CN109889370B - Network equipment position determining method and device and computer readable storage medium - Google Patents
Network equipment position determining method and device and computer readable storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a device for determining the position of network equipment and a computer readable storage medium, which screen out machine positions with machine position resource information meeting conditions from all idle machine positions through constraint conditions of resource demand information associated with the network equipment to be deployed, and then select the optimal machine position from the screened machine positions according to an optimization target associated with the machine position resource information. On one hand, the real-time machine position resources and the actual demand information are subjected to quantization processing and then input into the machine position selection model provided by the embodiment to output the optimal machine position, so that the balanced distribution of the machine position resources is realized; on the other hand, because the final determination of the target machine position is realized strictly through the machine position selection model and automatically by the computer program, compared with the prior art which mainly depends on the experience and level of technical personnel, the efficiency and the objectivity of equipment deployment are improved.
Description
Technical Field
The present invention relates to the field of electronic technologies, and in particular, to a method and an apparatus for determining a location of a network device, and a computer-readable storage medium.
Background
With the rapid development of Internet technology, in order to meet the increasing network service requirements of users, network devices such as Data servers need to operate in a suitable operating environment, and the solution is to host the network devices to an IDC (Internet Data Center) room, and the room is used to secure the network services of the users.
The method comprises the steps that one or more network devices are installed in an IDC machine room, the deployment positions of the network devices are usually determined by combining machine room resources, at present, the mode of determining the deployment positions of the network devices usually depends on-site investigation by special technicians, and then the deployment positions of the network devices are designed by combining on-site investigation conditions, however, the action of manual investigation usually lacks accurate and global control over the machine room resources, so that different machine room resources are difficult to realize balanced utilization; moreover, the working efficiency of manpower is relatively limited, so that the time consumption of the whole scheme making period is relatively long; in addition, the investigation and design are performed completely depending on the experience and level of the technicians, which usually has the subjectivity of the technicians, and whether the final solution is good or bad cannot be judged.
Disclosure of Invention
The embodiments of the present invention mainly aim to provide a method and an apparatus for determining a location of a network device, and a computer-readable storage medium, which can at least solve the problems in the related art that equilibrium utilization of machine room resources is difficult to achieve, a scheme is time-consuming to make, and a scheme has strong subjectivity due to the fact that a machine room is surveyed and a deployment location of the network device is designed by means of a manual field.
In order to achieve the above object, a first aspect of the embodiments of the present invention provides a method for determining a location of a network device, where the method includes:
determining resource demand information of network equipment to be deployed;
judging whether a machine position with machine position resource information meeting the constraint condition exists according to the constraint condition associated with the resource demand information;
when the machine positions meeting the constraint condition exist, performing integral sequencing on all the machine positions meeting the constraint condition according to an optimization target related to machine position resource information;
determining a target machine position from all the machine positions according to the sequencing result, and outputting machine position identification information corresponding to the target machine position; the machine position identification information is used for identifying the physical position of the machine position.
In order to achieve the above object, a second aspect of the embodiments of the present invention provides a network device location determining apparatus, including:
the demand determining module is used for determining resource demand information of the network equipment to be deployed;
the condition judgment module is used for judging whether the machine position with the machine position resource information meeting the constraint condition exists or not according to the constraint condition associated with the resource demand information;
the integral sequencing module is used for carrying out integral sequencing on all the machine positions meeting the constraint condition according to an optimization target related to the machine position resource information when the machine positions meeting the constraint condition exist;
the position determining module is used for determining a target machine position from all the machine positions according to the sequencing result and outputting machine position identification information corresponding to the target machine position; the machine position identification information is used for identifying the physical position of the machine position.
To achieve the above object, a third aspect of embodiments of the present invention provides an electronic apparatus, including: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute one or more programs stored in the memory to implement the steps of any of the above-described network device location determination methods.
To achieve the above object, a fourth aspect of the embodiments of the present invention provides a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement the steps of any one of the above network device location determination methods.
As can be seen from the technical solutions provided in the embodiments of the present invention, machine positions with machine position resource information meeting the conditions are screened from all idle machine positions through constraint conditions associated with resource demand information of network devices to be deployed, and then an optimal machine position is selected from the screened machine positions according to an optimization target associated with the machine position resource information. On one hand, the real-time machine position resources and the actual demand information are subjected to quantization processing and then input into the machine position selection model provided by the embodiment to output the optimal machine position, so that the balanced distribution of the machine position resources is realized; on the other hand, because the final determination of the target machine position is realized strictly through the machine position selection model and automatically by the computer program, compared with the prior art which mainly depends on the experience and level of technical personnel, the efficiency and the objectivity of equipment deployment are improved.
Other features and corresponding effects of the present invention are set forth in the following portions of the specification, and it should be understood that at least some of the effects are apparent from the description of the present invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic basic flow chart of a method for determining a location of a network device according to a first embodiment of the present invention;
fig. 2 is a detailed flowchart of a network device location determining method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a network device location determining apparatus according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
The first embodiment:
in order to solve the technical problems in the related art that equilibrium utilization of machine room resources is difficult to achieve, a scheme is time-consuming to make, and a scheme is strong in subjectivity due to the fact that a machine room is manually surveyed on site and a deployment position of a network device is designed, a method for determining a position of a network device is provided in this embodiment, and as shown in fig. 1, a basic flow diagram of the method for determining a position of a network device provided in this embodiment is shown, and the method for determining a position of a network device provided in this embodiment includes the following steps:
Specifically, in this embodiment, the network device is a server, a switch, a router, and other devices that need to be hosted to the computer room, and the resource requirement information refers to resource information that needs to occupy the computer room after the network device is deployed to the computer room.
In an optional implementation manner of this embodiment, the resource requirement information includes: power consumption p, cold consumption c, number of occupied power supply terminals t and number of occupied machine bits s. Specifically, after different network devices are deployed on machine positions of a machine room, occupied resources of the machine room are different, in practical application, the number of power supply terminals required to be occupied by a single network device is usually 2, while the number of machine positions required to be occupied by a single network device is not necessarily 1 because of different specifications, and in some cases, a plurality of machine positions are occupied.
And 102, judging whether the machine position with the machine position resource information meeting the constraint condition exists according to the constraint condition associated with the resource demand information.
Specifically, in practical application, a power supply system usually belongs to a plurality of machine rooms, the machine rooms belong to a plurality of first column cabinets, one first column cabinet also belongs to a plurality of racks, and one rack is provided with a plurality of machine positions, so that environments to which different machine positions belong are different, and further corresponding machine position resource information is different.
In an optional implementation manner of this embodiment, the machine position resource information may include: the residual electricity quantity P1 of the machine frame belonging to the machine position, the residual cold quantity C of the machine room belonging to the machine position, the residual power supply terminal number T of the machine frame belonging to the machine position and the idle machine position number S of the machine frame belonging to the machine position.
In addition, in practical application, the network device is necessarily deployed to an available machine position, that is, to a machine position capable of meeting basic operation requirements of the network device, and based on this, the present embodiment makes a constraint condition according to resource requirement information of the network device to screen out an available machine position relative to the current network device to be deployed from all idle machine positions.
In an optional implementation manner of this embodiment, the constraint condition is: the machine resource information meets all kinds of requirements in the resource requirement information. Specifically, in practical application, a corresponding constraint condition can be formulated according to the actual equipment deployment requirement, wherein the stricter the constraint condition is, the higher the pertinence of the output result is, and the method is suitable for a strictly deployed application scene; the constraint condition is relatively loose, the higher the flexibility of the output result is, and the method is suitable for application scenes with relatively loose requirements; the constraint condition in this embodiment is associated with all resource demand information, that is, the resource demand information includes: when the power consumption p, the cold consumption c, the number t of occupied power supply terminals and the number s of occupied machine digits are as follows: c > C, P1 > P, S > S, and T > T.
And 103, when the machine positions meeting the constraint conditions exist, performing integral sequencing on all the machine positions meeting the constraint conditions according to the optimization target related to the machine position resource information.
Specifically, in this embodiment, if there is no machine location meeting the constraint condition, it indicates that there is no available machine location to deploy the current network device, and the demand end may return to modify the resource demand information again; and when the machine positions meeting the constraint condition exist, further determining the optimal machine positions from the screened machine positions, wherein an optimization target, namely an optimal machine position selection principle, is preset in the embodiment, then integrating all the machine positions respectively by adopting an integration system according to the meeting conditions of the machine positions relative to the optimization target, and finally outputting an integration sequencing result.
In an optional implementation manner of this embodiment, the optimization objective includes: balancing the residual electric quantity of all power supply systems, balancing the residual electric quantity of all column head cabinets, deploying used racks preferentially, balancing the residual cold quantity of all machine rooms and deploying the racks from bottom to top. Correspondingly, the machine room resource information required to be acquired in this embodiment includes: the residual electricity quantity P1 of the machine frame belonging to the machine position, the residual cold quantity C of the machine room belonging to the machine position, the residual power supply terminal number T of the machine frame belonging to the machine position, the idle machine position number S of the machine frame belonging to the machine position, the residual electricity quantity P2 of the power supply system belonging to the machine position, the residual electricity quantity P3 of the head cabinet of the column belonging to the machine position and the height H of the machine position.
In this case, the specific way of performing the integral sorting on all the stands meeting the constraint condition is as follows: respectively performing positive sequence integration on the residual electric quantity P2 of the power supply system to which the stands of all stands in accordance with the constraint condition belong according to a balanced first optimization target of the residual electric quantities of all the power supply systems to obtain first integrals; respectively performing positive sequence integration on the residual electric quantity P3 of the first column cabinet to which the machine positions of all the machine positions in accordance with the constraint condition belong to obtain a second integral according to a balanced second optimization target of the residual electric quantity of all the first column cabinets; according to a third optimization target of the prior deployment of the used racks, performing reverse integration on the residual electric quantity P1 of the racks to which the machine positions of all the machine positions meet the constraint condition belong and/or the number S of idle machine positions of the racks to which each machine position belongs to obtain a third integral; according to a fourth optimization target of the balance of the residual cold of all the machine rooms, respectively performing positive sequence integration on the residual cold C of the machine room to which the machine positions of all the machine positions in accordance with the constraint condition belong to obtain a fourth integral; according to a fifth optimization target of the machine frame from bottom to top, respectively performing reverse-order integration on the machine height H of all the machine positions meeting the constraint condition to obtain a fifth integral; and respectively summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral of each machine position, and sequencing all summation results.
It should be noted that the positive-sequence integral in this embodiment means that the obtained score is positively correlated with a specific numerical value of the machine position resource information associated with the optimization target, and the negative-sequence integral is negatively correlated, as shown in tables 1 and 2, which are respectively an optional integral table with positive sequence arrangement and an optional integral table with reverse sequence arrangement. It should also be understood that, in practical applications, the optimization goal may of course be only a single optimization goal, and the corresponding output result is relatively coarse.
TABLE 1
| Positive sequence arrangement | The obtained score |
| 1 st position | 100 |
| Position 2 | 80 |
| Position 3 | 60 |
| Position 4 | 40 |
| Position 5 | 20 |
TABLE 2
| Reverse order arrangement | The obtained score |
| 1 st bit of the last | 100 |
| 2 nd from last | 80 |
| 3 rd bit of last | 60 |
| 4 th from last | 40 |
| 5 th from last | 20 |
In an optional implementation manner of this embodiment, weighting factors are respectively assigned to the first integral, the second integral, the third integral, the fourth integral, and the fifth integral; and summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral after the weighting factors are configured on each machine position respectively, and sequencing all summation results.
Specifically, since the present embodiment has a plurality of optimization targets, and in practical applications, the importance of each optimization target is different, so that the important optimization targets react more prominently on the result by correspondingly weighting the integral values of the optimization targets in the present embodiment.
In an optional implementation manner of this embodiment, corresponding weighting factors are respectively assigned to the first integral, the second integral, the third integral, the fourth integral, and the fifth integral according to the priority order of the first optimization goal, the second optimization goal, the third optimization goal, the fourth optimization goal, and the fifth optimization goal.
Specifically, in this embodiment, a corresponding priority is set for the importance of the optimization target, and then a weighting factor is further corresponding according to the difference of the priorities, where the higher the importance of the optimization target is, the higher the priority is, and the larger the corresponding weighting factor is.
104, determining a target machine position from all machine positions according to the sequencing result, and outputting machine position identification information corresponding to the target machine position; the airplane position identification information is used for identifying the physical position of the airplane position.
Specifically, in this embodiment, an optimal machine location is selected as a target machine location according to the sorting result, and then machine location identification information of the selected machine location is output to indicate the physical location of the target machine location to the user, where the machine location identification information may be composed of a machine room number, a first cabinet number, a rack number, and a rack location.
In an optional implementation manner of this embodiment, a plurality of selectable target positions are determined from all the positions according to the sorting result, and the position identification information corresponding to the plurality of selectable target positions is output.
Specifically, in this embodiment, a plurality of target machine positions are finally determined, so that a plurality of target machine positions are output at the same time for the user to select, that is, the overall network device location determination process of this embodiment only provides a reference for the user and provides a choice for the user, and may further meet the special and personalized requirements of the user to a certain extent, for example, in this embodiment, three optimal machine positions may be determined and then provided for the user, and finally, the user performs one of three selections according to personal wishes. It should be noted that, in other embodiments, of course, a unique target position may also be determined directly from the sorting result, so that the unique target position is a position where the end user deploys the network device.
It should be understood that, in this embodiment, after the network device to be deployed is deployed to the machine according to the output result, the machine resource information base inside the system is also updated, so as to record the occupied machine resource information, thereby ensuring the accuracy when other network devices are subsequently deployed.
According to the method for determining the position of the network equipment, provided by the embodiment of the invention, the machine positions with the machine position resource information meeting the condition are screened out from all the idle machine positions through the constraint condition of the resource demand information associated with the network equipment to be deployed, and then the optimal machine positions are selected from the screened machine positions according to the optimization target associated with the machine position resource information. On one hand, the real-time machine position resources and the actual demand information are subjected to quantization processing and then input into the machine position selection model provided by the embodiment to output the optimal machine position, so that the balanced allocation of the machine position resources is realized; on the other hand, because the final determination of the target machine position is realized strictly through the machine position selection model and automatically by the computer program, compared with the prior art which mainly depends on the experience and level of technical personnel, the efficiency and the objectivity of equipment deployment are improved.
Second embodiment:
in order to more intuitively understand the method for determining the location of the network device in the embodiment of the present invention, an embodiment of the present invention further provides a refined method for determining the location of the network device, as shown in fig. 2, which is a schematic detailed flow chart of the method for determining the location of the network device provided in this embodiment, and the method for determining the location of the network device provided in this embodiment includes the following steps:
the resource requirement information in this embodiment may include: power consumption, cold consumption, number of terminals occupying power supply and number of machine bits occupied.
in this embodiment, the machine level resource information may include: the residual electric quantity of the power supply system to which the machine position belongs, the residual electric quantity of the column head cabinet to which the machine position belongs, the residual electric quantity of the rack to which the machine position belongs, the residual cold quantity of the machine room to which the machine position belongs, the residual power supply terminal number of the rack to which the machine position belongs, the idle machine position number of the rack to which the machine position belongs and the height of the machine position. In addition, the machine position resource information base in this embodiment includes machine position resource information of all currently idle machine positions, where the machine position resource information is used to represent machine position attributes of the machine positions.
the optimization objectives of this embodiment may include: balancing the residual electric quantity of all power supply systems, balancing the residual electric quantity of all column head cabinets, deploying used racks preferentially, balancing the residual cold quantity of all machine rooms and deploying the racks from bottom to top. The weighting factors for weighting the integrals are associated with the priorities of the optimization targets, and the higher the importance of the optimization targets is, the higher the priority of the optimization targets is, the larger the weighting factors are.
in this embodiment, a plurality of target positions, that is, optimal positions, are output at the same time for the user to select, that is, the overall network device location determination process of this embodiment only provides a reference for the user and provides a choice for the user, and may further meet the special and personalized requirements of the user to a certain extent.
And step 207, after determining that the network device to be deployed is deployed to one of the output multiple optional target machine positions, adaptively updating the machine position resource information base.
According to the method for determining the position of the network equipment, provided by the embodiment of the invention, the machine positions with the machine position resource information meeting the condition are screened out from all the idle machine positions through the constraint condition of the resource demand information associated with the network equipment to be deployed, and then the optimal machine positions are selected from the screened machine positions according to the optimization target associated with the machine position resource information. On one hand, the real-time machine position resources and the actual demand information are subjected to quantization processing and then input into the machine position selection model provided by the embodiment to output the optimal machine position, so that the balanced allocation of the machine position resources is realized; on the other hand, because the final determination of the target machine position is realized strictly through the machine position selection model and automatically by the computer program, compared with the prior art which mainly depends on the experience and level of technical personnel, the method has the advantages that the efficiency and the objectivity of equipment deployment are improved, and the user experience is improved.
Second embodiment:
the present embodiment shows a network device location determining apparatus, and with specific reference to fig. 3, in order to solve the technical problems in the prior art that equilibrium utilization of machine room resources is difficult to achieve, a scheme is time-consuming to make, and a scheme has strong subjectivity due to relying on manual site survey of a machine room and design of a deployment location of a network device, the network device location determining apparatus of the present embodiment includes:
a requirement determining module 301, configured to determine resource requirement information of a network device to be deployed;
a condition judgment module 302, configured to judge whether there is a machine position in which the machine position resource information meets the constraint condition according to the constraint condition associated with the resource demand information;
the integral sorting module 303 is configured to, when there is a machine position that meets the constraint condition, perform integral sorting on all machine positions that meet the constraint condition according to an optimization target associated with the machine position resource information;
a position determining module 304, configured to determine a target machine position from all machine positions according to the sorting result, and output machine position identification information corresponding to the target machine position; the airplane position identification information is used for identifying the physical position of the airplane position.
Specifically, the resource demand information in this embodiment refers to resource information that needs to occupy the machine room after the network device is deployed to the machine room, and the machine location resource information is used to represent the machine location attribute of the machine location. In addition, in this embodiment, if there is no machine location meeting the constraint condition, it indicates that there is no available machine location to deploy the current network device, and the demand end may return to modify the resource demand information again; and when the positions meeting the constraint condition exist, further determining the optimal position from the screened positions according to the optimization target.
In some embodiments of this embodiment, the resource requirement information includes: power consumption, cold consumption, the number of occupied power supply terminals and the number of occupied machine positions; the machine position resource information comprises: the residual electric quantity of the machine frame to which the machine position belongs, the residual cold quantity of the machine room to which the machine position belongs, the residual power supply terminal number of the machine frame to which the machine position belongs and the idle machine position number of the machine frame to which the machine position belongs.
In other embodiments of this embodiment, the machine position resource information further includes: the residual electric quantity of the power supply system to which the machine position belongs, the residual electric quantity of the first cabinet of the column to which the machine position belongs and the height of the machine position.
In some embodiments of this embodiment, the constraint is: the machine resource information meets all kinds of requirements in the resource requirement information.
In some embodiments of this embodiment, the optimization objective comprises: balancing the residual electric quantity of all power supply systems, balancing the residual electric quantity of all column head cabinets, deploying used racks preferentially, balancing the residual cold quantity of all machine rooms and deploying the racks from bottom to top. Correspondingly, the machine room resource information required to be acquired in this embodiment includes: the residual electricity quantity P1 of the machine frame belonging to the machine position, the residual cold quantity C of the machine room belonging to the machine position, the residual power supply terminal number T of the machine frame belonging to the machine position, the idle machine position number S of the machine frame belonging to the machine position, the residual electricity quantity P2 of the power supply system belonging to the machine position, the residual electricity quantity P3 of the head cabinet of the column belonging to the machine position and the height H of the machine position.
Therefore, the integral sorting module 303 of this embodiment is specifically configured to perform positive sequence integration on the remaining electric quantities of the power supply systems to which the stands of all stands that meet the constraint condition belong, respectively, according to a first optimization goal of balancing the remaining electric quantities of all the power supply systems, so as to obtain first integrals; respectively performing positive sequence integration on the residual electric quantity of the first column cabinet to which the machine positions of all the machine positions which meet the constraint condition belong according to a balanced second optimization target of the residual electric quantity of all the first column cabinets to obtain second integration; respectively performing reverse integration on the residual electric quantity of the machine frame to which the machine positions of all the machine positions which meet the constraint condition belong and/or the idle machine position number of the machine frame to which each machine position belongs according to a third optimization target of the prior deployment of the used machine frame to obtain a third integral; according to a fourth optimization target of the balance of the residual cold quantities of all the machine rooms, respectively performing positive sequence integration on the residual cold quantities of the machine rooms to which the machine positions of all the machine positions in accordance with the constraint conditions belong to obtain fourth integrals; according to a fifth optimization target of the machine frame from bottom to top, respectively performing reverse integration on the machine height of all the machine positions meeting the constraint condition to obtain a fifth integration; and then summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral of each machine position respectively, and sequencing all summation results.
Further, in other embodiments of this embodiment, the integral sorting module 303 is specifically configured to, after determining the first integral, the second integral, the third integral, the fourth integral and the fifth integral, assign weighting factors to the first integral, the second integral, the third integral, the fourth integral and the fifth integral, respectively; and summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral after the weighting factors are configured on each machine position respectively, and sequencing all summation results.
Further, in still other embodiments of this embodiment, the integral sorting module 303 is specifically configured to, after determining the first integral, the second integral, the third integral, the fourth integral and the fifth integral, respectively assign corresponding weighting factors to the first integral, the second integral, the third integral, the fourth integral and the fifth integral according to the priority order of the first optimization goal, the second optimization goal, the third optimization goal, the fourth optimization goal and the fifth optimization goal; and summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral after the weighting factors are configured on each machine position respectively, and sequencing all summation results.
In some embodiments of the present embodiment, the position determining module 304 is specifically configured to determine a plurality of selectable target positions from all the positions according to the sorting result, and output the position identification information corresponding to the plurality of selectable target positions.
In some embodiments of this embodiment, the system further includes a resource updating module, configured to adaptively update the machine seat resource information base after determining that the network device to be deployed is deployed to the machine seat.
It should be noted that, the network device location determining methods in the first and second embodiments can be implemented based on the network device location determining apparatus provided in this embodiment, and it can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working process of the network device location determining apparatus described in this embodiment may refer to the corresponding process in the foregoing method embodiment, and details are not described here.
By using the network device location determining apparatus provided in this embodiment, the machine positions with the machine position resource information meeting the condition are screened from all the idle machine positions through the constraint condition of the resource demand information associated with the network device to be deployed, and then the optimal machine position is selected from the screened machine positions according to the optimization target associated with the machine position resource information. On one hand, the real-time machine position resources and the actual demand information are subjected to quantization processing and then input into the machine position selection model provided by the embodiment to output the optimal machine position, so that the balanced allocation of the machine position resources is realized; on the other hand, because the final determination of the target machine position is realized strictly through the machine position selection model and automatically by the computer program, compared with the prior art which mainly depends on the experience and level of technical personnel, the efficiency and the objectivity of equipment deployment are improved.
The third embodiment:
the present embodiment provides an electronic device, as shown in fig. 4, which includes a processor 401, a memory 402, and a communication bus 403, wherein: the communication bus 403 is used for realizing connection communication between the processor 401 and the memory 402; the processor 401 is configured to execute one or more computer programs stored in the memory 402 to implement at least one step of the network device location determination method in the first and/or second embodiments.
The present embodiments also provide a computer-readable storage medium including volatile or non-volatile, removable or non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, computer program modules or other data. Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash Memory or other Memory technology, CD-ROM (Compact disk Read-Only Memory), Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.
The computer-readable storage medium in this embodiment may be used for storing one or more computer programs, and the stored one or more computer programs may be executed by a processor to implement at least one step of the method in the above-mentioned embodiment one and/or two.
The present embodiment also provides a computer program, which can be distributed on a computer readable medium for execution by a computing device to implement at least one step of the method of the first and/or second embodiment; and in some cases at least one of the steps shown or described may be performed in an order different than that described in the embodiments above.
The present embodiments also provide a computer program product comprising a computer readable means on which a computer program as shown above is stored. The computer readable means in this embodiment may include a computer readable storage medium as shown above.
It will be apparent to those skilled in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software (which may be implemented in computer program code executable by a computing device), firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit.
In addition, communication media typically embodies computer readable instructions, data structures, computer program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to one of ordinary skill in the art. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a more detailed description of embodiments of the present invention, and the present invention is not to be considered limited to such descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (8)
1. A method for determining a location of a network device, comprising:
determining resource demand information of network equipment to be deployed; wherein the resource requirement information comprises: power consumption, cold consumption, the number of occupied power supply terminals and the number of occupied machine positions;
judging whether a machine position with machine position resource information meeting the constraint condition exists according to the constraint condition associated with the resource demand information; wherein the machine position resource information comprises: the residual electric quantity of the machine frame to which the machine position belongs, the residual cold quantity of the machine room to which the machine position belongs, the number of residual power supply terminals of the machine frame to which the machine position belongs, the number of idle machine positions of the machine frame to which the machine position belongs, the residual electric quantity of a power supply system to which the machine position belongs, the residual electric quantity of a column head cabinet to which the machine position belongs and the height of the machine position;
when the machine positions meeting the constraint conditions exist, performing integral sequencing on all the machine positions meeting the constraint conditions according to an optimization target related to machine position resource information; wherein the optimization objective comprises: balancing the residual electric quantity of all power supply systems, balancing the residual electric quantity of all column head cabinets, deploying used racks preferentially, balancing the residual cold quantity of all machine rooms and deploying the racks from bottom to top;
determining a target machine position from all the machine positions according to the sequencing result, and outputting machine position identification information corresponding to the target machine position; the machine position identification information is used for identifying the physical position of the machine position;
wherein the performing, according to the optimization objective associated with the machine position resource information, the integral ordering of all machine positions meeting the constraint condition includes:
respectively performing positive sequence integration on the residual electric quantities of the power supply systems to which the stands of all stands in accordance with the constraint condition according to a balanced first optimization target of the residual electric quantities of all the power supply systems to obtain first integrals; respectively performing positive sequence integration on the residual electric quantity of the first column cabinet to which the machine positions of all the machine positions which meet the constraint condition belong according to a balanced second optimization target of the residual electric quantity of all the first column cabinets to obtain second integration; according to a third optimization target of the used machine frame in preferential deployment, respectively performing reverse integration on the residual electric quantity of the machine frame to which the machine positions of all the machine positions which meet the constraint condition belong and/or the number of idle machine positions of the machine frame to which each machine position belongs to obtain a third integral; respectively performing positive sequence integration on the residual cold quantities of the machine rooms to which the machine positions of all the machine positions in accordance with the constraint condition belong according to a balanced fourth optimization target of the residual cold quantities of all the machine rooms to obtain a fourth integral; according to a fifth optimization target deployed from bottom to top of the rack, respectively performing reverse-order integration on the heights of all the machine positions meeting the constraint condition to obtain a fifth integral;
and summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral of each machine position respectively, and sequencing all summation results.
2. The method of network device location determination according to claim 1, wherein the constraints are: the machine resource information meets all kinds of requirements in the resource requirement information.
3. The method of claim 1, wherein summing the first, second, third, fourth, and fifth integrals for each machine position, respectively, and ordering the results of the summing comprises:
respectively assigning weighting factors to the first integral, the second integral, the third integral, the fourth integral and the fifth integral;
and summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral after the weighting factors are configured for each machine position respectively, and sequencing all summation results.
4. The network device location determination method of claim 3, wherein the assigning weighting factors to the first integral, the second integral, the third integral, the fourth integral, and the fifth integral, respectively, comprises:
and respectively allocating corresponding weighting factors to the first integral, the second integral, the third integral, the fourth integral and the fifth integral according to the priority order of the first optimization target, the second optimization target, the third optimization target, the fourth optimization target and the fifth optimization target.
5. The method according to any one of claims 1 to 4, wherein the determining a target machine position from all the machine positions according to the sorting result and outputting machine position identification information corresponding to the target machine position comprises:
and determining a plurality of selectable target machine positions from all the machine positions according to the sequencing result, and outputting machine position identification information corresponding to the plurality of selectable target machine positions.
6. A network device location determining apparatus, comprising:
the demand determining module is used for determining resource demand information of the network equipment to be deployed; wherein the resource requirement information comprises: power consumption, cold consumption, the number of occupied power supply terminals and the number of occupied machine positions;
the condition judgment module is used for judging whether the machine position with the machine position resource information meeting the constraint condition exists or not according to the constraint condition associated with the resource demand information; wherein the machine position resource information comprises: the residual electric quantity of the machine frame to which the machine position belongs, the residual cold quantity of the machine room to which the machine position belongs, the number of residual power supply terminals of the machine frame to which the machine position belongs, the number of idle machine positions of the machine frame to which the machine position belongs, the residual electric quantity of a power supply system to which the machine position belongs, the residual electric quantity of a column head cabinet to which the machine position belongs and the height of the machine position;
the integral sequencing module is used for carrying out integral sequencing on all the machine positions meeting the constraint condition according to an optimization target related to the machine position resource information when the machine positions meeting the constraint condition exist; wherein the optimization objective comprises: balancing the residual electric quantity of all power supply systems, balancing the residual electric quantity of all column head cabinets, deploying used racks preferentially, balancing the residual cold quantity of all machine rooms and deploying the racks from bottom to top;
the position determining module is used for determining a target machine position from all the machine positions according to the sequencing result and outputting machine position identification information corresponding to the target machine position; the machine position identification information is used for identifying the physical position of the machine position;
the integral sorting module is specifically configured to: respectively performing positive sequence integration on the residual electric quantities of the power supply systems to which the stands of all stands in accordance with the constraint condition according to a balanced first optimization target of the residual electric quantities of all the power supply systems to obtain first integrals; respectively performing positive sequence integration on the residual electric quantity of the first column cabinet to which the machine positions of all the machine positions which meet the constraint condition belong according to a balanced second optimization target of the residual electric quantity of all the first column cabinets to obtain second integration; according to a third optimization target of the used machine frame in preferential deployment, respectively performing reverse integration on the residual electric quantity of the machine frame to which the machine positions of all the machine positions which meet the constraint condition belong and/or the number of idle machine positions of the machine frame to which each machine position belongs to obtain a third integral; respectively performing positive sequence integration on the residual cold quantities of the machine rooms to which the machine positions of all the machine positions in accordance with the constraint condition belong according to a balanced fourth optimization target of the residual cold quantities of all the machine rooms to obtain a fourth integral; according to a fifth optimization target deployed from bottom to top of the rack, respectively performing reverse-order integration on the heights of all the machine positions meeting the constraint condition to obtain a fifth integral; and summing the first integral, the second integral, the third integral, the fourth integral and the fifth integral of each machine position respectively, and sequencing all summation results.
7. An electronic device, comprising: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute one or more programs stored in the memory to implement the steps of the network device location determination method according to any one of claims 1 to 5.
8. A computer-readable storage medium, having one or more programs stored thereon which are executable by one or more processors to perform the steps of the network device location determination method of any one of claims 1 to 5.
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| CN111158917A (en) * | 2019-12-31 | 2020-05-15 | 新浪网技术(中国)有限公司 | Resource management method and system for internet data center |
| CN113094325B (en) * | 2021-04-14 | 2024-02-20 | 中国工商银行股份有限公司 | Device deployment method, device, computer system and computer readable storage medium |
| CN116468199B (en) * | 2023-04-18 | 2024-03-19 | 北京众谊越泰科技有限公司 | Intelligent on-shelf position prediction method based on U-bit asset management system |
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