CN115002117A - Content distribution network dynamic scheduling method, system, device and storage medium - Google Patents
Content distribution network dynamic scheduling method, system, device and storage medium Download PDFInfo
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Abstract
The application discloses a dynamic scheduling method, a system, equipment and a storage medium for a content distribution network, wherein the dynamic scheduling method for the content distribution network comprises the following steps: the method comprises the steps of obtaining a trigger index item and a user-defined scheduling rule configured according to business requirements, generating a plurality of scheduling strategies based on the trigger index item and the user-defined scheduling rule, wherein the scheduling strategies comprise scheduling business services, index trigger conditions and a call-in node range, and triggering and executing the scheduling strategies corresponding to the trigger conditions when detecting that the trigger index item corresponding to a target node meets the trigger conditions so as to schedule the scheduling business services of the target node to the call-in node in the call-in node range. The method and the device solve the technical problems that when the service changes, a scheduling strategy needs to be developed for the second time to deal with a new fault service scene, so that the access request of a user cannot be effectively accelerated, and the use experience of the user is influenced.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a method, a system, a device, and a storage medium for dynamically scheduling a content delivery network.
Background
Currently, a CDN (Content Delivery Network) provides acceleration services. Taking the domain name access service as an example, the specific process is as follows: the CDN plans edge nodes of the CDN according to geographic positions or network operators, and domain name access can be realized from the edge nodes when users access domain names.
Each edge node in the existing CDN cluster is monitored for service by a corresponding monitoring device, and the monitored running state of the edge node is reported to the scheduling system. When a certain edge node is found to be faulty or the traffic of a service is too large, the service is scheduled to other available edge nodes nearby by using a static fixed scheduling policy, however, the static fixed scheduling policy cannot adapt to the change of the service, the expandability is poor, and a new faulty service scene needs to be dealt with through secondary development, so that the access request of a user cannot be effectively accelerated, and the user experience is influenced.
Disclosure of Invention
The present application mainly aims to provide a method, a system, a device and a storage medium for dynamically scheduling a content distribution network, and aims to solve the technical problem that when a service changes, a new fault service scenario needs to be dealt with by scheduling a policy through secondary development, so that an access request of a user cannot be effectively accelerated, and user experience is affected in the prior art.
In order to achieve the above object, the present application provides a dynamic scheduling method for a content delivery network, where the dynamic scheduling method for a content delivery network includes:
acquiring a trigger index item and a user-defined scheduling rule configured according to a service requirement;
generating a plurality of scheduling strategies based on the triggering index items and the custom scheduling rules, wherein the scheduling strategies comprise scheduling business services, triggering conditions and calling node ranges;
and if the triggering index item corresponding to the target node meets the triggering condition is detected, triggering and executing a scheduling strategy corresponding to the triggering condition so as to schedule the scheduling service of the target node to a call-in node in the range of the call-in node.
The present application further provides a dynamic scheduling system of a content delivery network, where the dynamic scheduling system of the content delivery network is a virtual system, and the dynamic scheduling system of the content delivery network includes:
the acquisition module is used for acquiring a trigger index item and a user-defined scheduling rule configured according to the service requirement;
the strategy generation module is used for generating a plurality of scheduling strategies based on the triggering index items and the user-defined scheduling rules, wherein the scheduling strategies comprise scheduling business services, index triggering conditions and calling node ranges;
and the strategy executing module is used for triggering and executing the scheduling strategy corresponding to the triggering condition if the triggering index item corresponding to the target node is detected to meet the triggering condition, so that the scheduling service of the target node is scheduled to the call-in node in the call-in node range.
The present application further provides a content delivery network dynamic scheduling device, where the content delivery network dynamic scheduling device is an entity device, and the content delivery network dynamic scheduling device includes: 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, on which a content distribution network dynamic scheduling program is stored, and the content distribution network dynamic scheduling program is executed by a processor to implement 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, the application firstly obtains a trigger index item and a custom scheduling rule configured according to business requirements, and then generates a plurality of scheduling strategies based on the trigger index item and the custom scheduling rule, wherein the scheduling strategies comprise scheduling business services, trigger conditions and a call-in node range, further, if the trigger index item corresponding to a target node is detected to meet the trigger conditions, the scheduling strategies corresponding to the trigger conditions are triggered and executed to schedule the scheduling business services of the target node to the call-in node in the call-in node range, thereby realizing the scheduling rules which can be set by self-definition and the trigger index item which is set by self-definition based on actual business requirements, and automatically generating the scheduling strategies, even if the service required by the service changes, the scheduling rule and the trigger index item corresponding to the new service can be set online, that is, the corresponding scheduling rule is adopted for scheduling different services, so that the requirements of each service can be met, the applicable scenes are wider, and further, when the trigger index item of the target node meets the trigger condition, the scheduling strategy is automatically triggered, so that the scheduling service of the target node is scheduled to the call-in node in the call-in 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 present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a dynamic scheduling method for a content distribution network according to a first embodiment of the present application;
fig. 2 is a schematic flowchart of a dynamic scheduling method for a content distribution network according to a second embodiment of the present application;
fig. 3 is a schematic diagram of scheduling in the content delivery network dynamic scheduling method of the present application;
fig. 4 is a schematic structural diagram of a content distribution network dynamic scheduling apparatus of a hardware operating environment according to an embodiment of the present application;
fig. 5 is a functional module diagram of a dynamic scheduling system of a content distribution network according to the present application.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In a first embodiment of the content delivery network dynamic scheduling method of the present application, referring to fig. 1, the content delivery network dynamic scheduling method includes:
step S10, acquiring a trigger index item and a user-defined scheduling rule configured according to the service requirement;
in this embodiment, it should be noted that the trigger index item is index information set by a user in a self-defined manner, 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 customized scheduling rule includes an index threshold (that is, a trigger condition), a duration, a policy influence range, and a scheduled service, where the policy influence range is a region range to which the scheduling rule is applied, for example, the policy influence range may set a specific node in a large region (a region is divided by adjacent provinces), a province, and a region, for example, when the policy influence range is shenzhen city, the trigger index items of each node in a default scheduling system in shenzhen city are detected in real time, and further, the scheduled service may be understood as each specific service with the same or different service types, for example, one service domain name 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 configured according to the service requirement and the user-defined scheduling rule comprises the following steps:
step S11, obtaining 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, performing statistical aggregation processing on the system index information, the service index information and the network index information to obtain each integrated index information, and storing each integrated index information in a preset time sequence database;
step S13, according to the service requirement, at least one index item is selected from each integration 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.
In this embodiment, as an implementable manner, specifically, in order to preset index information of each node in the scheduling system, at least one monitoring device for monitoring index information is set for each node, where a node may be understood as an edge server with an independent IP address for providing network services to the outside in a CDN cluster, or a group of servers sharing one IP address for providing services to the outside, and then history index information monitored by the monitoring device is collected, where the history 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, the system index information, the service index information, and the network index information are respectively subjected to statistical aggregation processing to obtain each integrated index information, and each integrated index information is stored in a preset time sequence database, therefore, the integration index information can be quickly inquired in the preset time sequence database, for example, the information such as the access times, the access flow, the access success rate and the access delay of a specific service on a node in each hour is counted, and the information such as the access times, the access success rate and the access delay corresponding to each day can be aggregated by the statistics.
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 configuration of the corresponding trigger index item and the corresponding scheduling rule according to different service requirements is realized, for example, three index items of a memory, an access flow and an access delay of a specific service are selected as the trigger index items, and then the corresponding scheduling rules are set for the three index items respectively.
Step S20, generating a plurality of scheduling strategies based on the triggering index items and the self-defined scheduling rules, wherein the scheduling strategies comprise scheduling service, triggering conditions and calling node ranges;
in this embodiment, it should be noted that the called node range is an area range to which the scheduling service is called, and the scheduling policy specifically includes a trigger index item, a numerical judgment (equal to, greater than, less than, and the like), a condition judgment (and/or unequal conditions), a duration of a condition (for example, N consecutive statistical periods all satisfy the trigger condition), and a statistical dimension of the index item (node, domain name, communication line, and the like).
As an implementable manner, specifically, for example, three index items of a memory in the system index information, an access flow in the service index information and an access delay in the network index information of a specific service are selected as the trigger index items, and further setting corresponding scheduling rules for the three index items, combining the three index items with the corresponding scheduling rules to form a scheduling policy, generating a scheduling policy for each index item and the corresponding scheduling rule, serving a plurality of or all services in one node, thereby realizing the scheduling by adopting corresponding scheduling rules aiming at different services, meeting the requirements of each service and simultaneously realizing the scheduling of the services according to various indexes, that is, the network index information, the system index information, and the service index information together determine whether a scheduling service is required.
In addition, after the scheduling strategies are determined, each scheduling strategy is analyzed to obtain corresponding conditional expressions, each conditional expression is stored in a preset rule database, and the corresponding conditional expressions can be directly scanned and executed in the preset rule database subsequently.
Step S30, if it is detected that the trigger index item corresponding to the target node satisfies the trigger condition, triggering and executing a scheduling policy corresponding to the trigger condition, so as to schedule the scheduling service of the target node to a call-in node in the call-in node range.
In this embodiment, it should be noted that the target node is a tune-away node that is within a policy influence range in the customized scheduling rule and meets a trigger condition, specifically, after a scheduling policy is generated, trigger indicator items of each target node within the policy influence range are detected in real time, when trigger indicator 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 indicator 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 executed in sequence according to the priority ordering sequence, for example, the scheduling policy priority of a node failure is set to 1, and setting the scheduling policy priority with the exceeding service flow as 2, and setting the scheduling policy priority with the poor service network quality as 3, wherein the smaller the number is, the highest priority is represented.
Further, in the process of triggering and executing the scheduling policy, the scheduling service of the target node is scheduled to the importing node in the importing node range, in an implementation manner, because a plurality of nodes exist in the importing node range, the remaining bearer service capacity of each node can be calculated, and then according to the size of each remaining bearer service capacity, the node with the largest remaining bearer service capacity is selected as the importing node, so that the scheduling service is scheduled to the importing node, wherein it needs to be stated that the importing node range can belong to a region range with the target node or not with the target node, for example, the target node meeting the triggering condition belongs to the Shenzhen city, and the importing node range can be set in the Shenzhen city, so that the scheduling service of the target node meeting the triggering condition is scheduled to other nodes in the Shenzhen city, when the calling node range is set in Guangzhou city, the dispatching business service of the target node meeting the triggering condition is dispatched to the node of the Guangzhou city.
If it is detected that the trigger index item corresponding to the target node meets the trigger condition, triggering and executing a scheduling policy corresponding to the trigger condition, specifically including:
step S31, acquiring trigger index items of each target node 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 each conditional expression, sorting each scheduling strategy according to a preset priority sorting rule to obtain a priority sorting sequence;
and step S33, executing each scheduling strategy in sequence according to the priority sorting sequence.
In this embodiment, specifically, the monitoring device detects information corresponding to the trigger index items of each target node within the policy influence range in real time, when it is detected that the trigger index item of the target node meets the trigger condition in the conditional expression, the scheduling policy of the trigger condition pair is directly triggered to be executed, when it is detected that the trigger index items of the plurality of target nodes meet the trigger condition in the conditional expression, the corresponding scheduling policies need to be prioritized, and then the scheduling policies are sequentially executed according to the prioritized sequence.
According to the scheme, the method comprises the steps of obtaining a trigger index item and a self-defined scheduling rule configured according to business requirements, and further generating a plurality of scheduling strategies based on the trigger index item and the self-defined scheduling rule, wherein the scheduling strategies comprise scheduling business services, trigger conditions and a call-in node range, further, if the trigger index item corresponding to a target node is detected to meet the trigger conditions, triggering and executing the scheduling strategies corresponding to the trigger conditions to schedule the scheduling business services of the target node into the call-in node in the call-in node range, realizing the scheduling rules which can be set based on self-definition and the trigger index item which can be set by self-definition, automatically generating the scheduling strategies, and even if the business services are changed, setting new scheduling rules and trigger index items on line, the method has a wide application scene, and further, when the trigger index item of the target node meets the trigger condition, a scheduling strategy is automatically triggered, so that the scheduling service of the target node is scheduled to the call-in node in the range of the call-in node.
Further, referring to fig. 2, based on the first embodiment in the present application, in another embodiment of the present application, after the step of scheduling the scheduled traffic service of the target node to a call-in node in the range of the call-in nodes, the method further includes:
step A10, based on the historical index information of the target node, calculating the historical access flow peak value of the scheduling service on the target node in the preselected time;
in this embodiment, it should be noted that the historical index information is system index information, service index information, and network index information detected by a monitoring device, the preset time is manually set according to an actual situation, for example, the preset time is set to 7 days, specifically, based on the historical index information of the target node, a traffic peak value of a scheduling service on the target node every day in a preselected time is determined, and further, a traffic peak value with a highest peak value is selected as a historical access traffic peak value of the scheduling service on the target node.
Step A20, after executing the dynamic scheduling policy, detecting the node real-time bandwidth of the call-in node, and determining the remaining bearer service capacity of the call-in node;
step A30, determining the called access flow based on the historical access flow peak value and the size between the real-time bandwidths of the nodes;
step a40, based on the remaining bearer service capacity, determining whether the call-in node can bear the call-out access traffic of the scheduling service;
step A50, if yes, determining that the scheduling is successful;
step A60, if yes, determining to join a scheduling node based on other call nodes in the call node range; scheduling the scheduling service of the target node to the joining scheduling node according to a preset flow scheduling method, and returning to the execution step: and after the dynamic scheduling strategy is executed, detecting the node real-time bandwidth of the call-in node, and determining the residual bearing service capacity of the call-in node.
In this embodiment, specifically, after scheduling a scheduling service of the target node to a call node in the range of the call node, a real-time bandwidth of a node scheduled by the scheduling service on the call node is detected in real time, the call access traffic is determined based on a size between a historical access traffic peak value and the real-time bandwidth of the node, further, whether the call node can bear the call access traffic of the scheduling service is determined based on the remaining bearer traffic capacity and a preset remaining proportion, if yes, the scheduling is determined to be successful, the scheduling service is scheduled to the call node, if not, based on other call nodes in the range of the call node, a joining scheduling node is selected, the scheduling 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 called access traffic of the scheduled service is averagely distributed to the joining scheduling node and the scheduling node, or the called access traffic of the scheduled service is averagely distributed to the joining scheduling node and the scheduling node according to a preset distribution proportion, which may be set according to an actual situation, where no specific limitation is made, and then the execution step is returned: after the dynamic scheduling policy is executed, detecting a node real-time bandwidth of the call node, and determining a remaining bearer service capacity of the call node, so as to further determine whether the call node and the joining scheduling node can bear call access traffic of the scheduling service until all call nodes joining the range of the call node are added or call access traffic of the scheduling service is determined, for example, a peak value of historical access traffic is a, the node real-time bandwidth is B, the remaining bearer service capacity of the call node is C, a ratio (a preset remaining ratio) required to be reserved is a (0 ═ a ═ 1), and if max (a, B) <c (1-a), the call access traffic capable of bearing the scheduling service is represented.
And scheduling the scheduling service of the target node to the joining scheduling node according to a preset flow scheduling method, and returning to the execution step: after the dynamic scheduling strategy is executed, detecting the node real-time bandwidth of the call-in node, and determining the residual bearing service capacity of the call-in node;
and b, if detecting that the residual bearing service capacity corresponding to all the call-in nodes in the range of the call-in nodes cannot bear the call-out access flow of the scheduling service, determining that the scheduling of the scheduling strategy fails, and sending out warning information.
In this embodiment, specifically, the party detects that all the call nodes added cannot bear the call access traffic of the scheduling service, determines that the scheduling of the scheduling policy fails, and sends out an alert message, thereby prompting the user to modify the scheduling policy.
Through the scheme, the embodiment of the application realizes that the bearing capacity of the call-in node is fully considered when the scheduling strategy is executed, and avoids the linkage problem that the response fails or the response is slow and the fault node spreads when a user accesses the service after the fault call exceeds the bearing capacity of the call-in node.
Referring to fig. 3, fig. 3 is a schematic diagram of scheduling in the dynamic scheduling method of the content distribution network of the present application, where 01 is a policy impact range, where the policy impact range includes A, B and C nodes, 02 is a tuning-in node range, where the tuning-in node range includes D, E, F and G four tuning-in nodes, a trigger index item of each node in the policy impact range is detected in real time, when it is detected that the trigger index item of the C node satisfies a trigger condition, a corresponding scheduling policy is triggered and executed, the C node in the tuning-in node range can be randomly selected as a tuning-in node, and then a scheduling service of the a node is scheduled to the C node, or based on the remaining bearer capacity of each node in the tuning-in node range, a node with the highest remaining bearer capacity is selected as a tuning-in node, and it is assumed that the relationship of the remaining bearer capacity is: d, E, F and G, further, in the scheduling process, judging whether the residual bearing capacity of the current called node can bear the called service flow 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 called node, then scheduling the scheduling service on the node A to the nodes C and E, returning to the step of judging whether the called service flow of the scheduling service on the node A can be borne until all the nodes in the range of the called node are added, if all the nodes in the range of the called node still cannot bear the called service flow of the scheduling service on the node A, determining that the scheduling is failed, and then sending alarm information.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a content distribution network dynamic scheduling device of a hardware operating 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, a memory 1005, and a communication bus 1002. The communication bus 1002 is used for realizing connection communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory 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, a Radio Frequency (RF) circuit, a sensor, an audio circuit, a WiFi module, and the like. The rectangular user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also comprise 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 apparatus architecture shown in fig. 4 does not constitute a limitation of the content distribution network dynamic scheduling apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 4, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, and a content distribution network dynamic scheduler. The operating system is a program for managing and controlling hardware and software resources of the content distribution network dynamic scheduling device, and supports the running of the content distribution network dynamic scheduling program and other software and/or programs. The network communication module is used for communication among the components in the memory 1005 and with other hardware and software in the content distribution network dynamic scheduling system.
In the content distribution network dynamic scheduling apparatus shown in fig. 4, the processor 1001 is configured to execute the content distribution network dynamic scheduling program stored in the memory 1005, and implement the steps of the content distribution network dynamic scheduling method described in any one of the above.
The specific implementation of the content distribution network dynamic scheduling device of the present application is basically the same as the embodiments of the content distribution network dynamic scheduling method, and is not described herein again.
In addition, referring to fig. 5, fig. 5 is a functional module schematic diagram of a content distribution network dynamic scheduling system according to the present application, and the present application further provides a content distribution network dynamic scheduling system, where the content distribution network dynamic scheduling system includes:
the acquisition module is used for acquiring a trigger index item and a user-defined scheduling rule configured according to the service requirement;
the strategy generation module is used for generating a plurality of scheduling strategies based on the triggering index items and the user-defined scheduling rules, wherein the scheduling strategies comprise scheduling business services, index triggering conditions and calling node ranges;
and the strategy executing module is used for triggering and executing the scheduling strategy corresponding to the triggering condition if the triggering index item corresponding to the target node is detected to meet the triggering condition, so that the scheduling service of the target node is scheduled to the call-in node in the call-in node range.
Optionally, the obtaining 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, service index information and network index information of different service services;
performing statistical aggregation processing on the system index information, the service index information and the network index information to obtain each integrated index information, and storing each integrated index information in a preset time sequence database;
and according to the service requirement, at least one index item is selected from all the integration index information of the time sequence database as the trigger index item, and a user-defined scheduling rule set according to the trigger index item is obtained.
Optionally, the content distribution network dynamic scheduling system is further configured to:
based on the historical index information of the target node, calculating a historical access flow peak value of the scheduling business service on the target node within a preselected time;
after the dynamic scheduling strategy is executed, detecting the node real-time bandwidth of the call-in node and determining the residual bearing service capacity of the call-in node;
determining the called-out access flow based on the historical access flow peak value and the size between the real-time bandwidths of the nodes;
judging whether the call-in node can bear the call-out access flow of the scheduling service based on the residual bearing service capacity;
if so, determining that the scheduling is successful;
if not, determining to join the scheduling node based on other calling nodes in the calling node range; scheduling the scheduling service of the target node to the joining scheduling node according to a preset flow scheduling method, and returning to the execution step: and after the dynamic scheduling strategy is executed, detecting the node real-time bandwidth of the call-in node, and determining the residual bearing service capacity of the call-in node.
Optionally, the content distribution network dynamic scheduling system is further configured to:
and if the remaining bearing service capacity corresponding to all the call-in nodes in the range of the call-in nodes is detected to be incapable of bearing the call-out access flow of the scheduling service, determining that the scheduling of the scheduling strategy fails, and sending out alarm information.
Optionally, the content distribution network dynamic scheduling system is further configured to:
and analyzing each scheduling strategy to obtain corresponding conditional expressions, and storing each conditional expression into a preset rule database.
Optionally, the policy enforcement module is further configured to:
acquiring trigger index items of each target node in the strategy influence range;
when detecting that trigger index items of a plurality of target nodes all meet trigger conditions in each conditional expression, sequencing each scheduling strategy according to a preset priority sequencing rule to obtain a priority sequencing sequence;
and executing each scheduling strategy in sequence according to the priority sequencing sequence.
The specific implementation of the content distribution network dynamic scheduling system of the present application is basically the same as the embodiments of the content distribution network dynamic scheduling method, and is not described herein again.
The present application provides a storage medium, which is a computer-readable storage medium, and the computer-readable storage medium stores one or more programs, which can be further executed by one or more processors for implementing the steps of the content distribution network dynamic scheduling method described in any one of the above.
The specific implementation manner of the computer-readable storage medium of the present application is substantially the same as that of each embodiment of the content distribution network dynamic scheduling method, and is not described herein again.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (10)
1. A dynamic scheduling method for a content distribution network is characterized in that the dynamic scheduling method for the content distribution network comprises the following steps:
acquiring a trigger index item and a user-defined scheduling rule configured according to a service requirement;
generating a plurality of scheduling strategies based on the trigger index items and the custom scheduling rules, wherein the scheduling strategies comprise scheduling business services, triggering conditions and calling node ranges;
and if the triggering index item corresponding to the target node meets the triggering condition is detected, triggering and executing a scheduling strategy corresponding to the triggering condition so as to schedule the scheduling service of the target node to a call-in node in the range of the call-in node.
2. The dynamic scheduling method of content delivery network according to claim 1, wherein the step of obtaining the trigger index item configured according to the service requirement and the customized scheduling rule comprises:
acquiring historical index information corresponding to each node in a preset scheduling system, wherein the historical index information comprises system index information, service index information and network index information of different service services;
performing statistical aggregation processing on the system index information, the service index information and the network index information to obtain each integrated index information, and storing each integrated index information in a preset time sequence database;
and according to the service requirement, at least one index item is selected from all the integration index information of the time sequence database as the trigger index item, and a user-defined scheduling rule set according to the trigger index item is obtained.
3. The method for dynamic scheduling of a content delivery network according to claim 1, wherein after the step of scheduling the scheduled traffic service of the target node into a calling node in the range of calling nodes, further comprising:
based on the historical index information of the target node, calculating a historical access flow peak value of the scheduling business service on the target node within a preselected time;
after the dynamic scheduling strategy is executed, detecting the node real-time bandwidth of the call-in node and determining the residual bearing service capacity of the call-in node;
determining the call-out access flow based on the historical access flow peak value and the size between the real-time bandwidths of the nodes;
judging whether the call-in node can bear the call-out access flow of the scheduling service based on the residual bearing service capacity;
if so, determining that the scheduling is successful;
if not, determining to join the scheduling node based on other calling nodes in the calling node range; scheduling the scheduling service of the target node to the joining scheduling node according to a preset flow scheduling method, and returning to the execution step: and after the dynamic scheduling strategy is executed, detecting the node real-time bandwidth of the call-in node, and determining the residual bearing service capacity of the call-in node.
4. The dynamic scheduling method of content delivery network according to claim 3, wherein the scheduling service of the target node is scheduled to the joining scheduling node according to the preset traffic scheduling method, and the execution steps are returned: after the dynamic scheduling strategy is executed, detecting the node real-time bandwidth of the call-in node, and determining the residual bearing service capacity of the call-in node;
and if the remaining bearing service capacity corresponding to all the call-in nodes in the range of the call-in nodes is detected to be incapable of bearing the call-out access flow of the scheduling service, determining that the scheduling of the scheduling strategy fails, and sending out alarm information.
5. The method for dynamically scheduling in a content distribution network according to claim 1, wherein after the step of generating a plurality of scheduling policies based on the trigger metric items and the customized scheduling rules, the method further comprises:
and analyzing each scheduling strategy to obtain corresponding conditional expressions, and storing each conditional expression into a preset rule database.
6. The content distribution network dynamic scheduling method of claim 5, wherein the scheduling policy further comprises a policy impact scope.
7. The method for dynamically scheduling a content delivery network according to claim 6, wherein the step of triggering and executing the scheduling policy corresponding to the trigger condition when it is detected that the trigger indicator item corresponding to the target node satisfies the trigger condition comprises:
acquiring trigger index items of each target node in the strategy influence range;
when detecting that trigger index items of a plurality of target nodes all meet trigger conditions in each conditional expression, sequencing each scheduling strategy according to a preset priority sequencing rule to obtain a priority sequencing sequence;
and executing each scheduling strategy in sequence according to the priority sequencing sequence.
8. A content distribution network dynamic scheduling system, characterized in that the content distribution network dynamic scheduling system comprises:
the acquisition module is used for acquiring a trigger index item and a user-defined scheduling rule configured according to the service requirement;
the strategy generation module is used for generating a plurality of scheduling strategies based on the triggering index items and the user-defined scheduling rules, wherein the scheduling strategies comprise scheduling business services, index triggering conditions and calling node ranges;
and the strategy executing module is used for triggering and executing the scheduling strategy corresponding to the triggering condition if the triggering index item corresponding to the target node is detected to meet the triggering condition, so that the scheduling service of the target node is scheduled to the call-in node in the call-in node range.
9. A content distribution network dynamic scheduling apparatus, characterized in that the content distribution network dynamic scheduling apparatus comprises: a memory, a processor, and a content distribution network dynamic scheduler stored on the memory,
the content distribution network dynamic scheduling program is executed by the processor to implement the content distribution network dynamic scheduling method according to any one of claims 1 to 7.
10. A storage medium which is a computer-readable storage medium, wherein the computer-readable storage medium has a content distribution network dynamic scheduling program stored thereon, and the content distribution network dynamic scheduling program is executed by a processor to implement the content distribution network dynamic scheduling method according to any one of claims 1 to 7.
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