CN115002117B - Dynamic scheduling method, system, equipment and storage medium for content distribution network - Google Patents
Dynamic scheduling method, system, equipment and storage medium for content distribution network Download PDFInfo
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Abstract
The application discloses a dynamic scheduling method, a system, equipment and a storage medium of a content distribution network, wherein the dynamic scheduling method of the content distribution network comprises the following steps: and acquiring a trigger index item and a self-defined scheduling rule configured according to service requirements, and generating a plurality of scheduling strategies based on the trigger index item and the self-defined scheduling rule, wherein the scheduling strategies comprise scheduling service, index trigger conditions and a scheduling node range, and triggering and executing the scheduling strategy corresponding to the trigger conditions when the trigger index item corresponding to a target node is detected to meet the trigger conditions so as to schedule the scheduling service of the target node to the scheduling node in the scheduling node range. The application solves the technical problems that when business service changes, a scheduling strategy is required to deal with a new fault business scene through secondary development, so that the access request of a user cannot be effectively accelerated and the use experience of the user is affected.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a method, a system, an apparatus, and a storage medium for dynamic scheduling of a content distribution network.
Background
Currently, CDNs (Content Delivery Network, content delivery networks) provide acceleration services. Taking a domain name access service as an example, the specific process is as follows: the CDN plans the edge nodes of the CDN according to the geographic position or a network operator, and when a user accesses the domain name, the domain name access can be realized from the edge nodes.
And each edge node in the existing CDN cluster is subjected to service monitoring by corresponding monitoring equipment, and the running state of the monitored edge node is reported to a dispatching system. When a certain edge node is found to be faulty or the service quantity of a service is too large, the service is scheduled to other available edge nodes nearby by utilizing a static fixed scheduling strategy, however, the static fixed scheduling strategy cannot adapt to the change of the service, the expandability is poor, and a new fault service scene needs to be dealt with through secondary development, so that the access request of a user cannot be effectively accelerated, and the use experience of the user is influenced.
Disclosure of Invention
The application mainly aims to provide a dynamic scheduling method, a system, equipment and a storage medium for a content distribution network, and aims to solve the technical problems that in the prior art, when service changes, a scheduling strategy is required to be developed for coping with a new fault service scene through secondary development, so that an access request of a user cannot be effectively accelerated, and the use experience of the user is influenced.
In order to achieve the above object, the present application provides a dynamic scheduling method for a content distribution network, the dynamic scheduling method for a content distribution network comprising:
acquiring a trigger index item configured according to service requirements and a custom scheduling rule;
generating a plurality of scheduling strategies based on the triggering index items and the self-defined scheduling rules, wherein the scheduling strategies comprise scheduling business services, triggering conditions and scheduling node ranges;
And triggering and executing a scheduling strategy corresponding to the triggering condition when the triggering index item corresponding to the target node is detected to meet the triggering condition, so as to schedule the scheduling business service of the target node to the scheduling node in the range of the scheduling node.
The application also provides a dynamic scheduling system of the content distribution network, which is a virtual system, and comprises:
the acquisition module is used for acquiring the trigger index item configured according to the service requirement and the custom scheduling rule;
The strategy generation module is used for generating a plurality of scheduling strategies based on the trigger index item and the custom scheduling rule, wherein the scheduling strategies comprise scheduling business service, index trigger conditions and a scheduling node range;
And the strategy execution module is used for triggering and executing a scheduling strategy corresponding to the triggering condition when the triggering index item corresponding to the target node is detected to meet the triggering condition, so as to schedule the scheduling service of the target node to the scheduling node in the range of the scheduling node.
The application also provides a dynamic scheduling device of the content distribution network, wherein the dynamic scheduling device of the content distribution network is entity equipment, and the dynamic scheduling device of the content distribution network comprises: the system comprises a memory, a processor and a content distribution network dynamic scheduling program stored on the memory, wherein the content distribution network dynamic scheduling program is executed by the processor to realize the steps of the content distribution network dynamic scheduling method.
The application also provides a storage medium which is a computer readable storage medium, wherein the computer readable storage medium stores a content distribution network dynamic scheduling program, and the content distribution network dynamic scheduling program is executed by a processor to realize the steps of the content distribution network dynamic scheduling method.
The application provides a dynamic scheduling method, a system, equipment and a storage medium of a content distribution network, firstly, a triggering index item and a self-defined scheduling rule configured according to service requirements are obtained, and then a plurality of scheduling strategies are generated based on the triggering index item and the self-defined scheduling rule, wherein the scheduling strategies comprise scheduling service, triggering conditions and a scheduling node range, further, if the triggering index item corresponding to a target node is detected to meet the triggering conditions, the scheduling strategy corresponding to the triggering conditions is triggered and executed, so that the scheduling service of the target node is scheduled to an access node in the scheduling node range, the scheduling strategy can be automatically generated based on the actual service requirements, the self-defined scheduling rule and the self-defined triggering index item, and even if the service of the service requirements changes, the scheduling rule and the triggering index item corresponding to new service can be set on line, namely, the corresponding scheduling rules are adopted for different services to schedule, the requirements of each service can be met, the service can be met widely, and further, the scheduling strategy can be scheduled to the target node in the scheduling node range is triggered when the triggering conditions are met automatically, and the service is scheduled to the service in the triggering node range.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a flowchart of a dynamic scheduling method for a content distribution network according to a first embodiment of the present application;
FIG. 2 is a flowchart of a second embodiment of a dynamic scheduling method for a content distribution network according to the present application;
FIG. 3 is a schematic diagram of a dynamic scheduling method for a content distribution network according to the present application;
Fig. 4 is a schematic structural diagram of a dynamic scheduling device of a content distribution network in a hardware running environment according to an embodiment of the present application;
fig. 5 is a schematic diagram of functional modules of a dynamic scheduling system of a content distribution network according to the present application.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
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 application.
An embodiment of the present application provides a method for dynamically scheduling a content distribution network, in a first embodiment of the present application, referring to fig. 1, the method for dynamically scheduling a content distribution network includes:
Step S10, a trigger index item and a self-defined scheduling rule configured according to service requirements are obtained;
In this embodiment, it should be noted that the trigger indicator item is index information set by user, where the index information includes system index information, service index information, and network index information, where the system index information includes information such as a CPU, a memory, and a disk, the service index information includes information such as access times and access success rate of a service domain name, and the network index information includes network performance information such as access delay, download efficiency, and throughput.
It should be further noted that, the custom scheduling rule includes an index threshold value (i.e., a trigger condition) corresponding to a trigger index item, a duration, a policy influence range, and a scheduling service, where the policy influence range is an area range to which the scheduling rule is applied, for example, the policy influence range may set a large area (an area is divided by adjacent provinces), a province, and specific nodes in the area, for example, when the policy influence range is Shenzhen city, the trigger index item of each node in a preset scheduling system in the Shenzhen city is detected in real time, further, the scheduling service may be understood as each specific service with the same or different service types, for example, one service domain corresponds to one domain name access service, and then different services may refer to different domain name access services.
The step of obtaining the trigger index item and the custom scheduling rule configured according to the service requirement comprises the following steps:
Step S11, acquiring historical index information corresponding to each node in a preset scheduling system, wherein the historical index information comprises system index information, business index information and network index information of different business services;
Step S12, carrying out statistical aggregation processing on the system index information, the business index information and the network index information to obtain all integrated index information, and storing all integrated index information in a preset time sequence database;
Step S13, selecting at least one index item from the integrated index information of the time sequence database as the trigger index item according to the service requirement, and acquiring a custom scheduling rule set according to the trigger index item.
In this embodiment, as an implementation manner, specifically, in order to preset index information of each node in the scheduling system, at least one monitoring device for monitoring the index information is set for each node, where a node may be understood as an edge server with an independent IP address that provides network services for the outside in a CDN cluster, or a group of servers sharing an IP address and providing services for the outside, and further collect historical index information monitored by the monitoring device, where the historical index information includes system index information, service index information, and network index information of different service services, and further, according to a preset index processing policy, statistics aggregation processing is performed on the system index information, the service index information, and the network index information, to obtain each integrated index information, and store each integrated index information in a preset time sequence database, so that the integrated index information can be quickly queried in the preset time sequence database, for example, the number of times of access, access flow, success rate, access delay, access time and other information, and corresponding times of each day may also be counted, and access success rate and other information may be counted.
Further, according to actual service requirements, at least one index item is selected from each piece of integrated index information of the time sequence database as the trigger index item, and a custom scheduling rule set according to the trigger index item is obtained, so that the corresponding trigger index item and the corresponding scheduling rule are configured according to different service requirements, for example, three index items of memory, access flow and access time delay of a specific service are selected as the trigger index items, and the corresponding scheduling rule is set for the three index items respectively.
Step S20, generating a plurality of scheduling strategies based on the triggering index item and the self-defined scheduling rule, wherein the scheduling strategies comprise scheduling business service, triggering conditions and a scheduling node range;
In this embodiment, it should be noted that, the scheduling node range is an area range into which the scheduled service is scheduled, and the scheduling policy specifically includes a trigger indicator item, a numerical judgment (equal to, greater than, less than, etc. conditions), a condition judgment (and, or, non-equal conditions), a duration of the condition (for example, N consecutive statistical periods all satisfy the trigger condition), and an indicator item statistical dimension (node, domain name, communication line, etc.).
As an implementation manner, specifically, for example, three index items of memory in system index information of a specific service, access flow in service index information and access delay in network index information are selected as trigger index items, and corresponding scheduling rules are set for the three index items respectively, so that a scheduling policy can be formed based on combining the three index items and the corresponding scheduling rules, each index item and the corresponding scheduling rules can be generated into a scheduling policy, and a plurality of or all service in a node can be used, so that scheduling is performed by adopting the corresponding scheduling rules for different services, thereby meeting the requirements of each service, and simultaneously determining whether scheduling service is needed or not according to various indexes, namely network index information, system index information and service index information.
Additionally, after determining the scheduling policy, each scheduling policy is parsed to obtain a corresponding conditional expression, each conditional expression is stored in a preset rule database, and the corresponding conditional expression can be directly scanned and executed in the preset rule database.
And step S30, triggering and executing a scheduling strategy corresponding to the triggering condition when the triggering index item corresponding to the target node is detected to meet the triggering condition, so as to schedule the scheduling service of the target node to the scheduling node in the range of the scheduling node.
In this embodiment, it should be noted that, the target node is a node that is within a policy influence range and meets a trigger condition in the custom scheduling rule, specifically, after a scheduling policy is generated, trigger index items of each target node within the policy influence range are detected in real time, when trigger index items of scheduling service on the target node all meet the trigger condition, a scheduling policy corresponding to the trigger condition is triggered and executed, further, when it is detected that trigger index items of a plurality of target nodes all meet the trigger condition in each conditional expression, each scheduling policy is ordered according to a preset priority ordering rule to obtain a priority ordering sequence, each scheduling policy is sequentially executed according to the priority ordering sequence, for example, a scheduling policy priority of a node failure is set to 1, a scheduling policy priority of a service flow exceeding is set to 2, a scheduling policy priority of a service network quality is set to 3, and a figure is smaller to represent a highest priority.
Further, in triggering and executing the scheduling policy, the scheduling service of the target node is scheduled to the scheduling node in the scheduling node range, in an implementation manner, since there are multiple nodes in the scheduling node range, the remaining bearing service capacity of each node can be calculated, and then, according to the size of each remaining bearing service capacity, the node with the largest remaining bearing service capacity is selected as the scheduling node, so that the scheduling service is scheduled to the scheduling node, where it is required to be noted that the scheduling node range and the target node belong to the same area range, or not belong to the same area range, for example, the scheduling node which satisfies the triggering condition belongs to the deep-in city, the scheduling node range can be set in the deep-in city, so that the scheduling service of the target node which satisfies the triggering condition is scheduled to other nodes in the deep-in city, and when the scheduling node range is set in the Guangzhou city, the scheduling service of the target node which satisfies the triggering condition is scheduled to the node in the Guangzhou city.
If the triggering index item corresponding to the target node is detected to meet the triggering condition, triggering and executing a scheduling strategy corresponding to the triggering condition, wherein the scheduling strategy specifically comprises the following steps:
step S31, collecting trigger index items of all target nodes in the strategy influence range;
step S32, when detecting that the trigger index items of a plurality of target nodes all meet the trigger conditions in the conditional expressions, sequencing the scheduling strategies according to a preset priority sequencing rule to obtain a priority sequencing sequence;
and step S33, each scheduling strategy is sequentially executed according to the priority ordering sequence.
In this embodiment, specifically, the monitoring device detects, in real time, information corresponding to the trigger index items of each target node in the policy influence range, and when detecting that the trigger index item of the target node exists and meets the trigger condition in the conditional expression, the scheduling policy of the trigger condition pair is directly triggered and executed, and when detecting that the trigger index items of the plurality of target nodes exist and meet the trigger condition in the conditional expression, priority ordering is required to be performed on each corresponding scheduling policy, and then each scheduling policy is sequentially executed according to the priority ordering sequence.
According to the scheme, namely, the trigger index item and the self-defined scheduling rule configured according to the service requirement are obtained, and then a plurality of scheduling strategies are generated based on the trigger index item and the self-defined scheduling rule, wherein the scheduling strategies comprise scheduling service, trigger conditions and a scheduling node range, further, if the trigger index item corresponding to a target node is detected to meet the trigger conditions, the scheduling strategy corresponding to the trigger conditions is triggered and executed, so that the scheduling service of the target node is scheduled to the scheduling node in the scheduling node range, the scheduling strategy is automatically generated based on the self-defined scheduling rule and the self-defined triggering index item, even if the service is changed, the new scheduling rule and the trigger index item can be set online, the application scene is wider, and further, when the trigger index item of the target node meets the trigger conditions, the scheduling strategy is automatically triggered, and the scheduling service of the target node is scheduled to the scheduling node in the scheduling node range.
Further, referring to fig. 2, according to the first embodiment of the present application, in another embodiment of the present application, after the step of scheduling the scheduled service of the target node to the scheduling node in the range of the scheduling node, the method further includes:
Step A10, calculating a historical access flow peak value of the scheduling business service on the target node in a preselected time based on the historical index information of the target node;
In this embodiment, it should be noted that, the history index information is system index information, service index information and network index information detected by a monitoring device, the preset time is set manually according to an actual situation, for example, the preset time is set to 7 days, specifically, based on the history index information of the target node, a traffic peak value of a scheduled service on the target node in each day in a preselected time is determined, and further, a traffic peak value with the highest peak value is selected as a historical access traffic peak value of the scheduled service on the target node.
Step A20, after executing the dynamic scheduling policy, detecting the node real-time bandwidth of the scheduling node and determining the residual bearing service capacity of the scheduling node;
step A30, determining the call-out access flow based on the magnitude between the historical access flow peak value and the node real-time bandwidth;
step A40, based on the residual bearing service capacity, judging whether the calling-in node can bear the calling-out access flow of the dispatching service;
step A50, if yes, determining that the dispatching is successful;
Step A60, if yes, determining to add a scheduling node based on other scheduling nodes in the range of the scheduling node; scheduling the scheduling service of the target node to the joining scheduling node according to a preset traffic scheduling method, and returning to the execution step: after executing the dynamic scheduling policy, detecting the node real-time bandwidth of the scheduling node, and determining the residual bearing service capacity of the scheduling node.
In this embodiment, specifically, after the scheduled service of the target node is scheduled to the scheduling node in the range of the scheduling node, real-time bandwidth of a node scheduled by the scheduled service on the scheduling node is detected in real time, the scheduled access traffic is determined based on the historical access traffic peak and the size between the node real-time bandwidths, further, based on the remaining bearer service capacity and the preset remaining proportion, whether the scheduling node can bear the scheduled access traffic of the scheduled service is determined, if yes, scheduling success is determined, and then the scheduled service is scheduled to the scheduling node, if no, a joining scheduling node is selected based on other scheduling nodes in the range of the scheduling node, and the scheduled service of the target node is scheduled to the newly joined joining scheduling node and the scheduling node according to a preset traffic scheduling method, for example, the scheduled access traffic of the scheduled service is evenly distributed to the joining scheduling node and the scheduling node, or the scheduled access traffic is evenly distributed to the joining scheduling node according to a preset distribution proportion, and the actual distribution is not specifically limited. After executing the dynamic scheduling policy, detecting a node real-time bandwidth of the scheduling node, and determining a remaining bearer service capacity of the scheduling node, so as to further determine whether the scheduling node and the joining scheduling node can bear a call-out access flow of the scheduling service until all the scheduling nodes within a range of the scheduling node are added or the call-out access flow of the scheduling service is determined, for example, a historical access flow peak value is a, the node real-time bandwidth is B, the remaining bearer service capacity of the scheduling node is marked as C, a ratio (preset remaining ratio) to be reserved is a (0 < = a < = 1), and if max (a, B) <= C (1-a), the call-out access flow capable of bearing the scheduling service is indicated.
And dispatching the dispatching business service of the target node to the joining dispatching node according to a preset flow dispatching method, and returning to the execution step: after the step of executing the dynamic scheduling policy, detecting the node real-time bandwidth of the scheduling node and determining the residual bearing service capacity of the scheduling node, the method further comprises the steps of;
And b, if the residual bearing service capacity corresponding to all the calling nodes in the calling node range is detected to be incapable of bearing the calling access flow of the dispatching service, determining that the dispatching strategy fails to dispatch, and sending out warning information.
In this embodiment, specifically, the party detects that all the joining nodes cannot bear the call access flow of the scheduling service, determines that the scheduling policy fails to schedule, and sends out a warning message, thereby reminding the user to modify the scheduling policy.
By the scheme, the embodiment of the application realizes that the bearing capacity of the dispatching node is fully considered when the dispatching strategy is executed, and the linkage problem that after the fault dispatching exceeds the bearing capacity of the dispatching node, the response failure or slow response and fault node diffusion occur when a user accesses the service is avoided.
Referring to fig. 3, fig. 3 is a schematic diagram of scheduling in the dynamic scheduling method of the content distribution network according to the present application, where 01 is a policy influence range, the policy influence range includes A, B and C three nodes, 02 is an ingress node range, the ingress node range includes D, E, F and G four ingress nodes, trigger index items of each node in the policy influence range are detected in real time, when the trigger index item of the C node is detected to meet a trigger condition, a corresponding scheduling policy is triggered and executed, and the C node in the ingress node range can be randomly selected as an ingress node, so that a scheduling service of the a node is scheduled to the C node, or a node with the highest remaining bearer capacity is selected as an ingress node based on the remaining bearer capacity of each node in the ingress node range, where the remaining bearer capacity is assumed to be: d > E > F > G, further, in the process of scheduling, judging whether the residual bearing capacity of the current scheduling node can bear the scheduling service traffic of the scheduling service on the node A, if so, determining that the scheduling is successful, if not, continuing to select the node E from the range of the scheduling node A, further scheduling the scheduling service on the node A to the nodes C and E, returning to the step of judging whether the scheduling service traffic of the scheduling service on the node A can be borne or not until all nodes in the range of the scheduling node A are added, and if all the nodes in the range of the scheduling node still cannot bear the scheduling service traffic of the scheduling service on the node A, determining that the scheduling is failed, and further sending alarm information.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a dynamic scheduling device of a content distribution network in a hardware running environment according to an embodiment of the present application.
As shown in fig. 4, the content distribution network dynamic scheduling apparatus may include: a processor 1001, such as a CPU, memory 1005, and a communication bus 1002. Wherein a communication bus 1002 is used to enable connected communication between the processor 1001 and a memory 1005. The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Optionally, the content distribution network dynamic scheduling device may further include a rectangular user interface, a network interface, a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. The rectangular user interface may include a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also include a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WIFI interface).
Those skilled in the art will appreciate that the content distribution network dynamic scheduling device structure shown in fig. 4 does not constitute a limitation of the content distribution network dynamic scheduling device, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 4, an operating system, a network communication module, and a content distribution network dynamic scheduler may be included in a memory 1005, which is a type of computer storage medium. The operating system is a program that manages and controls the dynamic scheduling of device hardware and software resources by the content distribution network, supporting the running of the dynamic scheduling of programs by the content distribution network, as well as other software and/or programs. The network communication module is used to enable communication between components within the memory 1005 and with other hardware and software in the content delivery network dynamic scheduling system.
In the content distribution network dynamic scheduling apparatus shown in fig. 4, a processor 1001 is configured to execute a content distribution network dynamic scheduling program stored in a memory 1005, to implement the steps of the content distribution network dynamic scheduling method described in any one of the above.
The specific implementation manner of the dynamic scheduling device for the content distribution network is basically the same as that of each embodiment of the dynamic scheduling method for the content distribution network, and is not repeated here.
In addition, referring to fig. 5, fig. 5 is a schematic functional block diagram of a dynamic scheduling system of a content distribution network according to the present application, and the present application further provides a dynamic scheduling system of a content distribution network, where the dynamic scheduling system of a content distribution network includes:
the acquisition module is used for acquiring the trigger index item configured according to the service requirement and the custom scheduling rule;
The strategy generation module is used for generating a plurality of scheduling strategies based on the trigger index item and the custom scheduling rule, wherein the scheduling strategies comprise scheduling business service, index trigger conditions and a scheduling node range;
And the strategy execution module is used for triggering and executing a scheduling strategy corresponding to the triggering condition when the triggering index item corresponding to the target node is detected to meet the triggering condition, so as to schedule the scheduling service of the target node to the scheduling node in the range of the scheduling node.
Optionally, the acquiring module is further configured to:
Acquiring historical index information corresponding to each node in a preset scheduling system, wherein the historical index information comprises system index information, business index information and network index information of different business services;
carrying out statistical aggregation processing on the system index information, the business index information and the network index information to obtain each piece of integrated index information, and storing each piece of integrated index information in a preset time sequence database;
And according to the service demand, at least one index item is selected from the integrated index information of the time sequence database as the trigger index item, and a self-defined scheduling rule set according to the trigger index item is obtained.
Optionally, the content distribution network dynamic scheduling system is further configured to:
calculating a historical access flow peak of the scheduling business service on the target node in a preselected time based on the historical index information of the target node;
after executing the dynamic scheduling strategy, detecting the node real-time bandwidth of the scheduling node, and determining the residual bearing service capacity of the scheduling node;
determining call-out access flow based on the magnitude between the historical access flow peak value and the node real-time bandwidth;
judging whether the calling-in node can bear calling-out access flow of the dispatching business service or not based on the residual bearing business capacity;
If yes, determining that the dispatching is successful;
If not, determining to add a scheduling node based on other scheduling nodes in the range of the scheduling node; scheduling the scheduling service of the target node to the joining scheduling node according to a preset traffic scheduling method, and returning to the execution step: after executing the dynamic scheduling policy, detecting the node real-time bandwidth of the scheduling node, and determining the residual bearing service capacity of the scheduling node.
Optionally, the content distribution network dynamic scheduling system is further configured to:
If the residual bearing service capacity corresponding to all the calling nodes in the calling node range is detected to be unable to bear the calling access flow of the dispatching service, determining that the dispatching strategy fails to dispatch, and sending out warning information.
Optionally, the content distribution network dynamic scheduling system is further configured to:
Analyzing each scheduling strategy to obtain a corresponding conditional expression, and storing each conditional expression into a preset rule database.
Optionally, the policy enforcement module is further configured to:
collecting trigger index items of all target nodes in the policy influence range;
When detecting that the trigger index items of a plurality of target nodes all meet the trigger conditions in the conditional expressions, sequencing the scheduling strategies according to a preset priority sequencing rule to obtain a priority sequencing sequence;
And executing each scheduling strategy in turn according to the priority ordering sequence.
The specific implementation manner of the dynamic scheduling system of the content distribution network is basically the same as that of each embodiment of the dynamic scheduling method of the content distribution network, and is not repeated here.
An embodiment of the present application provides a storage medium, where the storage medium is a computer readable storage medium, and the computer readable storage medium stores one or more programs, and the one or more programs are further executable by one or more processors to implement the steps of the dynamic scheduling method of a content distribution network according to any one of the foregoing embodiments.
The specific implementation manner of the computer readable storage medium of the present application is basically the same as the embodiments of the dynamic scheduling method of the content distribution network, and will not be described herein.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein, or any application, directly or indirectly, within the scope of the application.
Claims (9)
1. A method for dynamically scheduling a content distribution network, the method comprising:
acquiring a trigger index item configured according to service requirements and a custom scheduling rule;
generating a plurality of scheduling strategies based on the triggering index items and the self-defined scheduling rules, wherein the scheduling strategies comprise scheduling business services, triggering conditions and scheduling node ranges;
Triggering and executing a scheduling strategy corresponding to the triggering condition when the triggering index item corresponding to the target node is detected to meet the triggering condition, so as to schedule the scheduling service of the target node to a scheduling node in the range of the scheduling node;
the step of obtaining the trigger index item and the custom scheduling rule configured according to the service requirement comprises the following steps:
Acquiring historical index information corresponding to each node in a preset scheduling system, wherein the historical index information comprises system index information, business index information and network index information of different business services;
carrying out statistical aggregation processing on the system index information, the business index information and the network index information to obtain each piece of integrated index information, and storing each piece of integrated index information in a preset time sequence database;
And according to the service demand, at least one index item is selected from the integrated index information of the time sequence database as the trigger index item, and a self-defined scheduling rule set according to the trigger index item is obtained.
2. The method of dynamic scheduling of a content distribution network according to claim 1, further comprising, after the step of scheduling the scheduled traffic service of the target node into a scheduling node in the range of scheduling nodes:
calculating a historical access flow peak of the scheduling business service on the target node in a preselected time based on the historical index information of the target node;
after executing the dynamic scheduling strategy, detecting the node real-time bandwidth of the scheduling node, and determining the residual bearing service capacity of the scheduling node;
determining call-out access flow based on the magnitude between the historical access flow peak value and the node real-time bandwidth;
judging whether the calling-in node can bear calling-out access flow of the dispatching business service or not based on the residual bearing business capacity;
If yes, determining that the dispatching is successful;
If not, determining to add a scheduling node based on other scheduling nodes in the range of the scheduling node; scheduling the scheduling service of the target node to the joining scheduling node according to a preset traffic scheduling method, and returning to the execution step: after executing the dynamic scheduling policy, detecting the node real-time bandwidth of the scheduling node, and determining the residual bearing service capacity of the scheduling node.
3. The dynamic scheduling method of content delivery network according to claim 2, wherein, when the scheduling service of the target node is scheduled to the joining scheduling node according to a preset traffic scheduling method, the execution step is returned to: after the step of detecting the node real-time bandwidth of the scheduling node and determining the remaining bearer service capacity of the scheduling node after executing the dynamic scheduling policy, the method further comprises:
If the residual bearing service capacity corresponding to all the calling nodes in the calling node range is detected to be unable to bear the calling access flow of the dispatching service, determining that the dispatching strategy fails to dispatch, and sending out warning information.
4. The method for dynamic scheduling of a content distribution network according to claim 1, further comprising, after the step of generating a plurality of scheduling policies based on the trigger metrics and the custom scheduling rules:
Analyzing each scheduling strategy to obtain a corresponding conditional expression, and storing each conditional expression into a preset rule database.
5. The method for dynamic scheduling of a content distribution network according to claim 4, wherein the scheduling policy further comprises a policy scope of influence.
6. The method for dynamic scheduling of a content distribution network according to claim 5, wherein when it is detected that the trigger indicator item corresponding to the target node satisfies the trigger condition, the step of triggering and executing the scheduling policy corresponding to the trigger condition includes:
collecting trigger index items of all target nodes in the policy influence range;
When detecting that the trigger index items of a plurality of target nodes all meet the trigger conditions in the conditional expressions, sequencing the scheduling strategies according to a preset priority sequencing rule to obtain a priority sequencing sequence;
And executing each scheduling strategy in turn according to the priority ordering sequence.
7. A content distribution network dynamic scheduling system, the content distribution network dynamic scheduling system comprising:
the acquisition module is used for acquiring the trigger index item configured according to the service requirement and the custom scheduling rule;
The strategy generation module is used for generating a plurality of scheduling strategies based on the trigger index item and the custom scheduling rule, wherein the scheduling strategies comprise scheduling business service, index trigger conditions and a scheduling node range;
the strategy execution module is used for triggering and executing a scheduling strategy corresponding to the triggering condition when the triggering index item corresponding to the target node is detected to meet the triggering condition, so as to schedule the scheduling service of the target node to the scheduling node in the range of the scheduling node;
The acquisition module is further used for acquiring historical index information corresponding to each node in a preset scheduling system, wherein the historical index information comprises system index information, business index information and network index information of different business services;
carrying out statistical aggregation processing on the system index information, the business index information and the network index information to obtain each piece of integrated index information, and storing each piece of integrated index information in a preset time sequence database;
And according to the service demand, at least one index item is selected from the integrated index information of the time sequence database as the trigger index item, and a self-defined scheduling rule set according to the trigger index item is obtained.
8. A content distribution network dynamic scheduling apparatus, characterized in that the content distribution network dynamic scheduling apparatus comprises: memory, a processor and a content distribution network dynamic scheduler stored on the memory,
The content distribution network dynamic scheduling program performs the steps of implementing the content distribution network dynamic scheduling method according to any one of claims 1 to 6 by the processor.
9. A storage medium, which is a computer readable storage medium, wherein a content distribution network dynamic scheduler is stored on the computer readable storage medium, the content distribution network dynamic scheduler being executed by a processor to implement the steps of the content distribution network dynamic scheduling method according to any one of claims 1 to 6.
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