whole attribute set;
calculating a multi-attribute comprehensive evaluation value of each task by using the attribute weight normalized vector to obtain the priority of the task;
and carrying out dynamic scheduling on resources of different objects according to the priority of the task.
In this embodiment, a multi-attribute decision algorithm is adopted to implement a task scheduling mechanism when resources are insufficient, a request with highest priority and meeting resource constraints is processed first, a task priority of multi-attribute decision evaluates attribute weight calculation and sequencing algorithm, importance weight of task attributes has an important influence on the result of the multi-attribute decision method, rationality of task attribute weight directly affects accuracy of task priority evaluation, therefore, a weighting method with fast weight calculation speed and consistent weight characterization meaning with system targets is needed, the multi-attribute dispersion maximization decision method is an optimization decision method using objective information (attribute value) weighting, differences among evaluation attributes can be effectively amplified, task optimization and sequencing are facilitated, and therefore, a priority weight calculation method based on dispersion maximization realizes dynamic priority dispatch of tasks, and the dispersion maximization weight calculation method has the advantages of fast calculation speed, strong real-time performance and independence on historical data, and can better meet real-time task scheduling requirements compared with other multi-attribute decision methods.
The evaluation attribute indexes are generally classified into benefit type and cost type, the larger the benefit type index value is, the better the cost type index value is, the smaller the cost type index value is, because each attribute has different dimension and dimension units, in order to eliminate the incoordination, each attribute index of a task needs to be processed in a dimensionless manner before priority assignment is carried out, and the incoordination among the attributes means that no unified measurement standard exists among the attributes and cannot be directly compared.
An IDC machine room resource management system, comprising:
the on-site monitoring device is used for acquiring the resource utilization rate of different objects in the IDC machine room based on a probe technology;
the construction module is used for constructing an IDC machine room resource three-dimensional visual interaction model according to the WebGL technology and the resource utilization rate;
and the dynamic scheduling module is used for carrying out dynamic scheduling on resources of different objects according to a multi-attribute decision algorithm when the three-dimensional visual interaction model of the resources of the IDC machine room receives the task information, so that the management of the resources of the IDC machine room is realized.
Preferably, the field monitoring device includes:
the real-time monitoring module is used for monitoring the use conditions of different objects in the IDC machine room in one or more nodes in real time to obtain resource use data of the different objects in the IDC machine room;
the storage module is used for correspondingly storing the resource use data of different objects in the IDC machine room and the generation time of the resource use data into the resource use database;
and the statistical analysis module is used for carrying out statistical analysis on the resource use data in the resource use database to obtain the resource use rates of different objects in the IDC machine room.
Preferably, the construction module includes:
the first construction module is used for constructing a data service layer, wherein the data service layer is used for carrying out data docking with the database and the on-site monitoring device and accessing into the 3D cloud platform engine;
the second construction module is used for constructing an application service layer, wherein the application service layer is used for presetting scene objects for different objects in the IDC machine room according to the WebGL technology, mounting functional scripts of the corresponding scene objects and accessing the 3D cloud platform engine;
the third construction module is used for constructing a three-dimensional interaction layer, and the three-dimensional interaction layer is used for acquiring model data of the 3D cloud platform engine, distributing a three-dimensional visual scene to the three-dimensional man-machine interaction interface and/or receiving task information fed back by the three-dimensional man-machine interaction interface.
Preferably, the building module further includes a fourth building module for building a simplified scene object layer, the simplified scene object layer including:
the first setting module is used for counting the types of scene objects and setting different weights w according to different scene objects;
the second setting module is used for setting a sight distance threshold L;
the first acquisition module is used for acquiring a bounding sphere z of the shape of the scene object by a bounding box method;
the second acquisition module is used for acquiring the radius r and the sight distance d of the surrounding sphere z;
the first calculation module is used for calculating the ratio x of the radius r and the sight distance d;
the judging module is used for judging whether the scene object needs to be simplified or not according to the weight w multiplied by the ratio x and the threshold L.
Preferably, the dynamic scheduling module includes:
the third acquisition module is used for acquiring the evaluation attribute of the task information and establishing an attribute matrix;
the sorting module is used for sorting each attribute according to the attribute matrix to obtain the maximum value and the minimum value of each attribute;
the dimensionless processing module is used for carrying out dimensionless processing on the attribute according to the maximum value and the minimum value to obtain a decision matrix;
the second calculation module is used for calculating the decision matrix by using a dispersion maximization calculation method to obtain an attribute weight normalization vector which maximizes the dispersion of the whole attribute set;
the third calculation module is used for calculating the multi-attribute comprehensive evaluation value of each task by using the attribute weight normalized vector to obtain the priority of the task;
and the execution module is used for carrying out dynamic scheduling on the resources of different objects according to the priority of the task.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. The IDC machine room resource management method is characterized by comprising the following steps:
acquiring resource utilization rates of different objects in the IDC machine room based on a probe technology;
constructing an IDC machine room resource three-dimensional visual interaction model according to the WebGL technology and the resource utilization rate;
when the IDC machine room resource three-dimensional visual interaction model receives task information, dynamic scheduling of resources of different objects is carried out according to a multi-attribute decision algorithm, so that management of IDC machine room resources is realized.
2. The method for resource management of IDC room according to claim 1, wherein the acquiring the resource usage data of different objects in the IDC room based on the probe technology specifically comprises:
real-time monitoring is carried out on the use conditions of different objects in the IDC machine room in one or more nodes to obtain resource use data of the different objects in the IDC machine room;
correspondingly storing the resource use data of different objects in the IDC machine room and the generation time of the resource use data into a resource use database;
and carrying out statistical analysis on the resource usage data in the resource usage database to obtain the resource usage rate of different objects in the IDC machine room.
3. The IDC room resource management method of claim 2, wherein the constructing the IDC room resource three-dimensional visual interaction model according to WebGL technology and resource utilization rate specifically comprises:
constructing a data service layer, which is used for carrying out data docking with a database and a field monitoring device and accessing into a 3D cloud platform engine;
an application service layer is constructed and used for presetting scene objects for different objects in the IDC machine room according to the WebGL technology, mounting functional scripts of the corresponding scene objects and accessing a 3D cloud platform engine;
and constructing a three-dimensional interaction layer, wherein the three-dimensional interaction layer is used for acquiring model data of the 3D cloud platform engine, distributing a three-dimensional visual scene to the three-dimensional man-machine interaction interface and/or receiving task information fed back by the three-dimensional man-machine interaction interface.
4. The IDC room resource management method of claim 3, wherein the constructing the IDC room resource three-dimensional visual interaction model further comprises constructing a simplified scene object layer, the simplified scene object layer being used for simplifying scene objects, and specifically comprising:
counting the types of scene objects, and setting different weights w according to different scene objects;
setting a vision distance threshold L;
acquiring a bounding sphere z of the shape of a scene object by a bounding box method;
acquiring a radius r and a viewing distance d of the surrounding sphere z;
calculating the ratio x of the radius r and the sight distance d;
and judging whether the scene object needs to be simplified or not according to the weight w multiplied by the ratio x and the threshold L.
5. The method for IDC room resource management according to claim 4, wherein the dynamic scheduling of resources of different objects according to the multi-attribute decision algorithm specifically comprises:
acquiring evaluation attributes of task information and establishing an attribute matrix;
ordering each attribute according to the attribute matrix to obtain the maximum value and the minimum value of each attribute;
performing dimensionless treatment on the attribute according to the maximum value and the minimum value to obtain a decision matrix;
calculating the decision matrix by using a dispersion maximization calculation method to obtain an attribute weight normalization vector which maximizes the dispersion of the whole attribute set;
calculating a multi-attribute comprehensive evaluation value of each task by using the attribute weight normalized vector to obtain the priority of the task;
and carrying out dynamic scheduling on resources of different objects according to the priority of the task.
6. An IDC machine room resource management system, comprising:
the on-site monitoring device is used for acquiring the resource utilization rate of different objects in the IDC machine room based on a probe technology;
the construction module is used for constructing an IDC machine room resource three-dimensional visual interaction model according to the WebGL technology and the resource utilization rate;
and the dynamic scheduling module is used for carrying out dynamic scheduling on resources of different objects according to a multi-attribute decision algorithm when the three-dimensional visual interaction model of the resources of the IDC machine room receives the task information, so that the management of the resources of the IDC machine room is realized.
7. The IDC room resource management system of claim 6 wherein the in-situ monitoring device comprises:
the real-time monitoring module is used for monitoring the use conditions of different objects in the IDC machine room in one or more nodes in real time to obtain resource use data of the different objects in the IDC machine room;
the storage module is used for correspondingly storing the resource use data of different objects in the IDC machine room and the generation time of the resource use data into the resource use database;
and the statistical analysis module is used for carrying out statistical analysis on the resource use data in the resource use database to obtain the resource use rates of different objects in the IDC machine room.
8. The IDC room resource management system of claim 7, wherein the building block comprises:
the first construction module is used for constructing a data service layer, wherein the data service layer is used for carrying out data docking with the database and the on-site monitoring device and accessing into the 3D cloud platform engine;
the second construction module is used for constructing an application service layer, wherein the application service layer is used for presetting scene objects for different objects in the IDC machine room according to the WebGL technology, mounting functional scripts of the corresponding scene objects and accessing the 3D cloud platform engine;
the third construction module is used for constructing a three-dimensional interaction layer, and the three-dimensional interaction layer is used for acquiring model data of the 3D cloud platform engine, distributing a three-dimensional visual scene to the three-dimensional man-machine interaction interface and/or receiving task information fed back by the three-dimensional man-machine interaction interface.
9. The IDC room resource management system of claim 8 wherein the building block further comprises a fourth building block for building a simplified scene object layer comprising:
the first setting module is used for counting the types of scene objects and setting different weights w according to different scene objects;
the second setting module is used for setting a sight distance threshold L;
the first acquisition module is used for acquiring a bounding sphere z of the shape of the scene object by a bounding box method;
the second acquisition module is used for acquiring the radius r and the sight distance d of the surrounding sphere z;
the first calculation module is used for calculating the ratio x of the radius r and the sight distance d;
the judging module is used for judging whether the scene object needs to be simplified or not according to the weight w multiplied by the ratio x and the threshold L.
10. The IDC room resource management system of claim 9, wherein the dynamic scheduling module comprises:
the third acquisition module is used for acquiring the evaluation attribute of the task information and establishing an attribute matrix;
the sorting module is used for sorting each attribute according to the attribute matrix to obtain the maximum value and the minimum value of each attribute;
the dimensionless processing module is used for carrying out dimensionless processing on the attribute according to the maximum value and the minimum value to obtain a decision matrix;
the second calculation module is used for calculating the decision matrix by using a dispersion maximization calculation method to obtain an attribute weight normalization vector which maximizes the dispersion of the whole attribute set;
the third calculation module is used for calculating the multi-attribute comprehensive evaluation value of each task by using the attribute weight normalized vector to obtain the priority of the task;
and the execution module is used for carrying out dynamic scheduling on the resources of different objects according to the priority of the task.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102932279A (en) * | 2012-10-30 | 2013-02-13 | 北京邮电大学 | Multidimensional resource scheduling system and method for cloud environment data center |
| CN104991854A (en) * | 2015-06-12 | 2015-10-21 | 北京奇虎科技有限公司 | Method and system for monitoring and statistics of server sources |
| CN113298930A (en) * | 2021-05-12 | 2021-08-24 | 天海欧康科技信息(厦门)有限公司 | Three-dimensional process visual design method based on webgl technology |
| US11190411B1 (en) * | 2019-09-24 | 2021-11-30 | Amazon Technologies, Inc. | Three-dimensional graphical representation of a service provider network |
-
2023
- 2023-10-10 CN CN202311306953.6A patent/CN117149395A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102932279A (en) * | 2012-10-30 | 2013-02-13 | 北京邮电大学 | Multidimensional resource scheduling system and method for cloud environment data center |
| CN104991854A (en) * | 2015-06-12 | 2015-10-21 | 北京奇虎科技有限公司 | Method and system for monitoring and statistics of server sources |
| US11190411B1 (en) * | 2019-09-24 | 2021-11-30 | Amazon Technologies, Inc. | Three-dimensional graphical representation of a service provider network |
| CN113298930A (en) * | 2021-05-12 | 2021-08-24 | 天海欧康科技信息(厦门)有限公司 | Three-dimensional process visual design method based on webgl technology |
Non-Patent Citations (2)
| Title |
|---|
| 蒋召召: "基于WebGL的数据中心3D可视化系统的设计与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》, vol. 2019, no. 7, 15 July 2019 (2019-07-15), pages 39 - 40 * |
| 郭松辉: "一种动态优先级排序的虚拟机I/O调度算法", 《计算机科学》, vol. 44, no. 1, 31 January 2017 (2017-01-31), pages 13 - 19 * |
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