WO2024131402A1 - Service resource scheduling method and apparatus - Google Patents

Abstract

Provided in the embodiments of the present disclosure are a service resource scheduling method and apparatus. The method comprises: by means of acquiring a scheduling topological relationship between a user equipment (UE) and a content delivery network (CDN), acquiring a topological relationship between a broadband access server (BRAS) and a service router (SR) according to the scheduling topological relationship; according to the topological relationship between the BRAS and the SR, collecting network quality information of the BRAS and the SR, and obtaining a network quality test result; according to the network quality test result, calculating network quality of service (QoS) of service nodes of the UE and the CDN; and selecting an optimal service node according to a QoS value decision, and scheduling a service resource of the UE on the basis of the optimal service node.

Description

Service resource scheduling method and device

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based on Chinese patent application CN202211649540.3, filed on December 21, 2022, with the invention name “Scheduling method and device for service resources”, and claims the priority of the patent application, and all the contents disclosed therein are incorporated into this application by reference.

Technical Field

The present disclosure relates to the field of communications, and in particular to a method and device for scheduling service resources.

Background technique

With the rapid development of communication technology and semiconductor technology, the widespread popularization of mobile Internet, the rapid increase in the number of users of online TV and self-media, and the integration of video into thousands of industries as a production factor, the digital economy has brought more demands. At the same time, higher standards have been proposed for content delivery networks (CDN) and user experience, and the requirements for network quality have shifted from high stability and low latency to high security and super network perception; the requirements for network computing power have shifted from high performance and low cost to high flexibility and super computing power coordination.

The scheduling mechanism of traditional CDN networks selects the optimal node based on the home node pre-set by the user's IP address segment, the priority of the home node, and the remaining capacity (remaining bandwidth, number of concurrent connections). When the node capacity is sufficient to meet the user's service capacity, the optimal node returned by the CDN is actually constant. During peak business hours, it cannot dynamically perceive the impact of factors such as network quality (such as latency, jitter, and packet loss). Although the scheduling strategy schedules users to the node with the best capacity, the user service quality is not necessarily the best. When the network is congested, the service quality of the CDN business will decline, affecting the user experience.

The existing scheduling system based on network quality usually only takes network quality as the comprehensive indicator of each service node, and periodically generates the network health coefficient of this node according to the service quality of each node (such as packet loss rate, quality weight, download rate, etc.). The scheduling optimization finally realized is for CDN server nodes, which cannot meet the scenario where the same node serves users in multiple different network segments and some network segments have poor network quality. Because in actual business scenarios, the scheduling strategies of different network segments are often different, and there will be some identical service nodes between the scheduling strategies of different IP segments, and there may also be some other nodes with the same priority. Therefore, the index value obtained by periodically counting the network quality on the service node side is lagging. When the business volume of each node is uneven or the network of a small number of users is poor, the packet loss rate and download rate obtained by statistics may directly affect whether this node can continue to schedule users of other IP segments, which is far from fitting the actual business scenario.

Summary of the invention

The embodiments of the present disclosure provide a method and device for scheduling service resources, so as to at least solve the problem in the related art that only the network quality is used as a scheduling indicator, and all user IP sets and their affiliated nodes cannot be taken into account.

According to an embodiment of the present disclosure, a method for scheduling service resources is provided, comprising: obtaining a scheduling topology relationship between a user terminal UE and a content scheduling network CDN, and obtaining a topology relationship between a broadband access server BRAS and a service router SR according to the scheduling topology relationship; collecting network quality information of the BRAS and the SR according to the topology relationship between the BRAS and the SR, and obtaining a network quality detection result; and calculating the network quality detection result according to the network quality detection result. a network quality indicator QOS between the UE and the service node of the CDN network; selecting an optimal service node according to the QOS indicator value, and scheduling service resources of the UE based on the optimal service node.

According to another embodiment of the present disclosure, a scheduling device for service resources is provided, including: a topology acquisition module, configured to acquire a scheduling topology relationship between a user terminal UE and a content scheduling network CDN, and acquire a topology relationship between a broadband access server BRAS and a service router SR according to the scheduling topology relationship; a quality detection module, configured to collect network quality information of the BRAS and the SR according to the topology relationship between the BRAS and the SR, and obtain a network quality detection result; an indicator calculation module, configured to calculate a network quality indicator QOS between the UE and a service node of the CDN network according to the network quality detection result; and a decision scheduling module, configured to select an optimal service node according to the QOS indicator value, and schedule the service resources of the UE based on the optimal service node.

According to another embodiment of the present disclosure, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the steps of any one of the above method embodiments when running.

According to another embodiment of the present disclosure, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a hardware structure block diagram of a computer terminal of a method for scheduling service resources according to an embodiment of the present disclosure;

FIG2 is a flow chart of scheduling of service resources according to an embodiment of the present disclosure;

FIG3 is a flow chart of scheduling of service resources according to an embodiment of the present disclosure;

FIG4 is a flow chart of scheduling of service resources according to an embodiment of the present disclosure;

FIG5 is a structural block diagram of a device for scheduling service resources according to an embodiment of the present disclosure;

FIG6 is a structural block diagram of a device for scheduling service resources according to an embodiment of the present disclosure;

7 is a structural block diagram of a device for scheduling service resources according to an embodiment of the present disclosure;

FIG8 is a structural block diagram of a device for scheduling service resources according to an embodiment of the present disclosure;

FIG9 is a schematic diagram of the architecture of a service resource scheduling device according to an embodiment of the present disclosure;

FIG10 is a flow chart of a service resource scheduling method according to an embodiment of the present disclosure;

FIG11 is a schematic diagram of the architecture of a SR-BRAS network quality measurement model according to an embodiment of the present disclosure;

FIG. 12 is a schematic diagram of a method for dynamically optimizing network quality based on a scheduling path according to an embodiment of the disclosed scenario.

Detailed ways

The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

It should be noted that the terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a computer terminal as an example, FIG1 is a hardware structure block diagram of a computer terminal of a method for scheduling service resources in an embodiment of the present disclosure. As shown in FIG1 , the computer terminal may include one or more (only one is shown in FIG1 ) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the above-mentioned computer terminal may also include a transmission device 106 for communication functions and an input and output device 108. A person of ordinary skill in the art will appreciate that the structure shown in FIG1 is only For illustration purposes only, the structure of the computer terminal is not limited. For example, the computer terminal may include more or fewer components than those shown in FIG. 1 , or may have a configuration different from that shown in FIG. 1 .

The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the scheduling method of service resources in the embodiment of the present disclosure. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

The transmission device 106 is used to receive or send data via a network. The above-mentioned network example may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, RF) module, which is used to communicate with the Internet wirelessly.

In this embodiment, a method for scheduling service resources running on the above-mentioned computer terminal is provided. FIG. 2 is a flow chart of scheduling service resources according to an embodiment of the present disclosure. As shown in FIG. 2 , the flow chart includes the following steps:

Step S202, obtaining a scheduling topology relationship between a user terminal (User Equipment, UE) and a content scheduling network CDN, and obtaining a topology relationship between a broadband access server (Broadband Remote Access Server, BRAS) and a service router (Service Router, SR) according to the scheduling topology relationship;

Step S204, collecting network quality information of the BRAS and the SR according to the topological relationship between the BRAS and the SR, and obtaining a network quality detection result;

Step S206, calculating the network quality index (Quality of Service, QOS) of the UE and the service node of the CDN network according to the network quality detection result;

Step S208: selecting the best service node according to the QOS indicator value, and scheduling the service resources of the UE based on the best service node.

Through the above steps, by obtaining the scheduling topology relationship between the user terminal UE and the content scheduling network CDN, the topology relationship between the broadband access server BRAS and the service router SR is obtained according to the scheduling topology relationship; according to the topology relationship between BRAS and SR, the network quality information of BRAS and SR is collected, and the network quality detection result is obtained; according to the network quality detection result, the network quality index QOS of the service node of the UE and CDN network is calculated; according to the QOS index value, the optimal service node is selected, and the service resources of the UE are scheduled based on the optimal service node. The problem that in some cases, only network quality is used as a scheduling index and all user IP sets and their belonging nodes cannot be taken into account is solved, and the scheduling of service resources taking into account all user IP sets and their belonging nodes is achieved, and the effect of improving the service quality of the content scheduling network is achieved.

The execution subject of the above steps may be a base station, a terminal, etc., but is not limited thereto.

In an exemplary embodiment, obtaining a scheduling topology relationship between a user terminal UE and a content scheduling network CDN includes: obtaining a scheduling topology relationship based on a scheduling policy between a service node of the CDN network and the UE, wherein the scheduling topology relationship includes at least one of the following: an association relationship between the UE's IP address and the UE's IP set, an association relationship between the UE's IP set and a service node, an association relationship between a service node and an SR, and an association relationship between the UE's IP set and a BRAS.

In an exemplary embodiment, before calculating the network quality indicator QOS between the UE and the service node of the CDN network according to the network quality detection result, the method further includes: the scheduling server of the CDN network verifies the access control of the network quality detection result; If the verification is successful, the network quality detection result is obtained; if the verification is not successful, the access permission is re-obtained. FIG3 is a flowchart of the scheduling of service resources according to an embodiment of the present disclosure. As shown in FIG3, the process includes the following steps:

Step S302, obtaining a scheduling topology relationship between the user terminal UE and the content scheduling network CDN, and obtaining a topology relationship between the broadband access server BRAS and the service router SR according to the scheduling topology relationship;

Step S304, collecting network quality information of the BRAS and the SR according to the topological relationship between the BRAS and the SR, and obtaining a network quality detection result;

Step S306, the scheduling server of the CDN network verifies the access right to the network quality detection result. If the verification is successful, the network quality detection result is obtained; if the verification is not successful, the access right is re-obtained;

Step S308, calculating the network quality indicator QOS of the UE and the service node of the CDN network according to the network quality detection result;

Step S310: selecting the best service node according to the QOS indicator value, and scheduling the service resources of the UE based on the best service node.

In an exemplary embodiment, the network quality detection result includes at least one of the following: delay detection information; jitter detection information; and packet loss rate detection information.

In an exemplary embodiment, the network quality index QOS between the UE and the service node of the CDN network is calculated according to the network quality detection result, including: performing weighted calculation according to the delay detection information, jitter detection information, and packet loss rate detection information to obtain the QOS index value.

In an exemplary embodiment, before selecting the optimal service node according to the QOS indicator value, the method further includes: the UE sends a redirection request to the scheduling server of the CDN network. FIG4 is a flow chart of the scheduling of service resources according to an embodiment of the present disclosure. As shown in FIG4, the process includes the following steps:

Step S402, obtaining a scheduling topology relationship between the user terminal UE and the content scheduling network CDN, and obtaining a topology relationship between the broadband access server BRAS and the service router SR according to the scheduling topology relationship;

Step S404, collecting network quality information of the BRAS and the SR according to the topological relationship between the BRAS and the SR, and obtaining a network quality detection result;

Step S406, the scheduling server of the CDN network verifies the access right to the network quality detection result. If the verification is successful, the network quality detection result is obtained; if the verification is not successful, the access right is re-obtained;

Step S408, calculating the network quality indicator QOS of the UE and the service node of the CDN network according to the network quality detection result;

Step S410, the UE sends a redirection request to the scheduling server of the CDN network;

Step S412: selecting the best service node according to the QOS indicator value, and scheduling the service resources of the UE based on the best service node.

In an exemplary embodiment, the optimal service node is selected based on the QOS index value, including: based on the QOS index value and the remaining service resources of the service node, the service node with the smallest QOS index value and the most remaining service resources is selected as the optimal service node.

In an exemplary embodiment, after selecting the optimal service node based on the QOS indicator value decision, the method also includes: detecting the network quality detection result of the specified link, and when the network quality detection result of the specified link does not reach a preset threshold, controlling the BRAS and SR to adjust network parameters to optimize the network quality detection result of the specified link.

In an exemplary embodiment, scheduling service resources for a UE based on an optimal service node includes: the optimal service node receiving service request information from the UE; and the optimal service node providing service resources to the UE.

Through the description of the above implementation methods, the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the embodiment of the present disclosure is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, disk, CD), including a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the method described in the embodiment of the present disclosure.

In this embodiment, a scheduling device for service resources is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and/or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

Figure 5 is a structural block diagram of a scheduling device for service resources according to an embodiment of the present disclosure. As shown in Figure 5, the scheduling device 50 includes: a topology acquisition module 510, which is used to obtain the scheduling topology relationship between the user terminal UE and the content scheduling network CDN, and obtain the topology relationship between the broadband access server BRAS and the service router SR according to the scheduling topology relationship; a quality detection module 520, which is used to collect network quality information of the BRAS and the SR according to the topological relationship between the BRAS and the SR, and obtain the network quality detection result; an indicator calculation module 530, which is used to calculate the network quality indicator QOS of the UE and the service node of the CDN network according to the network quality detection result; a decision scheduling module 540, which is used to select the optimal service node according to the QOS indicator value, and schedule the service resources of the UE based on the optimal service node.

In an exemplary embodiment, Figure 6 is a structural block diagram of a scheduling device for service resources according to an embodiment of the present disclosure. As shown in Figure 6, in addition to the modules in Figure 5, the scheduling device 60 also includes: a verification module 610, which is arranged in the scheduling server of the CDN network, and is used to verify the access rights of the network quality detection results. If the verification passes, the network quality detection results are obtained and sent to the indicator calculation module; if the verification fails, the access rights are re-acquired.

In an exemplary embodiment, Figure 7 is a structural block diagram of a scheduling device for service resources according to an embodiment of the present disclosure. As shown in Figure 7, in addition to the modules in Figure 6, the scheduling device 70 also includes: a sending module 710, which is arranged in the UE and is used to send a redirection request to the scheduling server of the CDN network.

In an exemplary embodiment, Figure 8 is a structural block diagram of a scheduling device for service resources according to an embodiment of the present disclosure. As shown in Figure 8, in addition to the modules in Figure 7, the scheduling device 80 also includes: a receiving module 810 for receiving service request information from the UE; and a scheduling module 820 for providing service resources to the UE.

It should be noted that the above modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

The embodiments of the present disclosure further provide a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any one of the above method embodiments when running.

In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

An embodiment of the present disclosure further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

In an exemplary embodiment, the electronic device may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.

In this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

Obviously, the modules or steps of the above-mentioned embodiments of the present disclosure can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. In this way, the embodiments of the present disclosure are not limited to any specific combination of hardware and software.

In order to enable those skilled in the art to better understand the technical solutions of the embodiments of the present disclosure, the technical solutions are described below in conjunction with scenario embodiments.

Scenario Example 1

In view of the problems in some situations, a scheduling system based on the network quality between all user IP segments and all home service nodes is needed. In the scheduling algorithm, different network indicator values of different user IP sets to service nodes can be considered, and users can be scheduled to the service nodes with the best resources and the best network (including multi-network plane nodes) in a differentiated manner. At the same time, it is also necessary to be able to dynamically optimize the links with poor service quality.

In the embodiment of this scenario, the technical problem to be solved is to provide a CDN scheduling system based on IP network quality. By opening up the network quality query interface between CDN and the bearer network, the network quality information of all links between each CDN node and the user group (IP set) is obtained, and the service quality index (Quality Of Service, QOS) index between each user IP set and each CDN service node (including the QOS index in the multi-network plane service scenario) is calculated, and it is used as a scheduling strategy factor, breaking the constraints of the original scheduling mechanism, so that the CDN scheduling system can dynamically perceive the network quality of the computing power network (such as latency, jitter, packet loss), make up for the shortcomings of the CDN optimal node selection algorithm in the global scheduling process, and schedule users to the service node with the best capability and the best network, thereby comprehensively improving the user service quality; at the same time, according to the actual business situation of each user IP set to each node service point, it can timely adjust the network configuration of the optimal link, reasonably allocate and predict the service resources of the node, etc.

In this scenario embodiment, a CDN scheduling system based on IP network quality, namely a service resource scheduling device, is provided. FIG. 9 is an architectural schematic diagram of a service resource scheduling device according to an embodiment of the disclosed scenario. As shown in FIG. 9 , the device includes:

CDN management platform (CDN Manager, CDNM), CDN scheduling server (Global Service Load Balance, GSLB), CDN service node (CDN Service, CDNS), network controller cluster (Network Controller Cluster, NCC), broadband access server (Broadband Remote Access Server, BRAS), service router (Service Router, SR), user management module (User Management Module, UMM), user terminal (User Equipment, UE).

Among them, there are CDN management platform (marked as CDNM in Figure 9), CDN scheduling server (marked as GSLB in Figure 9), CDN service node (marked as CDNS in Figure 9), network controller cluster (marked as NCC in Figure 9), broadband access server (marked as BRAS in Figure 9), service router (marked as SR in Figure 9), user management module (marked as UMM in Figure 9), and user terminal (marked as UE in Figure 9).

In the present scenario embodiment, the topology acquisition module in the above embodiment can be set on the CDN management platform, the quality detection module can be set on the service router, the indicator calculation module and the decision scheduling module can be set on the CDN scheduling server, the verification module can also be set on the CDN scheduling server, the sending module is set on the user equipment UE, the receiving module can be set on the user management module or the CDN management platform, and the scheduling module can be set on the CDN scheduling server. It should be noted that the various modules in the embodiment of the present disclosure and the various components of the scheduling device in the embodiment of the present disclosure scenario are similar to each other. The corresponding relationship between them is not strictly limited, and the above is only an example, not a specific limitation. In the actual implementation process, a scheduling device with different component arrangements or component naming can be designed according to actual conditions.

CDN Management Platform (CDNM): manages the dispatching servers, service nodes and other equipment resources in the CDN system, automatically receives CDN user information synchronized by the User Management Module (UMM) (such as: the topological relationship between the user IP address segment and IP set, the topological relationship between the IP set and the BRAS device, and the topological relationship between the service node and the SR device), and maintains the dispatching topological relationship between the user IP set and the service node and other service configurations. At the same time, it is also responsible for synchronizing various service configurations to the dispatching server and network controller.

CDN Scheduling Server (GSLB): Responsible for collecting performance data from CDN service nodes CDNS regularly, and obtaining the status and resource information of each service node. Regularly access the network controller, and calculate the network quality of each IP set to the service node based on the CDN user IP address segment and scheduling topology. The network quality from the user to each node is included in the scheduling factor, and the optimal node is decided and returned to the user terminal.

CDN service node (CDNS): responsible for receiving performance collection requests from CDN scheduling node GSLB and returning collection results. At the same time, it receives service requests from user terminals UE and provides media services.

Broadband access server (BRAS): As the entrance to Internet services, it is deployed in the user-side metropolitan area network and is associated with the user's IP address set. It is a bridge between the access network and the backbone network, responsible for user identity authentication and firmly controlling the user's data in and out of the backbone network.

Service Router (SR): As a dedicated line access gateway, it is deployed in the metropolitan area network on the CDN service node side, receives service configuration data from the CDN management platform, and is responsible for dialing and measuring the network quality between the service node SR and the user terminal BRAS.

Network Controller Cluster (NCC): Deployed in the bearer network, it receives CDN service configuration data synchronized by the CDN management platform, and collects statistics on network quality information between each BRAS and the associated SR, such as latency (in ns), jitter (in ns), and packet loss (packet loss rate). At the same time, NCC is also responsible for receiving network quality query requests from the CDN scheduling server and returning network quality information between each BRAS and SR. In addition, it also has the ability to open path optimization to provide CDN services with network paths that meet service levels.

User Management Module (UMM): responsible for maintaining broadband users' account information (such as user, IP address, etc.), as well as the deployment information of user-side broadband access servers and service routers, and synchronizing relevant data of CDN service users to the CDN management platform.

User terminal (UE): initiates a redirection request to the scheduling server in the CDN system, obtains the optimal service node, and then requests media services from the service node.

According to the framework principle of the above scheduling device, a service resource scheduling method is also provided in this scenario embodiment, including the following steps:

The User Management Module (UMM) is used to record the account opening information of broadband users (such as IP addresses), the deployment information of user-side broadband access servers and service routers, aggregate CDN user IP addresses or address segments into IP sets, and synchronize relevant data to the CDN management platform.

The CDN management platform (CDNM) automatically receives data synchronization messages from the user management module (UMM) to update the dispatch server information, service node information, network controller address, BRAS and SR equipment information, user IP address segments, dispatch topology relationship data and other service configurations within the CDN system. At the same time, it is also responsible for synchronizing various service configurations to the dispatch nodes and network controllers. Among them, the dispatch topology relationship data at least includes: the topological relationship between the user IP set and the service node, the topological relationship between the user IP set and the BRAS device, the topological relationship between the service node and the SR device, etc.

The CDN dispatch server (GSLB) receives the service node information and network control information issued by the CDN management platform (CDNM). After receiving the controller address and service configuration data, it collects performance data from the CDN service node regularly to obtain the status and resource data of each service node. At the same time, it regularly accesses the network controller to obtain the network quality data between each BRAS and each SR device. According to the CDN user IP address set and scheduling topology, it calculates the network quality of each user IP set to the service node, incorporates the network quality into the scheduling factor, and decides on an optimal node to return to the user terminal.

The broadband access server (BRAS) is deployed in the user-side metropolitan area network and is responsible for user identity authentication, associating user IP address sets in different areas with different BRASs, and strictly controlling user data entering and leaving the backbone network.

The service router (SR) is deployed in the metropolitan area network on the CDN service node side, receives service configuration data from the CDN management platform, and is responsible for dialing and measuring the network quality between the SR and the BRAS where users under the service node are located.

The network controller cluster (NCC) is deployed in the bearer network. It receives the service configuration data from the CDN management platform and the equipment information of BRAS and SR. It collects the network quality information between each BRAS and SR (such as latency (unit: ns), jitter (unit: ns) and packet loss (packet loss rate) information) and summarizes it.

The Network Controller Cluster (NCC) regularly receives network quality query requests initiated by the CDN scheduling server, summarizes the network quality information between each BRAS and SR, and returns the data to the scheduling server.

The user terminal (UE) initiates a 302 redirection request to the scheduling server in the CDN system, obtains the optimal service node, and then continues to request media services from the service node.

Scenario Example 2

According to the framework structure of the scheduling device of the first scenario embodiment, in this scenario embodiment, the solution is introduced with the above-mentioned scheduling device as the execution body.

FIG10 is a flow chart of a service resource scheduling method according to an embodiment of the present disclosure. As shown in FIG10 , the CDN scheduling process based on IP network quality includes the following steps:

Step S1001, the user management module UMM records the account opening information of broadband users (such as user account, IP address), user-side broadband access server, and deployment information of service routers. The IP addresses of users who have activated CDN services are aggregated into IP sets, and the user IP address set <user IP address segment-IP set>, the topological relationship between the user IP set and the BRAS device <user IP set-BRAS address>, and the topological relationship between the service node and the SR device <service node-SR address> data are synchronized to the CDN management platform.

The CDNM management platform automatically receives the <user IP set-service node>, <user IP set-BRAS address>, <service node-SR address> data synchronized from the UMM and writes them into the local database. Together with the scheduling strategy between the user IP set and the service node, it generates the CDN scheduling topology (as shown in the following figure).

The association relationship between the user IP address segment and the IP set is shown in Table 1. Different IP addresses can be included in the same IP set.

Table 1 The relationship between user IP address segments and IP sets

The scheduling topology relationship between the user IP set and the CDN service node is shown in Table 2. Different IP address sets can be associated with the same CDN service node.

Table 2 Scheduling topology relationship between user IP sets and CDN service nodes

The association relationship between CDN service nodes and SR devices is shown in Table 3. Different CDN service nodes can belong to the same SR device.

Table 3 The relationship between CDN service nodes and SR devices

The association relationship between the CDN user IP set and the BRAS device is shown in Table 4. Different user IP sets may belong to the same BRAS device or to different BRAS devices.

Table 4 Association between CDN user IP sets and BRAS devices

Step S1002, the CDNM management platform associates the above groups of scheduling topology data to obtain the <BRAS address-SR address> association relationship, and synchronizes the relationship data to GSLB, NCC, SR and other devices.

Step S1003: After receiving the configuration data of the CDNM, the SR device periodically performs long-term network quality detection on the BRAS device to obtain a network quality matrix between the SR and the BRAS.

Step S1004: After receiving the service configuration data from the CDN management platform and the equipment information of the BRAS and SR, the NCC periodically initiates data collection to each SR. As shown in the measurement model of Figure 11: the NCC obtains network quality information between each BRAS and SR, such as latency (in ns), jitter (in ns), and packet loss (packet loss rate), and finally summarizes the network quality detection results between each SR and BRAS.

Step S1005: GSLB periodically sends a query request to the network controller NCC to obtain network quality data of all links between the BRAS and the SR device.

(1) Before sending a query request, GSLB first sends an https authentication request to the network controller NCC to obtain a valid accessToken. If the token is not obtained or has expired, it is necessary to obtain a token from the network controller again.

The GSLB authentication request message login-info is as follows, where user-name is the login user name and value is the password information.

The NCC authentication return information login-response is as follows, where expires is the authentication validity period, which is fixed at 1800 (unit: seconds); accessToken is the access token.

(2) After obtaining the legal token, GSLB queries the network controller NCC to obtain the network quality data between the BRAS and the SR device.

query-performance-input is a network quality query request message initiated by GSLB; where srIpAddr is the SR device address, brasIpAddr is the BRAS address, and accessToken is the token obtained through the authentication request. The network quality query request message encoding content is as follows:

query-performance-output is the network quality query response message returned by the NCC; srIpAddr is the SR device address; brasIpAddr is the BRAS address; latency, jitter, and packetLose are the three quality data returned by the network controller: latency (in ns), jitter (in ns), and packet loss rate. The network quality query response message encoding content is as follows Down:

The network quality data between the SR device and the BRAS device collected by GSLB from the network controller is shown in Table 5. The BRAS devices at different user ends can correspond to the SR device at the same service node end.

Table 5 Network quality data between SR equipment and BRAS equipment

Step S1006: GSLB calculates each user's IP address set based on the CDN user IP address set and the scheduling topology. The network quality QOS indicator value to the service node (as shown in the following table). In this topological relationship, when the same CDN service node supports user services on multiple network planes, the network quality of multiple network planes can be mapped to the QOS indicator value of different address sets to the same service node.

The GSLB associated scheduling topology and network quality matrix are shown in Table 6, and the QOS indicator value between each user IP address or address segment and different CDN service nodes is obtained.

Table 6 GSLB associated scheduling topology and network quality matrix

Example: QOS calculation method: QOS = ln[(latency/standard)]*delay weight + ln[(jitter/standard)]*jitter weight + ln[(packetLose/standard)]*packet loss rate weight.

Among them, delay weight + jitter weight + packet loss rate weight = 1.

Network standards: latency 100ms, jitter 40ms, and packet loss 1%. These are standard values obtained through big data analysis and are configurable.

Result: QOS＜0 means the network quality is good, QOS＞0 means the network quality is worse than the standard.

Step S1007, the user terminal UE initiates a 302 redirection request to the GSLB in the CDN system.

Step S1008, GSLB obtains the list of associated CDN service nodes according to the address segment where the user IP is located, incorporates the network quality QOS indicator value into the scheduling decision options, and determines an optimal node with the minimum QOS and the most remaining resources and returns it to the user terminal.

Step S1009: After obtaining the optimal service node information, the user terminal continues to request media services from the service node.

Step S1010: The service node receives a user service request and provides a media service.

Scenario Example 3

FIG12 is a schematic diagram of a method for dynamically optimizing network quality based on a scheduling path according to an embodiment of the present disclosure scenario. As shown in FIG12 , in order to better reflect the purpose of the present disclosure embodiment, a method for dynamically optimizing network quality based on a scheduling path is also proposed on the basis of the first embodiment of the present disclosure, which can be used as an extension of the embodiment shown in FIG10 , and can timely adjust the network quality of the optimal link and reasonably allocate bandwidth resources according to the actual business situation of each user IP set to each node service point. The following steps may be included:

Step S1201, the user management module UMM records the broadband user's account opening information (such as IP address), the user-side broadband access server, and the deployment information of the service router. The user IP addresses that have activated the CDN service are aggregated into an IP set, and the topological relationship data of <user IP address segment-IP set>, <user IP set-BRAS address>, and <service node-SR address> are synchronized to the CDN management platform.

The CDNM management platform automatically receives the <user IP address segment-IP set>, <user IP set-BRAS address>, and <service node-SR address> data synchronized from the UMM and writes them into the local database.

In step S1202, the CDNM management platform combines the user network information automatically received from the UMM with the local scheduling strategy <user IP set-service node> to generate a CDN scheduling topology, obtain the <BRAS address-SR address> association relationship, and synchronize the relationship data to GSLB, NCC, SR and other devices.

Step S1203: After receiving the configuration data of CDNM, the SR device periodically performs long-term network quality detection on the BRAS device to obtain a network quality matrix between the SR and the BRAS.

In step S1204, after the NCC receives the service configuration data from the CDN management platform and the equipment information of the BRAS and SR, it periodically initiates collection to each SR to obtain the network quality information between each BRAS and SR, such as: latency (unit ns), jitter (unit ns) and packet loss (packet loss rate) information, etc., and finally summarizes the network quality detection results between each SR and BRAS.

Step S1205: GSLB periodically sends a query request to the network controller NCC to obtain network quality data of all links between the BRAS and the SR device. (The query interface is the same as step S1006 in the first embodiment)

Step S1206, GSLB calculates the network quality QOS index value from each user IP address segment to the service node according to the CDN user IP address segment and scheduling topology.

Step S1207, the user terminal UE initiates a 302 redirection request to the GSLB in the CDN system.

Step S1208, GSLB obtains the list of associated CDN service nodes according to the address segment where the user IP is located, incorporates the network quality QOS indicator value into the scheduling decision options, and determines the optimal node with the minimum QOS and the most remaining resources and returns it to the user terminal.

Step S1209, GSLB counts the scheduling results within a certain time range. If it is found that the network quality of the optimal node within the scheduling policy range is still poor, it will actively initiate a network optimization request to the controller, carrying the address list of the target SR and the source BRAS.

update-performance-input is a network quality update request message initiated by GSLB; srIpAddr is the SR device address, brasIpAddr is the BRAS address, and accessToken is the token obtained through the authentication request. latency, jitter, and packetLose are the three current quality data: latency (unit ns), jitter (unit ns), and packet loss rate. The network quality update request message encoding content is as follows:

update-performance-output is the network quality update response message returned by NCC; srIpAddr is the SR device address; brasIpAddr is the BRAS address; latency, jitter, and packetLose are the quality data after the network controller adjusts the bandwidth configuration: latency (in ns), jitter (in ns), and packet loss rate. The network quality update response message encoding content is as follows:

Step S1210: After receiving the CDN network optimization request, the network controller NCC sends a network parameter tuning instruction to the SR and BRAS to adjust the network bandwidth configuration.

Step S1211: The network controller re-collects data to obtain the optimized network quality result.

Step S1212: The network controller returns the tuning result to GSLB.

Step S1213, GSLB recalculates the network quality QOS index value, and calculates the optimal node based on the new network quality index when processing subsequent scheduling requests.

Step S1214: the user terminal UE initiates a 302 redirection request to the GSLB in the CDN system.

Step S1215, GSLB obtains the list of associated CDN service nodes according to the address segment where the user IP is located, and decides an optimal node based on the new network quality indicator and returns it to the user terminal.

Step S1216: After obtaining the optimal service node, the user terminal continues to request media services from the service node.

Step S1217: The service node receives the user service request and provides media service.

In summary, the disclosed embodiment provides a method and device for scheduling service resources. First, by opening up the service interface between the CDN subsystem and the bearer network, the CDN scheduling system is integrated with the bearer network, and the scheduling strategy and network information are interconnected, which can enhance the reliability of the CDN architecture. Secondly, by adding the network quality information transmitted by the network controller NCC in the CDN global scheduling mechanism, the user can select the CDN node with the best resources and the best network to provide services, which can optimize the service quality, balance the CDN node load from the two aspects of resources and network, and improve the quality assurance of CDN services. Thirdly, the bearer network opens the path tuning capability to provide the CDN service with a network path that meets the service requirements, such as: by centrally arranging and dynamically adjusting the bandwidth configuration of each path in the region, the congested and faulty links can be optimized to improve the overall bandwidth utilization of the CDN network. In addition, the CDN management system can also realize the participation of network information in CDN load distribution based on the traffic statistics information transmitted by the network controller and the CDN service throughput information, dynamically adjust and predict CDN resources, release or increase the capacity of server resources, and reduce resource waste.

The CDN scheduling system constructed by the method disclosed in the embodiment of the present disclosure integrates the scheduling policy configuration of the CDN system with the network information of the bearer network, and enhances the CDN system's capabilities in node selection, resource balancing, etc. with network-assisted computing, optimizes the global scheduling algorithm, and can take into account the network quality between all user IP sets and their affiliated nodes (it can also include user scheduling in multi-network plane scenarios of the same node), and can balance the CDN node load from both node resources and network environment aspects, thereby improving the service quality and overall bandwidth utilization of the CDN system. The CDN scheduling system and method based on IP network quality disclosed in the embodiment of the present disclosure can also be extended to other business areas in the Internet, such as dynamic expansion and contraction of VCDN virtual nodes, prediction of network quality, etc.

The above description is only a preferred embodiment of the present disclosure, and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims (15)

A method for scheduling service resources, comprising: Acquire a scheduling topology relationship between a user terminal UE and a content scheduling network CDN, and acquire a topology relationship between a broadband access server BRAS and a service router SR according to the scheduling topology relationship; According to the topological relationship between the BRAS and the SR, network quality information of the BRAS and the SR is collected, and a network quality detection result is obtained; Calculating a network quality indicator QOS between the UE and the service node of the CDN network according to the network quality detection result; An optimal service node is selected according to the QOS indicator value, and service resources of the UE are scheduled based on the optimal service node. The method according to claim 1, wherein the obtaining the scheduling topology relationship between the user terminal UE and the content scheduling network CDN comprises: The scheduling topology relationship is obtained according to the scheduling strategy between the service node of the CDN network and the UE, wherein the scheduling topology relationship includes at least one of the following: an association relationship between the IP address of the UE and the IP set of the UE, an association relationship between the IP set of the UE and the service node, an association relationship between the service node and the SR, and an association relationship between the IP set of the UE and the BRAS. The method according to claim 1, wherein, before calculating the network quality indicator QOS between the UE and the service node of the CDN network according to the network quality detection result, the method further comprises: The scheduling server of the CDN network verifies the access right to the network quality detection result, and if the verification is successful, obtains the network quality detection result; if the verification is unsuccessful, re-obtains the access right. The method according to claim 1, wherein the network quality detection result includes at least one of the following: delay detection information; jitter detection information; packet loss rate detection information. The method according to claim 4, wherein the calculating, according to the network quality detection result, a network quality indicator QOS between the UE and the service node of the CDN network comprises: A weighted calculation is performed according to the delay detection information, the jitter detection information, and the packet loss rate detection information to obtain the QOS index value. The method according to claim 1, wherein, before selecting the optimal service node according to the QOS indicator value, the method further comprises: The UE sends a redirection request to the scheduling server of the CDN network. The method according to claim 1, wherein the step of selecting the optimal service node according to the QOS indicator value comprises: According to the QOS indicator value and the remaining service resources of the service node, a decision is made to select the service node with the smallest QOS indicator value and the largest remaining service resources as the optimal service node. The method according to claim 1, wherein after selecting the optimal service node according to the QOS indicator value, the method further comprises: Detect the network quality detection result of the designated link, and when the network quality detection result of the designated link does not reach a preset threshold, control the BRAS and the SR to adjust network parameters to optimize the network quality detection result of the designated link. The method according to claim 1, wherein the scheduling of service resources of the UE based on the optimal service node comprises: The optimal service node receives service request information of the UE; The optimal serving node provides serving resources to the UE. A scheduling device for service resources, comprising: A topology acquisition module, configured to acquire a scheduling topology relationship between a user terminal UE and a content scheduling network CDN, and acquire a topology relationship between a broadband access server BRAS and a service router SR according to the scheduling topology relationship; A quality detection module, configured to collect network quality information of the BRAS and the SR according to the topological relationship between the BRAS and the SR, and obtain a network quality detection result; An indicator calculation module, configured to calculate a network quality indicator QOS between the UE and the service node of the CDN network according to the network quality detection result; The decision-making and scheduling module is configured to select an optimal service node according to the QOS indicator value, and schedule the service resources of the UE based on the optimal service node. The device according to claim 10, further comprising: The verification module is set in the scheduling server of the CDN network and is configured to verify the access rights of the network quality detection result. If the verification is successful, the network quality detection result is obtained and sent to the indicator calculation module; if the verification fails, the access rights are re-acquired. The device according to claim 10, further comprising: The sending module is arranged in the UE and is configured to send a redirection request to the scheduling server of the CDN network. The device according to claim 10, further comprising: A receiving module, configured to receive service request information of the UE; The scheduling module is configured to provide service resources to the UE. A computer-readable storage medium having a computer program stored therein, wherein the computer program implements the method described in any one of claims 1 to 10 when executed by a processor. An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of claims 1 to 10 when executing the computer program.