CN118800039A - Method, device, equipment, medium and product for early warning and dispatching of sudden failure - Google Patents

Abstract

The application relates to the technical field of computers, provides a sudden fault early warning scheduling method apparatus, devices, media, and articles. The method comprises the following steps: determining early warning information of an early warning event and fault information of an emergency fault event; the early warning event is generated according to weather data, power failure data or seismic data; according to the coincidence information of the early warning information and the fault information, the early warning event is associated with the emergency fault event so as to locate the fault cause; the coincidence information includes any one of region coincidence information, base station coincidence information, and time coincidence information; and generating a task list according to the fault reasons and the priorities of the fault sites, and executing fault scheduling according to the task list. According to the application, through the coincidence information of the early warning information and the fault information, whether the current major fault is associated with the pre-early warning information can be judged more accurately, so that the fault cause is positioned rapidly, and the sudden fault scheduling efficiency is improved.

Description

Method, device, equipment, medium and product for early warning and dispatching of sudden failure

Technical Field

The present application relates to the field of computer technology, and in particular to a method, device, equipment, medium and product for early warning scheduling of sudden failures.

Background Art

When severe weather, power outages, earthquakes and other emergencies occur, there is a high probability that a large-scale power outage and wireless base station service outage will occur in the area, thereby affecting the communication equipment in the computer room and causing damage to customer business.

In the existing scheme, there are many lines for obtaining early warning information, no unified standards, insufficient information sharing rate, and it mostly relies on manual triggering, which has a large number of subjective factors. In addition, the association between emergencies and early warning information depends on manual experience and the degree of information collection. There is no quantitative indication of the importance of the computer room or it is only a static value, which is difficult to meet the real-time change requirements of faults. The scheduling priority needs to be matched offline and repeatedly confirmed, and the efficiency of fault scheduling is low.

Summary of the invention

The embodiments of the present application provide a method, device, equipment, medium and product for early warning scheduling of sudden faults, so as to solve the problem of low efficiency of fault scheduling in the prior art.

In a first aspect, an embodiment of the present application provides a method for early warning scheduling of sudden faults, including:

Determine warning information of warning events and fault information of sudden fault events; the warning events are generated based on weather data, power outage data or earthquake data;

According to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information;

A task list is generated according to the fault cause and the priority of each fault site, and fault scheduling is performed according to the task list.

According to a sudden fault warning scheduling method provided in an embodiment of the present application, the warning information includes a warning area, a warning base station and a warning time; the fault information includes a fault area, a fault base station and a fault time;

The associating the warning event with the sudden fault event according to the coincidence information of the warning information and the fault information includes:

If the area overlap information indicates that the fault area includes the warning area, determining that the warning event is associated with the sudden fault event;

If the base station coincidence information indicates that the coincidence degree between the early warning base station and the fault base station is greater than a set threshold, it is determined that the early warning event is associated with the sudden fault event;

If the time coincidence information indicates that the warning time is within the fault time range, it is determined that the warning event is associated with the sudden fault event.

According to a sudden fault warning scheduling method provided in an embodiment of the present application, if the warning event is a regional warning, the warning area is determined based on the following method:

Determining street data affected by the warning event;

If the street data can form a closed area, determining the warning area according to the closed area;

If the street data can form a road intersection, a first buffer zone is determined according to the road intersection, and the first buffer zone is used as the warning area;

If the street data cannot form a road intersection, the target user affected by the warning event is obtained, and the warning area is determined according to the location information of the target user.

According to a sudden fault warning scheduling method provided by an embodiment of the present application, determining the warning area according to the location information of the target user includes:

If there are multiple target users, determining the warning area according to the maximum longitude and latitude and the minimum longitude and latitude in the location information of the target users;

If there is one target user, a second buffer zone is determined according to the location information of the target user, and the second buffer zone is used as the warning zone.

According to a sudden fault early warning scheduling method provided in an embodiment of the present application, the sudden fault event is determined based on the following method:

If the ratio of the number of computer rooms with power outage alarms in the target area to the total number of computer rooms in the target area is greater than a set threshold value, it is determined that the sudden failure event occurs in the target area;

If the number of devices or services that have been decommissioned in the target area is greater than a set number, it is determined that the sudden failure event has occurred in the target area.

According to a sudden fault early warning scheduling method provided in an embodiment of the present application, the priority of the fault site is determined based on the following method:

Determine the weight value of the faulty site according to the weight of each computer room, the remaining battery life and the out-of-service information;

Determine a score value of each of the faulty sites according to the maximum weight value and the minimum weight value of the faulty sites and the weight value of each of the faulty sites;

The priority of the faulty site is determined according to the score value.

According to a sudden fault early warning scheduling method provided by an embodiment of the present application, performing fault scheduling according to the task list includes:

generating a scheduling request according to the task list;

Determine the dispatch distance of each maintenance agent to each of the fault sites, and determine the weight of each maintenance agent according to the dispatch distance and the score value of the fault site;

According to the weight of each maintenance agent, multiple target maintenance agents are determined;

The scheduling request is sent to the plurality of target maintenance personnel.

In a second aspect, an embodiment of the present application provides a sudden fault warning scheduling device, including:

A determination module, used to determine the warning information of the warning event and the fault information of the sudden fault event; the warning event is generated based on weather data, power outage data or earthquake data;

A fault cause locating module, used to associate the warning event with the sudden fault event according to the overlap information of the warning information and the fault information, so as to locate the fault cause; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information;

The task list generation module is used to generate a task list according to the fault cause and the priority of each fault site, and perform fault scheduling according to the task list.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory storing a computer program, wherein when the processor executes the program, the steps of the sudden fault warning scheduling method described in the first aspect are implemented.

In a fourth aspect, an embodiment of the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the sudden fault warning scheduling method described in the first aspect are implemented.

In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the sudden fault warning scheduling method described in the first aspect.

The sudden fault warning scheduling method, device, equipment, medium and product provided in the embodiment of the present application are determined by the warning information of the warning event and the fault information of the sudden fault event; the warning event is generated based on weather data, power outage data or earthquake data; according to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of the regional overlap information, the base station overlap information and the time overlap information; according to the cause of the fault and the priority of each fault site, a task list is generated, and the fault scheduling is performed according to the task list. Through the overlap information of the warning information and the fault information, the present application can more accurately determine whether the current major fault is associated with the advance warning information, thereby quickly locating the cause of the fault and improving the efficiency of sudden fault scheduling.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

FIG1 is a schematic diagram of a process flow of a sudden fault early warning scheduling method provided in an embodiment of the present application;

FIG2 is a schematic diagram of oil engine resource allocation provided by an embodiment of the present application;

FIG3 is a schematic diagram of the structure of a sudden fault warning and dispatching device provided in an embodiment of the present application;

FIG. 4 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

DETAILED DESCRIPTION

In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

FIG1 is a flow chart of a method for early warning and scheduling of sudden faults provided in an embodiment of the present application. Referring to FIG1 , an embodiment of the present application provides a method for early warning and scheduling of sudden faults, which may include:

Step 100, determining warning information of a warning event and fault information of a sudden fault event.

Warning events are generated based on weather data, power outage data or earthquake data, including weather warning events, power outage warning events and earthquake events. Among them, each warning event is generated based on the following methods:

(1) Weather warning events:

1.1) Based on keywords such as rain, snow, electricity, wind, and four, crawl the weather data of a specific area from various weather websites.

1.2) Update frequency: such as 5-minute granularity update.

1.3) Data timeliness: The expiration time of the data is the warning release time + the time keyword in the release content (such as occurring within 6 hours, occurring within 12 hours). If there is no time keyword, the data will expire 24 hours after the default release time. If there is no city, district, or county information, the keyword will be passed to the GIS (Geographic Information System) platform to return the city, district, and county information.

(2) Power outage warning events:

2.1) Crawl the power outage announcements in the last two days in a specific area from each power grid website.

2.2) Update frequency: such as updating at a granularity of 15 minutes.

2.3) Data timeliness: If the current system time is greater than the end time of the power outage, the single announcement message will be invalid.

(3) Earthquake warning events:

3.1) Crawl earthquake data of a specific area from the seismic station website.

3.2) Update frequency: 1 minute.

Optionally, warning events can also be generated based on water level and river level data, fire data, etc.

Sudden failure events include large-scale power outage events and large-scale outage events. Specifically, if the ratio of the number of computer rooms with power outage alarms in the target area to the total number of computer rooms in the target area is greater than the set threshold value, it is determined that a sudden failure event has occurred in the target area, that is, a large-scale power outage event has occurred. This means that in the target area, if the number of computer rooms with power outage alarms accounts for a large proportion, it will trigger the generation of a large-scale power outage event. Once a large-scale power outage event has been generated in the target area, the target area will not generate a new event again until this event is closed.

The target area can be understood as an area where a sudden failure occurs, such as a district or a county. The power outage alarm can be a dynamic power outage alarm, which is a power outage alarm about the power environment (power supply). In a device or system, the power environment usually refers to the environment that provides power to the device, including power supplies, cables, distribution cabinets, etc. When a power outage occurs in this environment, the system will generate a corresponding power outage alarm to prompt users or managers that the current device or system cannot operate normally.

If the number of devices or services that have been decommissioned in the target area is greater than the set number, it is determined that a sudden failure event has occurred in the target area, that is, a large-scale decommissioning event has occurred. This means that when a major fault-derived alarm occurs, that is, a fault causes the decommissioning of multiple related devices or services, it will trigger the generation of a large-scale decommissioning event. Such events are usually derived from major faults and may affect a large range of services or devices. Once a large-scale decommissioning event has been generated in the target area, the target area will not generate a new event again until this event is closed.

Among them, decommissioning refers to the state where a system, equipment or service stops operating or temporarily fails due to a fault or other reason. Large-scale decommissioning refers to a major fault that causes multiple related equipment or services to fail to work properly, thereby affecting the operation of a larger area, including the decommissioning of network equipment, servers, communication facilities, etc., and the service interruption or degradation caused by a major fault, thus affecting the normal operation of the entire area or system.

After determining the warning event and the sudden fault event, it is further necessary to determine the warning information of the warning event and the fault information of the sudden fault event. The warning information includes the warning area, the warning base station and the warning time; the fault information includes the fault area, the fault base station and the fault time.

Step 200: According to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault.

The overlap information includes any one of area overlap information, base station overlap information and time overlap information.

If the regional overlap information indicates that the fault area includes the warning area, it is determined that the warning event is associated with the sudden fault event. For example, when the prefecture-level city or county where the sudden fault event occurs includes any prefecture-level city or county where the warning event occurs, it can be considered that there is regional overlap. This means that the location where the fault occurred matches the location indicated in the prior warning, suggesting that the fault may have been caused by the warning event.

If the base station overlap information indicates that the overlap between the warning base station and the fault base station is greater than the set threshold, it is determined that the warning event is associated with the sudden fault event. For example, if the overlap between the number of base stations involved in the sudden fault event and the number of base stations in the affected base station range in the warning event reaches more than 60%, it can be considered that there is a base station overlap. This means that there is a certain degree of overlap between the base stations affected by the fault and the base stations that may be affected identified in the warning event, which further suggests that the fault may be caused by the warning event.

If the time overlap information indicates that the warning time is within the fault time range, then the warning event is determined to be associated with the sudden fault event. For example, if the occurrence time of the sudden fault event coincides with the range from the "warning start time" to the "estimated end time" of the warning event, it can be considered that there is a time overlap. This means that the time when the fault occurred overlaps with the potential impact period indicated in the warning event, suggesting that the fault was caused by the warning event.

Step 300: Generate a task list according to the fault cause and the priority of each fault site, and perform fault scheduling according to the task list.

For each computer room, the system will evaluate its importance, such as the business volume in the area where the computer room is located, the number of users, service coverage, importance of base stations, home broadband, customer service, type of computer room and other factors. The more important the computer room is, the greater the impact of its service interruption on users and business. Then, based on the importance of the computer room and other factors (such as remaining battery life, decommissioning, etc.), dynamic calculations are performed to determine the score value of each faulty site. Finally, based on the score value of each faulty site, the priority order of fault handling is determined, and a corresponding task list is generated, where the task list includes the cause of the fault at the faulty site.

In one embodiment, referring to Table 1, Table 1 is a task list.

Table 1

The sudden fault warning scheduling method provided by the embodiment of the present application determines the warning information of the warning event and the fault information of the sudden fault event; the warning event is generated based on weather data, power outage data or earthquake data; according to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of the regional overlap information, the base station overlap information and the time overlap information; according to the cause of the fault and the priority of each fault site, a task list is generated, and the fault scheduling is performed according to the task list. Through the overlap information of the warning information and the fault information, the embodiment of the present application can more accurately determine whether the current major fault is associated with the advance warning information, thereby quickly locating the cause of the fault and improving the efficiency of sudden fault scheduling.

Based on the above embodiment, the warning area is determined based on the following method:

Step 111, determining street data affected by the warning event;

Step 112, if the street data can form a closed area, determining the warning area according to the closed area;

Step 113, if the street data can form a road intersection, then a first buffer zone is determined according to the road intersection, and the first buffer zone is used as the warning area;

Step 114: If the street data cannot form a road intersection, then the target user affected by the warning event is obtained, and the warning area is determined according to the location information of the target user.

It should be noted that according to the warning scope of the warning event, it can be divided into full-area warning and regional warning.

Area-wide warnings (such as weather and earthquakes): These warnings generally affect the entire city, district, or county. Therefore, the warning area is usually the entire city or county. At the same time, you only need to link all base stations within the city or county to obtain the warning base station.

Regional warnings (such as power outages): These warnings usually affect base stations in a specific area, and further refinement is required to match the affected base stations to ensure that the affected area is accurately defined.

For power outage warning events, it is necessary to determine the street data affected by the power outage warning event, including road line data and intersection data. If the affected street data is road line data, the road line data can be used to form a closed area, that is, a closed shape composed of a polygon or multiple roads to surround the affected area. Then, a 100-meter buffer is loaded around this closed area to ensure that the potentially affected area is covered, and the power outage geographic range is obtained, that is, the warning range of the power outage warning event. It is understandable that power outages may cause impacts within a certain range, not just limited to the power outage point or the affected road. By loading the buffer, it can be considered that the impact of the power outage will gradually spread to the surrounding areas; on the other hand, there may be certain uncertainties in the specific impact range of the power outage, such as being affected by weather, equipment failure and other factors. Therefore, loading the buffer area helps to take into account the possible spatial diffusion and uncertainty factors of the power outage, and improve the accuracy and comprehensiveness of the geographical range of the power outage.

If the affected street data is intersection data, it is impossible to directly form a closed area. The first buffer zone is determined according to the road intersection and is used as the warning area. For example, a 500-meter buffer zone is loaded according to the road intersection, and a circular area with a radius of 500 meters is created with the road intersection as the center to define the geographical scope of the power outage.

If street data cannot be obtained or a road intersection cannot be formed based on street data, target users affected by the warning event are obtained, and the warning area is determined according to the location information of the target users, wherein the target users include high-risk affected users and affected users, etc.

Specifically, if there are multiple target users, the warning area is determined according to the maximum longitude and latitude and the minimum longitude and latitude in the location information of the target users. If there is only one target user, the second buffer zone is determined according to the location information of the target user and the second buffer zone is used as the warning area.

For example, when street data cannot be obtained or road intersections cannot be formed based on street data, the customer information of target users affected by the warning event is queried, and the customer information is spread on the GIS map to observe regional relationships and then divide the geographical scope of the power outage.

Multi-point customer information: If there are multiple target users, obtain the latitude and longitude information of the target customer based on the target user's location information, and then determine the maximum and minimum latitude and longitude from the latitude and longitude information, and add a 100-meter buffer zone to the maximum and minimum latitude and longitude to ensure the comprehensiveness of the boundary range and obtain the geographical scope of the power outage.

Single-point customer information: If the customer information is only a single point, the outage geographic scope is obtained by querying the point data and generating a 200-meter buffer around each point to form a frame range.

Target user ratio: Query the ratio of high-risk affected customers and affected customers on the GIS map. If the number of high-risk affected customers and affected customers is less than 50%, it is necessary to add a 500-meter buffer zone to the maximum longitude and latitude and the minimum longitude and latitude to expand the definition of the geographical scope of the power outage to ensure that the potential impact range is covered.

By analyzing the early warning information, the system can accurately determine the affected area, such as weather, earthquake or power outage, and thus more precisely determine the range of affected base stations. By accurately locating the range of affected base stations, the system can more effectively dispatch resources, quickly respond to fault handling needs, and improve the efficiency of fault handling.

Based on the above embodiment, the priority of the faulty site is determined based on the following method:

Step 311, determining the weight value of the faulty site according to the weight of each computer room, the remaining battery life and the service withdrawal information;

Step 312, determining a score value of each of the faulty sites according to the maximum weight value and the minimum weight value of the faulty sites and the weight value of each of the faulty sites;

Step 313: Determine the priority of the faulty site according to the score value.

The weight of each computer room is determined by comprehensively considering the importance of the base station, home bandwidth, customer service, and computer room type, as shown in Table 2.

Table 2

After determining the weight of the computer room, normalize and assign values to the three parameters: computer room weight, remaining battery life (dynamically calculated based on battery life and fault duration, the parameter weight of the decommissioned site is reset to the highest value), and decommissioning information (such as whether the service is decommissioned), as shown in Table 3.

Table 3

The weight of the faulty site is calculated based on the normalized data center weight, remaining battery life, and whether it is out of service. For example, the weight of the faulty site is obtained by summing up the three parameters:

_{Sfault site} = X _{parameter 1} + X _{parameter 2} + X _{parameter 3} ;

Among them, X _{parameter 1} is the weight of the computer room, X _{parameter 2} is the remaining battery life, X _{parameter 3} is whether to decommission, and S _{fault site} is the weight value of the fault site.

From the weight values of all faulty sites, determine the minimum weight value and the maximum weight value of the faulty site, and then calculate the score value of the faulty site. The calculation formula of the score value of the faulty site is as follows:

Among them, Xfault _Site is the score value of the fault site, min( _{Sfault Site} ) is the minimum weight value of the fault site, and max( _{Sfault Site} ) is the maximum weight value of the fault site.

The fault handling priority is determined based on the score value. The higher the score value, the higher the priority.

The embodiment of the present application helps the system to more reasonably determine the priority during fault scheduling by considering the weight of the computer room, the remaining battery life, and whether to be decommissioned, so as to ensure the effective use of resources and minimize the impact of the fault on users and services.

Based on the above embodiment, performing fault scheduling according to the task list includes:

Step 321, generating a scheduling request according to the task list;

Step 322, determining the dispatch distance of each maintenance agent to each of the fault sites, and determining the weight of each maintenance agent according to the dispatch distance and the score value of the fault site;

Step 323, determining multiple target maintenance personnel according to the weight of each maintenance personnel;

Step 324: Send the scheduling request to the multiple target maintenance personnel.

For emergencies caused by large-scale power outages, the system will use the location information of the oil engine and personnel, combined with the weight of the fault site to calculate the path, and thus provide the best scheduling suggestions. Among them, the scheduling distance from maintenance personnel i to a certain fault site is:

L _{dispatch distance i} = L _{oil engine - fault site} + L _{maintenance personnel i - oil engine} ;

Among them, L _{dispatch distance i} is the dispatch distance, L _{oil engine-fault site} is the distance between the oil engine and the fault site, and L _{personnel i-oil engine} is the distance between personnel i and the oil engine.

After calculating the dispatch distance, the weight of each maintenance personnel is determined according to the dispatch distance. The calculation formula is:

Among them, R _{maintenance personnel i} is the weight of the maintenance personnel, max(L _{dispatch distance 1,2,...,k} ) is the maximum dispatch distance, min(L _{dispatch distance 1,2,...,k} ) is the minimum dispatch distance, X _{fault site} is the score value of the fault site, k is the maintenance personnel around the specific range of the fault site, and the smaller the dispatch distance, the higher the weight.

After determining the weight of each maintenance agent, N maintenance agents with the highest weights are selected as target maintenance agents, and a scheduling request generated according to the task list is sent to the N maintenance agents.

By utilizing oil engine resources and personnel location information, the embodiment of the present application can enable the system to quickly respond to emergencies, such as large-scale power outages, thereby shortening the power outage time and reducing the impact on users and businesses. In addition, through path calculation and site weight considerations, the system can optimize the scheduling plan and maximize the use of oil engine resources and personnel to achieve the optimal allocation of power supply and avoid waste of resources. Through automated scheduling suggestions and task distribution, the system can improve the efficiency of emergency response and reduce the time and cost of human intervention. By reasonably scheduling oil engine resources and maintenance personnel, the system can enhance the reliability of power supply, ensure that normal power supply is restored in power outage areas as soon as possible, and improve user and business satisfaction.

In order to further analyze and explain the sudden failure warning scheduling method proposed in the embodiment of the present application, refer to the following embodiments.

The present application embodiment specifically proposes a sudden fault early warning dispatching system, which mainly solves the following problems:

(1) Intelligently crawl weather, power outage, and earthquake information to generate early warning events, link GIS maps to circle the affected base stations, and send frontline maintenance personnel in advance for support.

(2) Sudden large-scale power outages and service outages are associated with warning events to locate the cause of the fault.

(3) Perform data mining on the multi-dimensional attributes of the computer room, output the weight value of the computer room, and provide fault handling priority.

The embodiment of the present application constructs a smart scheduling system architecture through the data layer, service layer, and application layer, uses the system to intelligently crawl the event warning range, identifies the affected base stations through the classification query matching method, establishes a dynamic scheduling model for the computer room, quickly generates a task list, and ensures efficient scheduling and processing of faults.

Specifically, the intelligent dispatching system is mainly composed of data layer, service layer and application layer. It carries various services based on the underlying database and provides the applications required by the upper layer.

Data layer: Establish an underlying database to provide basic data such as weather warning information, power outage announcements, alarms, personnel and resource allocation, etc.

Service layer: provides intelligent crawling, field analysis, GIS services, report statistics, task list planning capabilities, etc. The intelligent crawling scope automatically adapts to the affected base stations and generates a dynamic scheduling list for the computer room.

Application layer: realizes multi-dimensional presentation and message push of events, task lists, GIS maps, topology, and dynamic tracking and scheduling of personnel and oil engine resources.

The sudden fault early warning dispatching method based on the intelligent dispatching system includes the following contents:

(1) Advance warning: Crawling weather, power outage, and earthquake data in real time to generate warning events.

(2) Early warning information affects the delineation of base station range.

According to the content of the warning information, weather and earthquake information are region-wide warnings, which generally affect the entire city, district or county, and are related to all base stations within the city or district; power outage information is a regional warning, and the information carries the affected streets and affected customers. In order to further refine the matching of affected base stations, rules for demarcating base stations in the affected area are formulated.

2.1) The affected street data is road line data, such as XX Road XX Street, and a closed frame can be formed based on the road information, and a 100-meter buffer zone is loaded around it to define the geographical scope of the power outage; if only an intersection can be formed but a closed frame cannot be formed, a 500-meter buffer zone is loaded based on the intersection to define the geographical scope of the power outage.

2.2) If the affected streets are only counties, towns, or if the street data cannot form an intersection, query the high-risk customer information and spread the customer information on the GIS map to observe the regional relationship:

2.21) Customer information can form an area, taking the maximum longitude and latitude, the minimum longitude and latitude plus 100 meters to generate a frame range;

2.22) If the customer information is a single point, the query point data will be framed according to a 200-meter buffer zone;

2.23) If the number of high-risk affected customers and affected customers that can be found on the GIS map is less than 50%, the maximum longitude and latitude and the minimum longitude and latitude are used to generate a frame range and a 500-meter buffer zone is added to define the geographical scope of the power outage.

(3) On-the-spot dispatching.

The event in the embodiment of the present application specifically refers to a large-scale failure within the network. When a qualified failure occurs, an event message will be generated. The event details will present all the faulty computer rooms involved in the current event and the computer room ranking priority calculated according to a specific algorithm, and the front line will be dispatched to handle the failure.

3.1) Definition of events:

When any of the following conditions is met, an event is generated at the regional granularity. Before the current event is closed, no new event will be generated in this district or county.

Large-scale power outage: When the ratio of the number of computer rooms with power outage alarms in the current district or county to the total number of computer rooms in the district or county reaches the preset threshold, a large-scale power outage is considered to have occurred;

Large-scale outage: A major fault generates an alarm;

Event ends: The large-scale outage alarm is cleared or the large-scale power outage is below the threshold. Event definitions and thresholds can be configured and adjusted.

3.2) Pre-warning and event correlation algorithm:

After an event occurs, it is associated with the prior warning information to determine whether it is a large-scale failure caused by the relevant warning.

Regional overlap: When the city, district, or county where the current major fault occurs is included in the warning event, it is judged to meet the conditions;

Base station overlap: If the overlap between the current major fault base station and the affected base stations is more than 60%, the condition is considered met;

Time coincidence: This condition is considered to be met when the current major fault occurrence time is included in the range from "warning start time" to "estimated end time" of the warning event;

Associate the warning events that meet the conditions with the current major fault; when associated with multiple warning events, all of them are spliced and displayed.

3.3) Event presentation:

Events that meet the threshold will enter the dispatch view, and the associated warning information will be presented simultaneously to facilitate fault cause location. The auxiliary GIS map intuitively presents information such as provincial and municipal fault sites, the number of affected base stations, and fault causes to guide fault dispatch work.

3.4) Task list generation:

According to the importance of the computer room, the fault dispatch priority is evaluated and the comprehensive weight is dynamically calculated. The computer room weight is used as one of the core parameters, and the remaining battery life and service withdrawal status are dynamically calculated, and a task list is output.

3.5) Task list push:

The generated task list is pushed automatically or manually to guide the front-line fault dispatch and processing. The list is refreshed at a 15-minute granularity to ensure timely and effective dispatch.

3.6) Oil engine resource allocation:

In case of emergencies caused by large-scale power outages, the optimal dispatching suggestion is provided through path calculation based on the oil engine, personnel location information, and site weights, and power generation dispatching tasks are sent to the 1-3 maintenance personnel with the highest dispatching weight P. The personnel location information is connected to the maintenance personnel trajectory module to obtain the maintenance personnel information within a certain range near the computer room.

The embodiment of the present application generates warning events by automatically obtaining weather and power outage information, and circles the affected base stations by associating them with the GIS map. Frontline maintenance personnel can be sent in advance for protection, and caring text messages can be sent to customers. The cause of the fault can be quickly located by associating sudden fault events with warning events. The comprehensive weight is dynamically calculated to generate a task list, which is updated regularly through 5G messages. The GIS map is intuitively presented, and the resource location is dynamically tracked, which greatly improves the efficiency of fault scheduling and processing.

The sudden fault warning scheduling device provided in an embodiment of the present application is described below. The sudden fault warning scheduling device described below and the sudden fault warning scheduling method described above can be referred to each other.

Referring to FIG. 3 , FIG. 3 is a schematic diagram of the structure of a sudden fault warning dispatching device provided in an embodiment of the present application. The sudden fault warning dispatching device provided in an embodiment of the present application includes:

Determination module 301, used to determine warning information of warning events and fault information of sudden fault events; the warning events are generated based on weather data, power outage data or earthquake data;

A fault cause locating module 302 is used to associate the warning event with the sudden fault event according to the overlap information of the warning information and the fault information, so as to locate the fault cause; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information;

The task list generation module 303 is used to generate a task list according to the fault cause and the priority of each fault site, and perform fault scheduling according to the task list.

The sudden fault warning and dispatching device provided by the embodiment of the present application determines the warning information of the warning event and the fault information of the sudden fault event; the warning event is generated based on weather data, power outage data or earthquake data; according to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of the regional overlap information, the base station overlap information and the time overlap information; according to the cause of the fault and the priority of each fault site, a task list is generated, and the fault dispatch is performed according to the task list. Through the overlap information of the warning information and the fault information, the embodiment of the present application can more accurately determine whether the current major fault is associated with the advance warning information, thereby quickly locating the cause of the fault and improving the efficiency of sudden fault dispatching.

In one embodiment, the fault cause location module 302 is further configured to:

If the area overlap information indicates that the fault area includes the warning area, determining that the warning event is associated with the sudden fault event;

If the base station coincidence information indicates that the coincidence degree between the early warning base station and the faulty base station is greater than a set threshold, it is determined that the early warning event is associated with the sudden fault event;

If the time coincidence information indicates that the warning time is within the fault time range, it is determined that the warning event is associated with the sudden fault event.

In one embodiment, the warning area is determined based on the following method:

Determining street data affected by the warning event;

If the street data can form a closed area, determining the warning area according to the closed area;

If the street data can form a road intersection, a first buffer zone is determined according to the road intersection, and the first buffer zone is used as the early warning area;

If the street data cannot form a road intersection, the target user affected by the warning event is obtained, and the warning area is determined according to the location information of the target user.

In one embodiment, determining the warning area according to the location information of the target user includes:

If there are multiple target users, determining the warning area according to the maximum longitude and latitude and the minimum longitude and latitude in the location information of the target users;

If there is one target user, a second buffer zone is determined according to the location information of the target user, and the second buffer zone is used as the warning zone.

In one embodiment, the sudden failure event is determined based on the following method:

If the ratio of the number of computer rooms with power outage alarms in the target area to the total number of computer rooms in the target area is greater than a set threshold value, it is determined that the sudden failure event occurs in the target area;

If the number of devices or services that have been decommissioned in the target area is greater than a set number, it is determined that the sudden failure event has occurred in the target area.

In one embodiment, the priority of the failed site is determined based on the following method:

Determine the weight value of the faulty site according to the weight of each computer room, the remaining battery life and the out-of-service information;

Determine a score value of each of the faulty sites according to the maximum weight value and the minimum weight value of the faulty sites and the weight value of each of the faulty sites;

The priority of the faulty site is determined according to the score value.

In one embodiment, the task list generation module 303 is further used to:

generating a scheduling request according to the task list;

Determine the dispatch distance of each maintenance agent to each of the fault sites, and determine the weight of each maintenance agent according to the dispatch distance and the score value of the fault site;

According to the weight of each maintenance agent, multiple target maintenance agents are determined;

The scheduling request is sent to the plurality of target maintenance personnel.

FIG4 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG4 , the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call a computer program in the memory 430 to execute the steps of the sudden fault early warning scheduling method, for example, including:

Determine warning information of warning events and fault information of sudden fault events; the warning events are generated based on weather data, power outage data or earthquake data;

According to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information;

A task list is generated according to the fault cause and the priority of each fault site, and fault scheduling is performed according to the task list.

In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk.

On the other hand, an embodiment of the present application further provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the sudden fault early warning scheduling method provided in the above embodiments are implemented, for example, including:

Determine warning information of warning events and fault information of sudden fault events; the warning events are generated based on weather data, power outage data or earthquake data;

According to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information;

A task list is generated according to the fault cause and the priority of each fault site, and fault scheduling is performed according to the task list.

On the other hand, an embodiment of the present application further provides a computer program product, the computer program product including a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can perform the steps of the sudden fault early warning scheduling method provided in the above embodiments, for example, including:

Determine warning information of warning events and fault information of sudden fault events; the warning events are generated based on weather data, power outage data or earthquake data;

According to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information;

A task list is generated according to the fault cause and the priority of each fault site, and fault scheduling is performed according to the task list.

The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM/RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims (11)

1. A method for early warning and scheduling of sudden failures, characterized by comprising: Determine warning information of warning events and fault information of sudden fault events; the warning events are generated based on weather data, power outage data or earthquake data; According to the overlap information of the warning information and the fault information, the warning event is associated with the sudden fault event to locate the cause of the fault; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information; A task list is generated according to the fault cause and the priority of each fault site, and fault scheduling is performed according to the task list. 2. The method for early warning and dispatching of sudden faults according to claim 1, characterized in that the early warning information includes an early warning area, an early warning base station and an early warning time; the fault information includes a fault area, a fault base station and a fault time; The associating the warning event with the sudden fault event according to the coincidence information of the warning information and the fault information includes: If the area overlap information indicates that the fault area includes the warning area, determining that the warning event is associated with the sudden fault event; If the base station coincidence information indicates that the coincidence degree between the early warning base station and the fault base station is greater than a set threshold, it is determined that the early warning event is associated with the sudden fault event; If the time coincidence information indicates that the warning time is within the fault time range, it is determined that the warning event is associated with the sudden fault event. 3. The method for early warning and dispatching of sudden failures according to claim 2, wherein if the early warning event is a regional early warning, the early warning area is determined based on the following method: Determining street data affected by the warning event; If the street data can form a closed area, determining the warning area according to the closed area; If the street data can form a road intersection, a first buffer zone is determined according to the road intersection, and the first buffer zone is used as the warning area; If the street data cannot form a road intersection, the target user affected by the warning event is obtained, and the warning area is determined according to the location information of the target user. 4. The method for early warning and dispatching of sudden failures according to claim 3, characterized in that the step of determining the early warning area according to the location information of the target user comprises: If there are multiple target users, determining the warning area according to the maximum longitude and latitude and the minimum longitude and latitude in the location information of the target users; If there is one target user, a second buffer zone is determined according to the location information of the target user, and the second buffer zone is used as the warning zone. 5. The method for early warning and dispatching of sudden failures according to claim 1, wherein the sudden failure event is determined based on the following method: If the ratio of the number of computer rooms with power outage alarms in the target area to the total number of computer rooms in the target area is greater than a set threshold value, it is determined that the sudden failure event occurs in the target area; If the number of devices or services that have been decommissioned in the target area is greater than a set number, it is determined that the sudden failure event has occurred in the target area. 6. The method for early warning and scheduling of sudden failures according to claim 1, wherein the priority of the fault site is determined based on the following method: Determine the weight value of the faulty site according to the weight of each computer room, the remaining battery life and the out-of-service information; Determine a score value of each of the faulty sites according to the maximum weight value and the minimum weight value of the faulty sites and the weight value of each of the faulty sites; The priority of the faulty site is determined according to the score value. 7. The method for early warning and scheduling of sudden faults according to claim 6, wherein the performing of fault scheduling according to the task list comprises: generating a scheduling request according to the task list; Determine the dispatch distance of each maintenance agent to each of the fault sites, and determine the weight of each maintenance agent according to the dispatch distance and the score value of the fault site; According to the weight of each maintenance agent, multiple target maintenance agents are determined; The scheduling request is sent to the plurality of target maintenance personnel. 8. A sudden fault early warning dispatching device, characterized by comprising: A determination module, used to determine the warning information of the warning event and the fault information of the sudden fault event; the warning event is generated based on weather data, power outage data or earthquake data; A fault cause locating module, used to associate the warning event with the sudden fault event according to the overlap information of the warning information and the fault information, so as to locate the fault cause; the overlap information includes any one of regional overlap information, base station overlap information and time overlap information; The task list generation module is used to generate a task list according to the fault cause and the priority of each fault site, and perform fault scheduling according to the task list. 9. An electronic device, comprising a processor and a memory storing a computer program, wherein the processor implements the steps of the sudden failure early warning scheduling method according to any one of claims 1 to 7 when executing the computer program. 10. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the sudden failure early warning scheduling method according to any one of claims 1 to 7 are implemented. 11. A computer program product, comprising a computer program, characterized in that when the computer program is executed by a processor, the steps of the sudden failure early warning scheduling method according to any one of claims 1 to 7 are implemented.