CN117479235B - Scheduling management method and system for terminal network facilities - Google Patents
Scheduling management method and system for terminal network facilities Download PDFInfo
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- 238000007726 management method Methods 0.000 title claims abstract description 19
- 230000002093 peripheral effect Effects 0.000 claims abstract description 72
- 238000000034 method Methods 0.000 claims abstract description 70
- 238000005265 energy consumption Methods 0.000 claims abstract description 28
- 238000012804 iterative process Methods 0.000 claims description 20
- 238000010586 diagram Methods 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 13
- 238000004458 analytical method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
- H04W28/09—Management thereof
- H04W28/0958—Management thereof based on metrics or performance parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
- H04W28/09—Management thereof
- H04W28/0925—Management thereof using policies
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
Abstract
The invention relates to the technical field of local facility management, and particularly discloses a peripheral network facility scheduling management method and a peripheral network facility scheduling management system, wherein the method comprises the steps of updating equipment types and equipment positions in real time, and creating peripheral nodes according to the equipment types and the equipment positions; establishing a connection channel with a task set, identifying tasks in the task set, extracting task labels, and obtaining a label set; selecting a peripheral node according to the task label, connecting the peripheral node, and determining a task flow; and counting the task flow in real time, calculating the energy consumption, and updating the determination process of the task flow according to the energy consumption. The task processing network is represented by the two-dimensional layers, the task adjustment problem is converted into the point position selection problem among the layers, when the task processing network is updated, the corresponding two-dimensional layers are only required to be updated, and the original point position selection scheme is adopted, so that a new processing scheme can be quickly obtained, and the flexibility is extremely high.
Description
Technical Field
The invention relates to the technical field of local facility management, in particular to a peripheral network facility scheduling management method and system.
Background
The peripheral network includes a sensor network, a wireless sensor network, an industrial control network, various short-range wireless communication networks, and the like. The sensing node and the peripheral network have the functions of information acquisition, control task and the like of the Internet of things. In popular terms, it is a clustered task processing network, and under the very mature condition of WLAN technology, the same task can be processed in different ways in the task processing network, and this time, scheduling problems are involved.
The existing method for solving the scheduling problem is generally a pre-scheme solving way, namely, each type of task is pre-planned, the solution is determined, when a new problem is received, the task is identified and classified, and the corresponding solution is queried; the distribution speed of the scheme is extremely high, but the flexibility is slightly insufficient, when the task processing network is updated or the task is changed greatly, the original solution is difficult to change rapidly, and the task processing network needs to be updated automatically by staff according to new conditions; how to improve the scheduling flexibility when facing to updating scenes is a technical problem to be solved by the technical scheme of the invention.
Disclosure of Invention
The invention aims to provide a scheduling management method and system for a peripheral network facility, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a method of scheduling management of a peripheral network facility, the method comprising:
updating the equipment type and the equipment position in real time, and creating a peripheral node according to the equipment type and the equipment position;
establishing a connection channel with a task set, identifying tasks in the task set, extracting task labels, and obtaining a label set; the task labels are in one-to-one correspondence with the equipment types, and the task labels in the label set contain sequences;
selecting a peripheral node according to the task label, connecting the peripheral node, and determining a task flow;
counting task flows in real time, calculating energy consumption, and updating a determining process of the task flows according to the energy consumption;
the process of determining the task flow at least comprises parameters reflecting node idleness and parameters reflecting node performance.
As a further scheme of the invention: the step of updating the equipment type and the equipment position in real time and creating the peripheral node according to the equipment type and the equipment position comprises the following steps:
receiving the type and the position of the equipment uploaded by the user in real time based on the equipment table;
reading an area map, determining a point position numerical value according to the type of the equipment, and determining a point position coordinate according to the position of the equipment;
inserting the point position numerical value into a point position coordinate to serve as a peripheral node, and obtaining a region real graph;
the regional map comprises a regional marking port used for receiving a regional range and a regional type input by a user.
As a further scheme of the invention: selecting a peripheral node according to the task label, connecting the peripheral node, and determining the task flow comprises the following steps:
counting task labels related to all label sets, and sequentially inquiring the equipment types and point position values corresponding to each task label;
traversing the real map of the region according to the point position value, and marking a target point position;
counting the target points, creating a node map layer with the same size as the real map of the region, and taking task labels as indexes;
iteratively calculating the task flow of each tag set based on the node diagram layer until the iteration jumps out of the conditions; the iteration jump condition comprises that the iteration times reach a preset time threshold value and the longest predicted time consumption of all task flows is smaller than the preset time consumption threshold value.
As a further scheme of the invention: the step of iteratively calculating the task flow of each tab set based on the node diagram layer until the iteration jump-out condition comprises the following steps:
randomly selecting a tag set, and sequentially reading task tags in the tag set;
inquiring a node map layer corresponding to the task label, and selecting a peripheral node based on the selection probability of each point; wherein the selection process affects the selection probability;
when the task labels of the label set are read, connecting the peripheral nodes to obtain a task flow;
counting task flows of all tag sets, and judging whether iteration jump conditions are reached;
the selection probability is as follows:
；/>；
in the method, in the process of the invention,probability of choosing for the j-th point in a node map layer,/for each node map layer>For the degree of idleness of the j-th point, +.>For the performance parameter of the j-th point, +.>And->The weight coefficient is preset; />For t+1th iteration process, the idleness of the jth point is +.>Is a preset volatilization speed; />The idle degree of the jth point in the t iterative processes is calculated, and m is the total number of times of selecting the jth point in the t iterative processes; />And selecting the occupancy rate of the jth point for the kth point in the t iterative processes.
As a further scheme of the invention: the step of counting the task flows of all the tag sets and judging whether the iteration jump condition is reached comprises the following steps:
inquiring equipment corresponding to the task flow, and predicting the completion time according to the equipment parameters;
comparing the completion time of different task flows, and determining the longest predicted time consumption;
when the longest predicted time consumption is greater than a preset time consumption threshold, reserving selection probability, and performing loop iteration;
when the longest predicted time is smaller than a preset time consumption threshold, judging that an iteration jump condition is reached;
and recording the iteration times in real time, and judging that the iteration jump condition is reached when the iteration times reach a preset time threshold.
As a further scheme of the invention: the step of counting the task flow in real time, calculating the energy consumption and updating the determining process of the task flow according to the energy consumption comprises the following steps:
counting all task flows in real time, inquiring equipment corresponding to the task flows, and calculating predicted energy consumption according to equipment parameters;
correcting a calculation process of the selection probability according to the predicted energy consumption; the correction mode comprises an addition parameter and an adjustment parameter.
The technical scheme of the invention relates to a dispatching management system for a peripheral network facility, which comprises the following components:
the terminal node creation module is used for updating the equipment type and the equipment position in real time and creating a terminal node according to the equipment type and the equipment position;
the task identification module is used for establishing a connection channel with the task set, identifying the tasks in the task set, extracting task labels and obtaining a label set; the task labels are in one-to-one correspondence with the equipment types, and the task labels in the label set contain sequences;
the task flow determining module is used for selecting a peripheral node according to the task label, connecting the peripheral node and determining a task flow;
the determining process updating module is used for counting the task flow in real time, calculating the energy consumption and updating the determining process of the task flow according to the energy consumption;
the process of determining the task flow at least comprises parameters reflecting node idleness and parameters reflecting node performance.
As a further scheme of the invention: the tip node creation module includes:
the device information receiving unit is used for receiving the device type and the device position uploaded by the user in real time based on the device table;
the point location mapping unit is used for reading the regional map, determining point location numerical values according to the equipment types and determining point location coordinates according to the equipment positions;
the point position inserting unit is used for inserting the point position numerical value into a point position coordinate as a peripheral node to obtain a region real graph;
the regional map comprises a regional marking port used for receiving a regional range and a regional type input by a user.
As a further scheme of the invention: the task flow determination module comprises:
the query unit is used for counting task labels related to all label sets and sequentially querying the equipment types and the point position values corresponding to each task label;
the traversing marking unit is used for traversing the real map of the region according to the point position value and marking the target point position;
the layer creation unit is used for counting the target point positions, creating a node layer with the same size as the real map of the region, and taking the task label as an index;
the iteration execution unit is used for iteratively calculating the task flow of each tag set based on the node diagram layer until the iteration jump-out condition; the iteration jump condition comprises that the iteration times reach a preset time threshold value and the longest predicted time consumption of all task flows is smaller than the preset time consumption threshold value.
As a further scheme of the invention: the iteration execution unit includes:
the reading subunit is used for randomly selecting a label set and sequentially reading task labels in the label set;
a selecting subunit, configured to query a node map layer corresponding to the task label, and select a peripheral node based on a selection probability of each point; wherein the selection process affects the selection probability;
the connection subunit is used for connecting the peripheral nodes to obtain a task flow when the task labels of the label set are read;
the judging subunit is used for counting task flows of all the tag sets and judging whether iteration jump conditions are reached;
the selection probability is as follows:
；/>；
in the method, in the process of the invention,probability of choosing for the j-th point in a node map layer,/for each node map layer>For the degree of idleness of the j-th point, +.>For the performance parameter of the j-th point, +.>And->The weight coefficient is preset; />For t+1th iteration process, the idleness of the jth point is +.>Is a preset volatilization speed; />The idle degree of the jth point in the t iterative processes is calculated, and m is the total number of times of selecting the jth point in the t iterative processes; />And selecting the occupancy rate of the jth point for the kth point in the t iterative processes.
Compared with the prior art, the invention has the beneficial effects that: the task processing network is represented by the two-dimensional layers, the task adjustment problem is converted into the point position selection problem among the layers, when the task processing network is updated, the corresponding two-dimensional layers are only required to be updated, and the original point position selection scheme is adopted, so that a new processing scheme can be quickly obtained, and the flexibility is extremely high.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
FIG. 1 is a flow diagram of a method for scheduling management of a peripheral network facility.
Fig. 2 is a flow chart of step S100.
Fig. 3 is a flow chart of step S300.
Fig. 4 is a flow chart of step S400.
FIG. 5 is a block diagram showing the structure of a peripheral network facility scheduling management system.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Fig. 1 is a flow chart of a method for scheduling and managing a peripheral network facility, and in an embodiment of the present invention, a method for scheduling and managing a peripheral network facility includes:
step S100: updating the equipment type and the equipment position in real time, and creating a peripheral node according to the equipment type and the equipment position;
the peripheral network comprises a sensor network, a wireless sensor network, an industrial control network, various short-distance wireless communication networks and the like, and is often used for limiting an area, wherein the limited area is a server cluster, a large number of electronic devices are contained in the server cluster, all the electronic devices are counted, the positions and the types of the electronic devices are acquired, and the electronic devices can be represented by a map, the map comprises a plurality of points, namely peripheral nodes, and the peripheral nodes correspond to the devices.
Because the electronic devices in the server cluster have replacement requirements (replacement frequency is different), the process of creating the tip node is a process of updating in real time.
Step S200: establishing a connection channel with a task set, identifying tasks in the task set, extracting task labels, and obtaining a label set; the task labels are in one-to-one correspondence with the equipment types, and the task labels in the label set contain sequences;
each server cluster has a task list, namely the task set, wherein the tasks in the task set are tasks to be completed in the future, each task is read in sequence, and the electronic equipment related to each task is queried, so that task labels are obtained, and the tasks are converted into a task label set.
It should be noted that, the task sets with the same task labels but different ordering orders are different.
Step S300: selecting a peripheral node according to the task label, connecting the peripheral node, and determining a task flow;
selecting a peripheral node from the determined map containing the point positions according to the task labels, and connecting the peripheral node to obtain a path, wherein the path is a two-dimensional representation form of the task flow; and carrying out iterative analysis on the task flow in the two-dimensional representation form, and determining the final task flow.
Step S400: counting task flows in real time, calculating energy consumption, and updating a determining process of the task flows according to the energy consumption;
based on the above, a global judgment condition is added for the task flow selection process, all task flows are analyzed, fine adjustment is further performed in step S300, and the determination accuracy of the task flows is changed.
It should be noted that, the determining process of the task flow at least includes parameters reflecting the node idle degree and parameters reflecting the node performance, and the practical significance is that when selecting the device, the idle device is preferentially selected, and the device with high performance is preferentially selected.
It should be noted that, in the technical solution of the present invention, the server cluster includes different types of electronic devices, and the number of each type of electronic device is not unique, so that a solution of the same task (task flow is not unique) has an optimal flow and multiple preferred flows.
Fig. 2 is a flowchart of step S100, where the step of updating the device type and the device position in real time and creating the tip node according to the device type and the device position includes:
step S101: receiving the type and the position of the equipment uploaded by the user in real time based on the equipment table;
step S102: reading an area map, determining a point position numerical value according to the type of the equipment, and determining a point position coordinate according to the position of the equipment;
step S103: inserting the point position numerical value into a point position coordinate to serve as a peripheral node, and obtaining a region real graph;
the regional map comprises a regional marking port used for receiving a regional range and a regional type input by a user.
The above specifically defines the process of creating the peripheral node, and firstly, an equipment table is created, wherein the equipment table contains an input port, and the input port receives the equipment type and the equipment position input by a user; at this time, the device table plays a role of buffering. Then, inquiring the point position value according to the equipment type, wherein the meaning of the step is that the equipment type is represented by the value in the image; the device types include a graphic processing device, a character string processing device, an audio processing device, and the like; and finally, selecting the pixel points corresponding to the electronic equipment as peripheral nodes according to the map and the actual position mapping relation.
In colloquial terms, the above-mentioned process of generating a real map of an area can be understood as changing the value of a point location corresponding to an electronic device in an image in which the values of all the point locations are the same.
FIG. 3 is a block flow diagram of step S300, wherein the steps of selecting a peripheral node according to a task tag, connecting the peripheral node, and determining a task flow include:
step S301: counting task labels related to all label sets, and sequentially inquiring the equipment types and point position values corresponding to each task label;
step S302: traversing the real map of the region according to the point position value, and marking a target point position;
step S303: counting the target points, creating a node map layer with the same size as the real map of the region, and taking task labels as indexes;
step S304: iteratively calculating the task flow of each tag set based on the node diagram layer until the iteration jumps out of the conditions; the iteration jump condition comprises that the iteration times reach a preset time threshold value and the longest predicted time consumption of all task flows is smaller than the preset time consumption threshold value.
Step S301 to step S304 provide a specific task flow determining scheme, and the task flow generating process is a core scheme of the technical scheme of the present invention, and the flow is as follows:
and extracting the point positions with the same numerical value in the real map of the region to obtain a plurality of node map layers, wherein the node map layers take task labels as indexes, at the moment, each node map layer represents the distribution condition of various electronic equipment, and all the node map layers are mutually overlapped to obtain the real map of the region.
After the node diagram layer is generated, determining a task flow based on the node diagram layer; the process of determining the task flow is a multi-time circulation process, the task flow is continuously determined, and then the determination process is subjected to recursion adjustment, so that a better scheme meeting certain conditions can be finally obtained.
Specifically, the step of iteratively calculating the task flow of each tag set based on the node map layer until the iteration jump-out condition includes:
randomly selecting a tag set, and sequentially reading task tags in the tag set;
inquiring a node map layer corresponding to the task label, and selecting a peripheral node based on the selection probability of each point; wherein the selection process affects the selection probability;
when the task labels of the label set are read, connecting the peripheral nodes to obtain a task flow;
counting task flows of all tag sets, and judging whether iteration jump conditions are reached;
the above-mentioned contents define step S304 (task flow is determined based on node diagram layer), the tag set itself contains an order, the node diagram layer is queried based on the order, the terminal node is selected in the queried node diagram layer, the parameter of selection probability is introduced in the selection process, the terminal node is selected under the selection probability, and the process is repeated continuously, so as to obtain the task flow.
On the basis, the selection probability is adjusted according to all the selection processes, and the processes are repeated, so that a plurality of proper task flows can be obtained and used for completing the tasks in the task set.
Wherein, the selection probability is:
；/>；
in the method, in the process of the invention,probability of choosing for the j-th point in a node map layer,/for each node map layer>For the degree of idleness of the j-th point, +.>For the performance parameter of the j-th point, +.>And->The weight coefficient is preset; />For t+1th iteration process, the idleness of the jth point is +.>Is a preset volatilization speed; />The idle degree of the jth point in the t iterative processes is calculated, and m is the total number of times of selecting the jth point in the t iterative processes; />And selecting the occupancy rate of the jth point for the kth point in the t iterative processes.
The description about the selection probability is specifically as follows:
the term reflects the idle condition of the peripheral node, +.>The item reflects the performance parameters of the equipment corresponding to the tip node, and the larger the two items are, the larger the selection probability is; on the basis, the basic rule of the calculation process of the idle condition is that the more times are selected, the lower the idle degree is, and correspondingly, the lower the selection probability is.
In the course of the calculation of the degree of idleness,reflects the influence of single selection on idle conditions, and the more the selection times are, the more the selection times are>The smaller the item is->The smaller the term.
Further, the method comprises the steps of,items are data which are introduced and reflect the change condition of the idle degree, tasks are continuously processed along with the time, and the idle degree is increased.
Furthermore, regarding t and t+1, the t and t+1 are used to characterize the determined relationship, i.e. each time the probability of choosing is determined by the previous iteration process, which can simplify the calculation process; of course, there is also a way to record the selecting times of the j-th point in real time, and accumulate the occupancy rate according to the selecting times for replacingAn item.
As a preferred embodiment of the technical solution of the present invention, the step of counting task flows of all tag sets and determining whether an iteration-jump condition is reached includes:
inquiring equipment corresponding to the task flow, and predicting the completion time according to the equipment parameters;
comparing the completion time of different task flows, and determining the longest predicted time consumption;
when the longest predicted time consumption is greater than a preset time consumption threshold, reserving selection probability, and performing loop iteration;
when the longest predicted time is smaller than a preset time consumption threshold, judging that an iteration jump condition is reached;
and recording the iteration times in real time, and judging that the iteration jump condition is reached when the iteration times reach a preset time threshold.
The above-mentioned contents define the loop jump-out condition of the loop iteration process, and the judging conditions are two, one is a time condition and the other is a frequency condition; specifically, the total duration of all task flows is calculated once after each iteration is finished, if the total duration does not reach the standard, the iteration is continued, and if the total duration is small enough, the iteration is jumped out.
On this basis, if the total duration does not reach the standard all the time, but the iteration times are enough, the iteration can be jumped out.
It should be noted that the above-mentioned iteration-jump condition may also have other conditions, for example, the difference between the predicted completion durations of the two adjacent iteration results is sufficiently small, which may be determined by a worker according to circumstances, and is not specifically limited; in summary, the more iterations, the overall duration is generally downward.
It should be noted that the above iterative jump-out condition is a global condition, and is a comprehensive analysis of all task flows.
Fig. 4 is a flow chart of step S400, where the step of calculating the energy consumption according to the real-time statistical task flow and updating the determination process of the task flow according to the energy consumption includes:
step S401: counting all task flows in real time, inquiring equipment corresponding to the task flows, and calculating predicted energy consumption according to equipment parameters;
step S402: correcting a calculation process of the selection probability according to the predicted energy consumption; the correction mode comprises an addition parameter and an adjustment parameter.
Based on the above, all task flows are counted, the related equipment parameters are inquired, the predicted energy consumption is calculated, and the calculation process of the selection probability is adjusted from the energy consumption angle, so that the optimization degree of the task flows is further improved.
In particular, in regard to the adjustment process, what has been said above is adjustedItem and->Item>And->This belongs to the basic parameters, on the basis of which it is also possible to apply +.>And adjusting.
FIG. 5 is a block diagram of the constituent architecture of a peripheral network facility dispatch management system, in an embodiment of the present invention, a peripheral network facility dispatch management system, the system 10 comprising:
a terminal node creation module 11, configured to update the device type and the device position in real time, and create a terminal node according to the device type and the device position;
the task identification module 12 is used for establishing a connection channel with the task set, identifying the tasks in the task set, extracting task labels and obtaining a label set; the task labels are in one-to-one correspondence with the equipment types, and the task labels in the label set contain sequences;
the task flow determining module 13 is used for selecting a peripheral node according to the task label, connecting the peripheral node and determining a task flow;
a determining process updating module 14, configured to count a task flow in real time, calculate energy consumption, and update a determining process of the task flow according to the energy consumption;
the process of determining the task flow at least comprises parameters reflecting node idleness and parameters reflecting node performance.
Further, the tip node creation module 11 includes:
the device information receiving unit is used for receiving the device type and the device position uploaded by the user in real time based on the device table;
the point location mapping unit is used for reading the regional map, determining point location numerical values according to the equipment types and determining point location coordinates according to the equipment positions;
the point position inserting unit is used for inserting the point position numerical value into a point position coordinate as a peripheral node to obtain a region real graph;
the regional map comprises a regional marking port used for receiving a regional range and a regional type input by a user.
Specifically, the task flow determining module 13 includes:
the query unit is used for counting task labels related to all label sets and sequentially querying the equipment types and the point position values corresponding to each task label;
the traversing marking unit is used for traversing the real map of the region according to the point position value and marking the target point position;
the layer creation unit is used for counting the target point positions, creating a node layer with the same size as the real map of the region, and taking the task label as an index;
the iteration execution unit is used for iteratively calculating the task flow of each tag set based on the node diagram layer until the iteration jump-out condition; the iteration jump condition comprises that the iteration times reach a preset time threshold value and the longest predicted time consumption of all task flows is smaller than the preset time consumption threshold value.
Wherein the iterative execution unit includes:
the reading subunit is used for randomly selecting a label set and sequentially reading task labels in the label set;
a selecting subunit, configured to query a node map layer corresponding to the task label, and select a peripheral node based on a selection probability of each point; wherein the selection process affects the selection probability;
the connection subunit is used for connecting the peripheral nodes to obtain a task flow when the task labels of the label set are read;
the judging subunit is used for counting task flows of all the tag sets and judging whether iteration jump conditions are reached;
the selection probability is as follows:
；/>；
in the method, in the process of the invention,probability of choosing for the j-th point in a node map layer,/for each node map layer>For the degree of idleness of the j-th point, +.>For the performance parameter of the j-th point, +.>And->The weight coefficient is preset; />For t+1th iteration process, the idleness of the jth point is +.>Is a preset volatilization speed; />The idle degree of the jth point in the t iterative processes is calculated, and m is the total number of times of selecting the jth point in the t iterative processes; />And selecting the occupancy rate of the jth point for the kth point in the t iterative processes.
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, and alternatives falling within the spirit and principles of the invention.
Claims (6)
1. A method of scheduling management of a peripheral network facility, the method comprising:
updating the equipment type and the equipment position in real time, and creating a peripheral node according to the equipment type and the equipment position;
establishing a connection channel with a task set, identifying tasks in the task set, extracting task labels, and obtaining a label set; the task labels are in one-to-one correspondence with the equipment types, and the task labels in the label set contain sequences;
selecting a peripheral node according to the task label, connecting the peripheral node, and determining a task flow;
counting task flows in real time, calculating energy consumption, and updating a determining process of the task flows according to the energy consumption;
the process of determining the task flow at least comprises parameters reflecting node idle degree and parameters reflecting node performance;
the step of updating the equipment type and the equipment position in real time and creating the peripheral node according to the equipment type and the equipment position comprises the following steps:
receiving the type and the position of the equipment uploaded by the user in real time based on the equipment table;
reading an area map, determining a point position numerical value according to the type of the equipment, and determining a point position coordinate according to the position of the equipment;
inserting the point position numerical value into a point position coordinate to serve as a peripheral node, and obtaining a region real graph;
the regional map comprises a regional marking port and a regional marking port, wherein the regional marking port is used for receiving a regional range and a regional type input by a user;
selecting a peripheral node according to the task label, connecting the peripheral node, and determining the task flow comprises the following steps:
counting task labels related to all label sets, and sequentially inquiring the equipment types and point position values corresponding to each task label;
traversing the real map of the region according to the point position value, and marking a target point position;
counting the target points, creating a node map layer with the same size as the real map of the region, and taking task labels as indexes;
iteratively calculating the task flow of each tag set based on the node diagram layer until the iteration jumps out of the conditions; the iteration jump condition comprises that the iteration times reach a preset time threshold value and the longest predicted time consumption of all task flows is smaller than the preset time consumption threshold value.
2. The peripheral network facility scheduling management method according to claim 1, wherein the step of iteratively calculating the task flow of each tab set based on the node map layer until an iteration jump out condition comprises:
randomly selecting a tag set, and sequentially reading task tags in the tag set;
inquiring a node map layer corresponding to the task label, and selecting a peripheral node based on the selection probability of each point; wherein the selection process affects the selection probability;
when the task labels of the label set are read, connecting the peripheral nodes to obtain a task flow;
counting task flows of all tag sets, and judging whether iteration jump conditions are reached;
the selection probability is as follows:
wherein p is j Selecting probability tau for j-th point in a node map layer j For the degree of idleness, η of the j-th point j The performance parameter of the j-th point is that alpha and beta are preset weight coefficients; τ j (t+1) is the idleness of the j-th point in the t+1 iterative process, and ρ is the preset volatilization speed; τ j (t) the idle degree of the jth point in the t iterative processes, and m is the total number of times of selecting the jth point in the t iterative processes;and selecting the occupancy rate of the jth point for the kth point in the t iterative processes.
3. The method for scheduling and managing a peripheral network facility according to claim 2, wherein the step of counting task flows of all tag sets and determining whether an iterative jump-out condition is reached comprises:
inquiring equipment corresponding to the task flow, and predicting the completion time according to the equipment parameters;
comparing the completion time of different task flows, and determining the longest predicted time consumption;
when the longest predicted time consumption is greater than a preset time consumption threshold, reserving selection probability, and performing loop iteration;
when the longest predicted time is smaller than a preset time consumption threshold, judging that an iteration jump condition is reached;
and recording the iteration times in real time, and judging that the iteration jump condition is reached when the iteration times reach a preset time threshold.
4. The peripheral network facility scheduling management method according to claim 2, wherein the step of counting task flows in real time, calculating energy consumption, and updating a determination process of task flows according to the energy consumption comprises:
counting all task flows in real time, inquiring equipment corresponding to the task flows, and calculating predicted energy consumption according to equipment parameters;
correcting a calculation process of the selection probability according to the predicted energy consumption; the correction mode comprises an addition parameter and an adjustment parameter.
5. A peripheral network facility dispatch management system, the system comprising:
the terminal node creation module is used for updating the equipment type and the equipment position in real time and creating a terminal node according to the equipment type and the equipment position;
the task identification module is used for establishing a connection channel with the task set, identifying the tasks in the task set, extracting task labels and obtaining a label set; the task labels are in one-to-one correspondence with the equipment types, and the task labels in the label set contain sequences;
the task flow determining module is used for selecting a peripheral node according to the task label, connecting the peripheral node and determining a task flow;
the determining process updating module is used for counting the task flow in real time, calculating the energy consumption and updating the determining process of the task flow according to the energy consumption;
the process of determining the task flow at least comprises parameters reflecting node idle degree and parameters reflecting node performance;
the tip node creation module includes:
the device information receiving unit is used for receiving the device type and the device position uploaded by the user in real time based on the device table;
the point location mapping unit is used for reading the regional map, determining point location numerical values according to the equipment types and determining point location coordinates according to the equipment positions;
the point position inserting unit is used for inserting the point position numerical value into a point position coordinate as a peripheral node to obtain a region real graph;
the regional map comprises a regional marking port and a regional marking port, wherein the regional marking port is used for receiving a regional range and a regional type input by a user;
the task flow determination module comprises:
the query unit is used for counting task labels related to all label sets and sequentially querying the equipment types and the point position values corresponding to each task label;
the traversing marking unit is used for traversing the real map of the region according to the point position value and marking the target point position;
the layer creation unit is used for counting the target point positions, creating a node layer with the same size as the real map of the region, and taking the task label as an index;
the iteration execution unit is used for iteratively calculating the task flow of each tag set based on the node diagram layer until the iteration jump-out condition; the iteration jump condition comprises that the iteration times reach a preset time threshold value and the longest predicted time consumption of all task flows is smaller than the preset time consumption threshold value.
6. The peripheral network facility scheduling management system according to claim 5, wherein the iterative execution unit comprises:
the reading subunit is used for randomly selecting a label set and sequentially reading task labels in the label set;
a selecting subunit, configured to query a node map layer corresponding to the task label, and select a peripheral node based on a selection probability of each point; wherein the selection process affects the selection probability;
the connection subunit is used for connecting the peripheral nodes to obtain a task flow when the task labels of the label set are read;
the judging subunit is used for counting task flows of all the tag sets and judging whether iteration jump conditions are reached;
the selection probability is as follows:
wherein p is j Selecting probability tau for j-th point in a node map layer j For the degree of idleness, η of the j-th point j The performance parameter of the j-th point is that alpha and beta are preset weight coefficients; τ j (t+1) is the idleness of the j-th point in the t+1 iterative process, and ρ is the preset volatilization speed; τ j (t) the idle degree of the jth point in the t iterative processes, and m is the total number of times of selecting the jth point in the t iterative processes;and selecting the occupancy rate of the jth point for the kth point in the t iterative processes.
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