CN114338536B

CN114338536B - Scheduling method, device, equipment and medium based on block chain

Info

Publication number: CN114338536B
Application number: CN202210251180.5A
Authority: CN
Inventors: 刘晓赫; 郑旗; 郑斌
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2022-03-15
Filing date: 2022-03-15
Publication date: 2022-06-17
Anticipated expiration: 2042-03-15
Also published as: CN114338536A

Abstract

The disclosure provides a scheduling method, device, equipment and medium based on a block chain, relates to the technical field of computers, and particularly relates to a block chain technology. The method is applied to the block chain node and comprises the following steps: processing a flow detection transaction request through a preplanning machine contract to control preplanning machine nodes arranged outside a chain and collect flow data from a network to be scheduled; obtaining flow data fed back by the nodes of the language prediction machine through the contract of the language prediction machine; and processing a network scheduling transaction request through the language predictive machine contract, determining a scheduling scheme according to the traffic data based on a scheduling strategy deployed in a block chain, and controlling the language predictive machine node to execute the scheduling scheme so as to send a scheduling instruction to the network to be scheduled. The scheme realizes the public transparency of the scheduling strategy and improves the good trust relationship between the user and the operator.

Description

Scheduling method, device, equipment and medium based on block chain

Technical Field

The present disclosure relates to the field of computer technology, and more particularly, to a blockchain technique.

Background

Software Defined Wide Area Network (SD-WAN) is a service formed by applying SDN technology to a Wide Area Network scenario, and is used to connect enterprise networks, data centers, internet applications, and cloud services in a Wide geographic range.

Intelligent scheduling is required in the SDN network, specifically, by using path selection, a controller of the SD-WAN may select different types of links and establishment modes according to a service policy and a service quality, and when the performance of a link is degraded or an interruption occurs, traffic may be routed along a backup path without manual intervention.

However, the use of an SD-WAN controller as a centralized traffic collection and scheduling center presents a risk of doing malicious work. For users, the scheduling strategy is not public and transparent, and a good trust relationship cannot be established between the users and operators.

Disclosure of Invention

The disclosure provides a scheduling method, device, equipment and medium based on a block chain, so as to realize the openness and transparency of a scheduling strategy and improve a good trust relationship between a user and an operator.

According to an aspect of the present disclosure, there is provided a scheduling method based on a blockchain, applied to a blockchain node, the method including:

processing a flow detection transaction request through a preplanning machine contract to control preplanning machine nodes arranged outside a chain and collect flow data from a network to be scheduled;

obtaining flow data fed back by the nodes of the language prediction machine through the contract of the language prediction machine;

and processing a network scheduling transaction request through the language predictive machine contract, determining a scheduling scheme according to the traffic data based on a scheduling strategy deployed in a block chain, and controlling the language predictive machine node to execute the scheduling scheme so as to send a scheduling instruction to the network to be scheduled.

According to another aspect of the present disclosure, there is provided a block chain-based scheduling method applied to a predictive engine node, the method including:

acquiring a flow detection transaction request executed by a predictive engine contract deployed on a block chain;

collecting flow data from a network to be scheduled according to the flow detection transaction request, and feeding the flow data back to the prophetic machine contract;

and acquiring a scheduling scheme generated by the prediction machine contract, generating a scheduling instruction according to the scheduling scheme, and sending the scheduling instruction to the network to be scheduled.

According to another aspect of the present disclosure, there is provided a scheduling apparatus based on a blockchain, configured at a blockchain node, the apparatus including:

the detection transaction request processing module is used for processing the flow detection transaction request through a preplan contract so as to control preplan nodes arranged outside the chain and collect flow data from the network to be scheduled;

the traffic data acquisition module is used for acquiring traffic data fed back by the nodes of the language predictive controller through the contract of the language predictive controller;

and the scheduling transaction request processing module is used for processing a network scheduling transaction request through the prompter contract, determining a scheduling scheme according to the traffic data based on a scheduling strategy deployed in a block chain, and controlling the prompter node to execute the scheduling scheme so as to send a scheduling instruction to the network to be scheduled.

According to another aspect of the present disclosure, there is provided a scheduling apparatus based on a block chain, configured at a predictive engine node, the apparatus including:

the detection transaction request acquisition module is used for acquiring a flow detection transaction request executed by a preplan contract deployed on a block chain;

the flow data feedback module is used for acquiring flow data from a network to be scheduled according to the flow detection transaction request and feeding the flow data back to the prompter contract;

and the scheduling scheme acquisition module is used for acquiring the scheduling scheme generated by the prompter contract, generating a scheduling instruction according to the scheduling scheme and sending the scheduling instruction to the network to be scheduled.

According to another aspect of the present disclosure, there is also provided an electronic device including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any one of the methods of blockchain based scheduling provided by embodiments of the present disclosure.

According to another aspect of the present disclosure, there is also provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform any one of the blockchain based scheduling methods provided by the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is also provided a computer program product, including a computer program, which when executed by a processor implements any one of the scheduling methods based on a block chain provided by the embodiments of the present disclosure.

According to the technology disclosed by the invention, the dispatching strategy is realized to be open and transparent, and the good trust relationship between the user and the operator is improved.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

fig. 1 is a schematic diagram of a block chain based scheduling method provided in an embodiment of the present disclosure;

fig. 2 is a schematic diagram of another scheduling method based on a block chain according to an embodiment of the present disclosure;

fig. 3A is a schematic diagram of another scheduling method based on a block chain according to an embodiment of the present disclosure;

fig. 3B is an interaction diagram of another scheduling method based on a blockchain according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a scheduling apparatus based on a block chain according to an embodiment of the present disclosure;

fig. 5 is a schematic structural diagram of a scheduling apparatus based on a block chain according to an embodiment of the present disclosure;

fig. 6 is a block diagram of an electronic device for implementing a block chain based scheduling method according to an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

Fig. 1 is a schematic diagram of a scheduling method based on a blockchain according to an embodiment of the present disclosure, which is applicable to a case where a blockchain network controls traffic scheduling in an out-of-chain network. The method may be performed by a blockchain-based scheduling apparatus, which may be implemented in hardware and/or software, and may be configured in an electronic device, which may be a blockchain node. Referring to fig. 1, the method is applied to a blockchain node, and specifically includes the following steps:

and S110, processing the traffic detection transaction request through a preplan contract to control preplan nodes arranged outside the chain and collect traffic data from the network to be scheduled.

The forecasting contract can be an intelligent contract which is pre-deployed in the blockchain node and used for making flow scheduling decision. The traffic detection transaction request may be a request for detecting traffic of the network to be scheduled and performing traffic data acquisition on the network to be scheduled. The Network to be scheduled may be a Network that needs to perform traffic scheduling and is deployed outside a chain, for example, the Network to be scheduled may be a Software Defined Wide Area Network (SD-WAN). The traffic data may be traffic data of each link node such as a bearer traffic of a VPN (Virtual Private Network) of the Network to be scheduled.

The generation mode of the traffic detection transaction request may be timing generation or initiated by a client of the block chain.

In an optional embodiment, before processing the traffic detection transaction request by the president contract, the method further comprises: timing by a timing trigger started by a forecast contract, and generating a flow detection transaction request when the timing reaches a set time condition; or receive a client-initiated traffic detection transaction request via a prediction engine contract.

Wherein the timing trigger can be pre-deployed in the blockchain. The time condition may be preset by a related technician, for example, the time condition may be a preset specific time, for example, the specific time may be 12:00, 13:20, 14:10, etc. every day; the time condition may also be a preset time interval period, for example, the time interval period may be 10 minutes, that is, the timing trigger generates a traffic detection transaction request every 10 minutes.

For example, a timer trigger may be started by a forecast contract to perform timing, and a traffic detection transaction request may be generated at a time when a set time condition is met; or, a traffic detection transaction request can be initiated by a client of the blockchain, and the traffic detection transaction request initiated by the client is received by the prediction machine contract and processed.

Specifically, a user who has a demand for traffic scheduling, for example, a network manager or a user to be scheduled, may initiate a traffic scheduling transaction request through a client of a block chain; after the block link point acquires the traffic scheduling transaction request, a prediction machine contract can be called to process the traffic scheduling transaction request.

In the scheme of the optional embodiment, the automatic timing triggering of the traffic detection transaction request is realized by a mode that the timing trigger initiates the traffic detection transaction request at regular time; in addition, a traffic detection transaction request can be generated in a reporting mode by a client of the block chain, so that the traffic detection transaction request can be initiated by any user who needs traffic detection or traffic scheduling through the client, and the convenience of the user who needs the traffic detection transaction request is improved.

For example, a traffic detection transaction request initiated by a client at any time or initiated by a timing trigger can be acquired by a block link point, and a prediction contract is invoked to process the traffic detection transaction request. The predictive machine contract can communicate with a predictive machine node arranged outside the chain in an interface calling mode and control the predictive machine node to obtain a flow detection transaction request; the node of the prediction machine acquires flow data from the network to be scheduled according to the acquired flow detection transaction request; specifically, the node of the predictive speaker initiates a traffic detection instruction to the network to be scheduled, and the network to be scheduled sends traffic data to the node of the predictive speaker according to the received traffic detection instruction.

And S120, acquiring flow data fed back by the nodes of the predictive controller through the contract of the predictive controller.

For example, the predictive engine node may feed back the traffic data to the block link point through the client of the block chain, and the block link point calls a predictive engine contract to acquire and process the traffic data.

S130, processing the network scheduling transaction request through a predictive engine contract, determining a scheduling scheme according to the traffic data based on a scheduling strategy deployed in the block chain, and controlling a predictive engine node to execute the scheduling scheme so as to send a scheduling instruction to a network to be scheduled.

The network scheduling transaction request may be initiated by the block link point after acquiring the traffic data, and specifically may be triggered and generated by processing the received traffic data by using a prediction engine contract, and the network scheduling transaction request may be a transaction request for performing traffic scheduling on the network to be scheduled. The scheduling instruction may be an instruction for performing traffic scheduling on the network to be scheduled.

Wherein the scheduling policy may be preset by a related technician. For example, the scheduling policy may be to determine whether traffic of the network to be scheduled is abnormal according to the acquired traffic data, for example, determine whether the network traffic reaches load balancing, and determine whether to perform traffic scheduling on the network to be scheduled according to a determination result. If the traffic of the network to be scheduled is not abnormal and the network traffic reaches load balance, the traffic of the network to be scheduled does not need to be scheduled. If the traffic of the network to be scheduled is abnormal or the network traffic does not reach the load balance, the traffic of the network to be scheduled needs to be scheduled, and a scheduling scheme of traffic scheduling is determined according to the traffic data by a prompter contract.

The scheduling scheme may be determined by the prediction machine from the traffic data. The scheduling scheme may be a coarse-grained scheme, for example, the scheduling scheme may be that traffic of the to-be-scheduled network whose traffic load does not reach balance is reduced to a preset traffic value, so that the to-be-scheduled network which does not reach the traffic load balance can be adaptively scheduled. For example, the scheduling scheme may be an adaptive scheduling instruction for generating the network to be scheduled with the number "XXX 1" and the number "XXX 2", so that the network to be scheduled with the number "XXX 1" and the number "XXX 2" can adaptively adjust the network traffic of the network to be scheduled, so as to achieve load balancing. Wherein, the network to be scheduled with the number "XXX 1" and the number "XXX 2" may be the network to be scheduled with overloaded traffic.

The scheduling scheme may also be a fine-grained scheme, for example, the scheduling scheme may also be that traffic scheduling allocation is performed on at least one VPN network in the network to be scheduled, and specifically, a traffic usage-overloaded VPN network in the network to be scheduled is scheduled to a relatively idle VPN network.

Illustratively, after the block link point acquires the traffic data, a network scheduling transaction request is generated, and the network scheduling transaction request is processed through a prediction machine contract; and the prediction machine contract judges whether the network flow to be scheduled is abnormal or whether the flow reaches load balance or not according to the flow data in the network scheduling transaction request and based on a pre-deployed scheduling strategy, and determines whether to perform network flow scheduling on the network to be scheduled according to a judgment result. If network flow scheduling is needed, the predictive engine contract determines a scheduling scheme according to the flow data, sends the scheduling scheme to the predictive engine node, and the predictive engine node executes the scheduling scheme and sends a scheduling instruction to a network to be scheduled.

The scheme of the embodiment of the disclosure processes the flow detection transaction request through the preplan contract to control the preplan node and collect flow data from the network to be scheduled; and acquiring flow data fed back by the nodes of the predictive terminal, processing the network scheduling transaction request by a contract of the predictive terminal so as to determine a scheduling scheme according to the flow data based on a scheduling strategy deployed in a block chain, and controlling the nodes of the predictive terminal to execute the scheduling scheme so as to send a scheduling instruction to a network to be scheduled. According to the scheme, the scheduling strategy is executed and determined by the prompter contract on the block chain, so that the scheduling strategy is public and transparent, the occurrence of the malicious situation of centralized traffic collection and a scheduling center during traffic scheduling is avoided, the safety in the traffic scheduling process is improved, the fault occurrence and the malicious risk of the single-point controller serving as the scheduling center are reduced, and the good trust relationship between a user and an operator is improved.

Fig. 2 is a schematic diagram of another scheduling method based on a block chain according to an embodiment of the present disclosure, and this embodiment is an alternative proposed on the basis of the foregoing embodiment.

Referring to fig. 2, the scheduling method based on the block chain provided in this embodiment includes:

s210, processing a flow detection transaction request through a prediction machine contract, generating a detection event log, and recording the detection event log in a block; and the detection event log is used for triggering the predictive speaker node to acquire and execute the flow detection transaction request when the predictive speaker node monitors the event log.

The content to be recorded in the detection event log can be preset by a related technician when the prediction machine contract is deployed. For example, the detection event log may be event information generated during execution of a traffic detection transaction request by a prediction engine contract. The event information may be related information of a traffic detection event.

The detection event log may be recorded in a block, wherein the block includes a block header or a block body, i.e., the detection event log may be recorded in the block header or the block body. The block body may record therein detailed data of the block, for example, at least one request data generated or received during execution of the block chain. The block header may record the hash value of the previous block and the hash value of the present block, and at least one tree for recording information. For example, the detection event log may be recorded in a log tree in the block header. The log tree may be a data structure for recording event information in the block. The event information may be information related to a traffic detection event.

For example, the block chain node calls a predictive machine contract to process the traffic detection transaction request, and the predictive machine contract can generate a detection event log corresponding to the processing traffic detection transaction request during the process of executing the traffic detection transaction request, and record the log in the block header or the block body. What is formed in the detection event log may be predefined, that is, information which is included in all detection events generated when the prediction engine contract executes the traffic detection transaction request is set. Correspondingly, the detection event log can be broadcasted in the network by the prediction machine contract, so that the prediction machine node monitors the detection event log, and if the detection event log is monitored, the prediction machine node can acquire and execute the flow detection transaction request.

Compared with the method of sending the flow detection transaction request to the predicting machine node by adopting an interface calling mode, the method of monitoring the detection event log realizes that the predicting machine node can timely obtain the flow detection transaction request, so that the predicting machine contract of the block chain node does not need to carry out interface calling on a specific predicting machine node. The blockchain network includes a plurality of blockchain nodes, and if the predictor nodes are called separately, a large number of call requests may be generated.

And S220, receiving a flow feedback transaction request initiated by the predictive node through the blockchain client.

The traffic feedback transaction request can be a transaction request for feeding back traffic data, which is initiated by the talker node to the block link node.

Illustratively, when the node of the predictive speaker monitors the detection event log, a traffic detection transaction request is obtained, and traffic data is collected from the network to be scheduled according to the traffic detection transaction request; and the predicting machine node starts a flow feedback transaction request to the block chain link point based on the block chain client according to the acquired flow data.

And S230, calling a predictive engine contract to execute the flow feedback transaction request, acquiring flow data fed back by the predictive engine node from the flow feedback transaction request, and performing uplink storage.

Illustratively, after the block link point obtains the traffic feedback transaction request, a predictive engine contract is called to execute the traffic feedback transaction request, and traffic data fed back by the predictive engine node is obtained from the traffic feedback transaction request to perform uplink storage, and meanwhile, a network scheduling transaction request is generated. The network scheduling transaction request may be a transaction request for performing traffic scheduling on a network to be scheduled.

It should be noted that, in order to improve the reliability of the traffic data acquired by the block chain node from the talker node and reduce the malicious risk of the talker node, the traffic data and the signature of the talker node may be fed back to the block link node by the talker node, so that the block chain node performs signature verification on the talker node.

In an optional embodiment, the process of invoking the president contract to execute the traffic feedback transaction request further includes: and verifying the signature of the nodes of the prediction machine.

The signature of the talker node may be a result of the talker node signing the acquired traffic data.

Illustratively, the prediction machine node feeds back the flow data and the signature of the prediction machine node to the block chain link point through the block chain client, and the block chain link point calls a prediction machine contract to verify the signature of the prediction machine node. If the verification is successful, the obtained flow data is valid; if the verification fails, the acquired traffic data may be considered invalid.

In the optional embodiment, the signature of the nodes of the predictive speech machine is verified, so that the reliability of the flow data acquired by the link points of the block is ensured, and the malicious risk of the nodes of the predictive speech machine is reduced, thereby improving the accuracy of the scheduling scheme determined by the follow-up contract of the predictive speech machine based on the scheduling strategy according to the flow data.

S240, processing the network scheduling transaction request through a prediction machine contract to generate a scheduling event log which is recorded in a block; and the scheduling event log is used for triggering the predictive speaker node to acquire the scheduling scheme and execute when the predictive speaker node monitors the scheduling event log.

The content to be recorded in the scheduling event log may be preset by a related technician when deploying the forecast contract. For example, the scheduled event log may be event information generated during execution of a network scheduled transaction request by a prediction engine contract. The event information may be related information of a network scheduling event, and the scheduling event log may be recorded in a block header or a block body.

Illustratively, the block chain node calls a prompter contract to process the network scheduling transaction request; and the predicting machine contract determines a scheduling scheme based on a pre-deployed scheduling strategy according to the flow data in the network scheduling transaction request, generates a scheduling event log corresponding to the network scheduling transaction request at the same time, and records the log in a block header or a block body. The content formed in the scheduling event log may be predefined, that is, it is set which information is included in all scheduling events generated when the scheduler contract executes the network scheduling transaction request. Correspondingly, the scheduling event log can be broadcasted in the network by the prediction machine contract, so that the prediction machine node monitors the scheduling event log, and if the scheduling event log is monitored, the prediction machine node can acquire the scheduling scheme and execute the scheduling scheme so as to send a scheduling instruction to the network to be scheduled.

By adopting the method of monitoring the scheduling event log, the nodes of the prediction machine can timely acquire the scheduling scheme, and the scheduling efficiency is improved.

And S250, acquiring a scheduling result fed back by the nodes of the prediction machine through the prediction machine contract.

Illustratively, when a predictive node monitors a scheduling event log, a scheduling scheme is obtained, and a scheduling instruction is sent to a network to be scheduled according to the scheduling scheme; and the network to be scheduled carries out flow scheduling according to the scheduling instruction, and sends a scheduling result to the propheter node, and the propheter node feeds the scheduling result back to the block chain network.

The scheduling result may include a successful scheduling or a failed scheduling, that is, the scheduling result needs to be sent to the block link node no matter whether the traffic scheduling of the network to be scheduled is successful or not.

In an optional embodiment, obtaining the scheduling result fed back by the predictive engine node through the predictive engine contract comprises: receiving a scheduling result transaction request initiated by a prediction machine node through a block chain client; and calling a predictive engine contract to execute the scheduling result transaction request, acquiring the scheduling result fed back by the predictive engine node from the scheduling result transaction request, and performing uplink storage.

The scheduling result transaction request may be a transaction request initiated by the talker node to the blockchain node to feed back a scheduling result of the network to be scheduled.

Illustratively, when the node of the prediction machine monitors the scheduling event log, a scheduling scheme is obtained, and a scheduling instruction is sent to the network to be scheduled according to the scheduling scheme, so that the network to be scheduled schedules the network traffic according to the scheduling instruction. And the to-be-scheduled network sends the scheduling result to the predictive node, and the predictive node starts a scheduling result transaction request to the block chain link point based on the block chain client according to the obtained scheduling result. The block chain node acquires a scheduling result transaction request and calls a president contract to execute the scheduling result transaction request; and the predicting machine contract acquires the scheduling result fed back by the predicting machine node from the scheduling result transaction request and stores the uplink.

Optionally, in order to improve the reliability of the scheduling result obtained by the block chain node from the prolog machine node and reduce the malicious risk of the prolog machine node, the prolog machine node may feed back both the scheduling result and the signature of the prolog machine node to the block chain link point, so that the block chain node verifies the signature of the prolog machine node.

In the optional embodiment, the scheduling result transaction request initiated by the block chain client is received, the scheduling result transaction request is executed by calling the prolog contract, the scheduling result fed back by the prolog node is obtained from the scheduling result transaction request, and uplink storage is performed.

According to the scheme of the embodiment of the invention, the detection event log and the scheduling event log are generated by the preloader node, and the event log is broadcasted, so that the preloader node monitors the event log, the flow detection transaction request and the scheduling scheme can be timely acquired, and the acquisition efficiency is improved. Meanwhile, the situation of network congestion caused by a large amount of data transmission and data requests generated by interface calling of a large number of block link points is avoided. The mode of uplink storage is carried out on the flow data received by the president contract, so that the flow data can be persistently stored, and the flow data can be directly checked and acquired when the flow data is required subsequently. The scheduling result fed back by the nodes of the prediction machine is obtained through the contract of the prediction machine, so that the scheduling result generated by executing the scheduling instruction in the network to be scheduled is obtained in time, and the contract of the prediction machine is convenient to store the scheduling result in time.

Fig. 3A is a schematic diagram of a scheduling method based on a blockchain according to an embodiment of the present disclosure, which is applicable to a case where a blockchain network controls the scheduling of the out-of-link network traffic. The method may be performed by a block chain based scheduling apparatus, which may be implemented in hardware and/or software, and may be configured in an electronic device, which may be a predictive engine node. Referring to fig. 3A, the method is applied to a predictive engine node, and specifically includes the following steps:

s310, acquiring a flow detection transaction request executed by a predictive engine contract deployed on the blockchain.

The traffic detection transaction request may be a request for detecting traffic of a network to be scheduled and acquiring traffic data of the network to be scheduled. The traffic detection transaction request can be generated by a timing trigger or initiated by a client of the block chain.

For example, a traffic detection transaction request initiated by a client at any time or initiated by a timing trigger can be acquired by a block link point, and a prediction contract is invoked to process the traffic detection transaction request. The predictive engine node can communicate with a predictive engine contract arranged on the chain in an interface calling mode, and acquire a flow detection transaction request sent by the predictive engine contract arranged on the block chain.

In an alternative embodiment, obtaining a traffic detection transaction request executed by a predictive engine contract deployed on a blockchain comprises: if the detection event log is generated in the block chain, the flow detection transaction request is read from the block.

The content to be recorded in the detection event log can be preset by a related technician when the prediction machine contract is deployed. For example, the detection event log may be event information generated during execution of a traffic detection transaction request by a president contract. The event information may be related information of a traffic detection event, and the detection event log may be recorded in a block header or a block body.

For example, the detection event log may be broadcast in the network by a predictive machine contract, the predictive machine node listens to the detection event log, and if the predictive machine node listens to the detection event log, the traffic detection transaction request may be acquired and executed by the predictive machine node.

In the optional embodiment, the traffic detection transaction request is read from the block in a manner that the predictive controller node monitors the detection event log generated in the block chain, so that the predictive controller node can timely obtain the traffic detection transaction request, the predictive controller contract of the block chain node does not need to perform interface calling on a specific predictive controller node, and the request obtaining efficiency is improved.

And S320, collecting flow data from the network to be scheduled according to the flow detection transaction request, and feeding the flow data back to the prediction machine contract.

The Network to be scheduled may be a Software Defined Wide Area Network (SD-WAN). The traffic data may be bearer traffic of a VPN (Virtual Private Network) of the Network to be scheduled.

For example, a traffic acquisition instruction may be sent to the network to be scheduled by the node of the prediction machine according to the acquired traffic detection transaction request, so that the network to be scheduled acquires traffic data according to the traffic acquisition instruction; and the predicting machine node acquires the flow data and feeds the flow data back to the predicting machine contract.

In an alternative embodiment, feeding back traffic data to the predictive engine contract comprises: and initiating a flow feedback transaction request carrying flow data through the block chain client to request to call a prediction machine contract to execute the flow feedback transaction request.

The traffic feedback transaction request may be a transaction request initiated by the talker node to feed back traffic data to the block link node.

Illustratively, when a node of a prediction machine monitors a detection event log, a traffic detection transaction request is acquired, and traffic data is collected from a network to be scheduled according to the traffic detection transaction request; and the predictive controller node starts a flow feedback transaction request to the block chain link point based on the block chain client according to the acquired flow data so as to request to call a predictive controller contract to execute the flow feedback transaction request.

In the optional embodiment, the block chain client initiates a flow feedback transaction request carrying flow data to request to call the predictive engine contract to execute the flow feedback transaction request, and the flow data is sent in the transaction request mode based on the block chain client, so that the security of the predictive engine contract in the process of acquiring the flow feedback transaction request is improved.

S330, obtaining a scheduling scheme generated by a prediction machine contract, generating a scheduling instruction according to the scheduling scheme, and sending the scheduling instruction to a network to be scheduled.

Wherein the scheduling scheme may be determined by the prediction machine based on the traffic data. The scheduling scheme may be a coarse-grained scheme, for example, the scheduling scheme may be that traffic of the to-be-scheduled network whose traffic load does not reach balance is reduced to a preset traffic value, so that the to-be-scheduled network which does not reach the traffic load balance can be adaptively scheduled. The scheduling scheme may also be a fine-grained scheme, for example, the scheduling scheme may also be to perform traffic scheduling allocation on at least one VPN network in the network to be scheduled, and specifically may be to schedule a VPN network whose traffic usage is overloaded to a VPN network that is relatively idle.

For example, a scheduling scheme generated by a predictive engine contract may be obtained by a predictive engine node, and a scheduling instruction may be generated according to the scheduling scheme; and the predictive machine node sends the scheduling instruction to the network to be scheduled so that the network to be scheduled can generate a scheduling result according to the scheduling instruction.

In an alternative embodiment, obtaining a scheduling scheme generated by a president contract comprises: if the block chain is monitored to generate the scheduling event log, the scheduling scheme is read from the block.

Wherein, the content to be recorded in the scheduling event log can be preset by related technicians when the prediction machine contract is deployed. For example, the scheduled event log may be event information generated during execution of a network scheduled transaction request by a prediction engine contract. The event information may be related information of a network scheduling event, and the scheduling event log may be recorded in a block header or a block body.

For example, the scheduled event log may be broadcast by a predictive engine contract in the network, such that the predictive engine node listens to the scheduled event log. When the predictive machine node monitors the scheduling event log, the predictive machine node reads the scheduling scheme from the block and executes the scheduling scheme so as to send a scheduling instruction to the network to be scheduled.

In the optional embodiment, the scheduling scheme is read from the block in a manner that the predictive machine node monitors the scheduling event log generated in the block chain, so that the predictive machine node can timely acquire the scheduling scheme, the predictive machine contract of the block chain node does not need to perform interface call on a specific predictive machine node, and the acquisition efficiency of the scheduling scheme is improved.

In an optional embodiment, after generating the scheduling instruction according to the scheduling scheme and sending the scheduling instruction to the network to be scheduled, the method further includes: and acquiring a scheduling result from the network to be scheduled, and initiating a scheduling result transaction request carrying the scheduling result through the block chain client.

Illustratively, when the node of the prediction machine monitors the scheduling event log, a scheduling scheme is obtained, and a scheduling instruction is sent to the network to be scheduled according to the scheduling scheme, so that the network to be scheduled schedules the network traffic according to the scheduling instruction. And the to-be-scheduled network sends the scheduling result to the predictive node, and the predictive node starts a scheduling result transaction request to the block chain link point based on the block chain client according to the obtained scheduling result.

In the optional embodiment, the scheduling result transaction request carrying the scheduling result is initiated by the block chain client, and the scheduling result is sent in the transaction request mode based on the block chain client, so that the security of the prediction machine contract in the process of obtaining the scheduling result is improved.

In a specific embodiment, refer to an interactive schematic diagram of a block chain based scheduling method shown in fig. 3B. A timing trigger starts a flow detection transaction request to a block chain node at fixed time; and after acquiring the traffic detection transaction request, the block link point calls a preplanning machine contract to process the traffic detection transaction request, generates a detection event log, and broadcasts the detection event log in a network. And monitoring a detection event log by the nodes of the prediction machine, acquiring a flow detection transaction request when the detection event log is monitored, and sending a flow detection instruction to the VPE-CPE network. And after receiving the flow detection instruction, the VPE-CPE network acquires flow data and sends the flow data to the predictive controller node. And feeding back the acquired flow data to the block link point by the prophetic machine node. And the block link point stores the uplink of the flow data, judges whether the scheduling is needed or not based on a preset scheduling strategy, and tries the scheduling to generate a scheduling event log if the scheduling is needed. And the talker node monitors the scheduling event log, acquires a scheduling scheme when monitoring the scheduling event log, and sends a scheduling instruction to the VPE-CPE network based on the scheduling scheme. The VPE-CPE network generates a scheduling result according to the received scheduling instruction, feeds the scheduling result back to the block chain link point through the prediction machine node, and carries out uplink storage on the scheduling result by the block chain link point.

According to the scheme of the embodiment of the disclosure, a node of the prediction machine acquires a flow detection transaction request, acquires flow data from a network to be scheduled according to the flow detection transaction request, and feeds the flow data back to a contract of the prediction machine; and acquiring a scheduling scheme generated by a prediction machine contract, generating a scheduling instruction according to the scheduling scheme, and sending the scheduling instruction to a network to be scheduled. According to the scheme, the scheduling strategy is executed and the scheduling scheme is determined by the president contract on the block chain, so that the scheduling strategy is public and transparent, the occurrence of the malicious situation of the centralized traffic collection and the scheduling center during traffic scheduling is avoided, the safety in the traffic scheduling process is improved, the fault occurrence and the malicious risk of the single-point controller serving as the scheduling center are reduced, and the good trust relationship between a user and an operator is improved.

Fig. 4 is a schematic diagram of a scheduling apparatus based on a blockchain according to an embodiment of the present disclosure, which is applicable to an application scenario in which a blockchain network controls traffic scheduling. The electronic device may be a block chain node, and referring to fig. 4, the scheduling apparatus 400 based on a block chain specifically includes the following:

a detection transaction request processing module 401, configured to process a traffic detection transaction request through a talker about contract, so as to control a talker about node arranged outside a chain, and collect traffic data from a network to be scheduled;

a traffic data obtaining module 402, configured to obtain, through the foresight machine contract, traffic data fed back by the foresight machine node;

a scheduling transaction request processing module 403, configured to process a network scheduling transaction request according to the talker per contract, determine a scheduling scheme according to the traffic data based on a scheduling policy deployed in a blockchain, and control the talker node to execute the scheduling scheme, so as to send a scheduling instruction to the network to be scheduled.

The scheme of the embodiment of the disclosure processes the flow detection transaction request through the preplan contract to control the preplan node and collect flow data from the network to be scheduled; obtaining flow data fed back by the nodes of the predictive terminal, processing a network scheduling transaction request by a contract of the predictive terminal, determining a scheduling scheme according to the flow data based on a scheduling strategy deployed in a block chain, and controlling the nodes of the predictive terminal to execute the scheduling scheme so as to send a scheduling instruction to a network to be scheduled. According to the scheme, the scheduling strategy is executed and determined by the prompter contract on the block chain, so that the scheduling strategy is public and transparent, the occurrence of the malicious situation of centralized traffic collection and a scheduling center during traffic scheduling is avoided, the safety in the traffic scheduling process is improved, the fault occurrence and the malicious risk of the single-point controller serving as the scheduling center are reduced, and the good trust relationship between a user and an operator is improved.

In an optional implementation manner, the module 401 for processing a detection transaction request includes:

a detection event log generating unit, configured to process the traffic detection transaction request through the prompter contract, generate a detection event log, and record the detection event log in a block; the detection event log is used for triggering the predictive controller node to acquire the flow detection transaction request and execute the flow detection transaction request when the detection event log is monitored by the predictive controller node;

correspondingly, the scheduling transaction request processing module 403 includes:

a scheduling event log generating unit, configured to process the network scheduling transaction request through the prompter contract, generate a scheduling event log, and record the scheduling event log in a block; and the scheduling event log is used for triggering the predictive controller node to acquire the scheduling scheme and execute the scheduling scheme when the scheduling event log is monitored by the predictive controller node.

In an alternative embodiment, the apparatus 400 further comprises:

and the event log broadcasting module is used for broadcasting the detected event log or the scheduling event log.

In an alternative embodiment, the apparatus 400 further comprises:

the first flow detection request generation module is used for timing by a timing trigger started by a preplanning machine contract before the flow detection transaction request is processed by the preplanning machine contract, and generating a flow detection transaction request when the timing reaches a set time condition; or

And the second traffic detection request generation module is used for receiving a traffic detection transaction request initiated by the client through the foresight machine contract before the traffic detection transaction request is processed through the foresight machine contract.

In an optional implementation manner, the traffic data obtaining module 402 includes:

the flow feedback request receiving unit is used for receiving a flow feedback transaction request initiated by the talker node through the block chain client;

and the flow feedback request calling unit is used for calling the predictive engine contract to execute the flow feedback transaction request, acquiring flow data fed back by the predictive engine node from the flow feedback transaction request, and performing uplink storage.

In an optional implementation manner, the traffic data obtaining module 402 further includes:

and the signature verification unit is used for verifying the signature of the nodes of the language predictive machine in the process of calling the contract of the language predictive machine to execute the flow feedback transaction request.

In an alternative embodiment, the apparatus 400 further comprises:

and the scheduling result acquisition module is used for acquiring the scheduling result fed back by the predictive controller node through the predictive controller contract after controlling the predictive controller node to execute the scheduling scheme so as to send a scheduling instruction to the network to be scheduled.

In an optional implementation manner, the scheduling result obtaining module includes:

a scheduling result transaction request receiving unit, configured to receive a scheduling result transaction request initiated by the predictive speaker node through the blockchain client;

and the scheduling result transaction request execution unit is used for calling the predicting machine contract to execute the scheduling result transaction request, acquiring a scheduling result fed back by the predicting machine node from the scheduling result transaction request, and performing uplink storage.

In an optional implementation manner, the network to be scheduled is a software-defined wide area network, and the traffic data is bearer traffic of a VPN.

The scheduling apparatus based on the block chain according to the technical solution of the embodiment of the present disclosure may execute the scheduling method based on the block chain according to any embodiment of the present disclosure, and has functional modules and beneficial effects corresponding to the execution of the scheduling method based on the block chain.

Fig. 5 is a schematic diagram of a scheduling apparatus based on a blockchain according to an embodiment of the present disclosure, which is applicable to an application scenario in which a blockchain network controls traffic scheduling. The electronic device may be a predictive engine node, and referring to fig. 5, the block chain based scheduling apparatus 500 specifically includes the following:

a detection transaction request obtaining module 501, configured to obtain a traffic detection transaction request executed by a preplan contract deployed on a blockchain;

a traffic data feedback module 502, configured to collect traffic data from a network to be scheduled according to the traffic detection transaction request, and feed back the traffic data to the prompter contract;

and a scheduling scheme obtaining module 503, configured to obtain a scheduling scheme generated by the prompter contract, generate a scheduling instruction according to the scheduling scheme, and send the scheduling instruction to the network to be scheduled.

According to the scheme of the embodiment of the disclosure, a node of the prediction machine acquires a flow detection transaction request, acquires flow data from a network to be scheduled according to the flow detection transaction request, and feeds the flow data back to a contract of the prediction machine; and acquiring a scheduling scheme generated by a prediction machine contract, generating a scheduling instruction according to the scheduling scheme, and sending the scheduling instruction to a network to be scheduled. According to the scheme, the scheduling strategy is executed and determined by the prompter contract on the block chain, so that the scheduling strategy is public and transparent, the occurrence of the malicious situation of centralized traffic collection and a scheduling center during traffic scheduling is avoided, the safety in the traffic scheduling process is improved, the fault occurrence and the malicious risk of the single-point controller serving as the scheduling center are reduced, and the good trust relationship between a user and an operator is improved.

In an optional implementation manner, the module for acquiring a detection transaction request 501 includes:

the detection transaction request reading unit is used for reading the flow detection transaction request from the block if a detection event log is monitored to be generated in the block chain;

correspondingly, the scheduling scheme obtaining module 503 includes:

and the scheduling scheme reading unit is used for reading the scheduling scheme from the block if the generation of the scheduling event log in the block chain is monitored.

In an optional embodiment, the traffic data feedback module 502 includes:

and the feedback transaction request initiating unit is used for initiating a flow feedback transaction request carrying the flow data through a block chain client so as to request to call the prompter contract to execute the flow feedback transaction request.

In an optional embodiment, the apparatus 500 further comprises:

and the scheduling result transaction request initiating module is used for acquiring a scheduling result from the network to be scheduled after generating a scheduling instruction according to the scheduling scheme and sending the scheduling instruction to the network to be scheduled, and initiating a scheduling result transaction request carrying the scheduling result through the block chain client.

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and the like of the related flow detection transaction request, flow data, network scheduling transaction request, scheduling instruction and the like all accord with the regulations of related laws and regulations, and do not violate the customs of public order.

The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.

FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 6, the apparatus 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the device 600 can also be stored. The calculation unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

A number of components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, or the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 601 performs the various methods and processes described above, such as a block chain based scheduling method. For example, in some embodiments, the blockchain-based scheduling method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the above described blockchain based scheduling method may be performed. Alternatively, in other embodiments, the calculation unit 601 may be configured by any other suitable means (e.g. by means of firmware) to perform the blockchain based scheduling method.

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Network (WAN) blockchain networks, and the internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome. The server may also be a server of a distributed system, or a server incorporating a blockchain.

Artificial intelligence is the subject of research that makes computers simulate some human mental processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), both at the hardware level and at the software level. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing, and the like; the artificial intelligence software technology mainly comprises a computer vision technology, a voice recognition technology, a natural language processing technology, a machine learning/deep learning technology, a big data processing technology, a knowledge map technology and the like.

Cloud computing (cloud computing) refers to accessing an elastically extensible shared physical or virtual resource pool through a network, where resources may include servers, operating systems, networks, software, applications, storage devices, and the like, and may be a technical system that deploys and manages resources in a self-service manner as needed. Through the cloud computing technology, high-efficiency and strong data processing capacity can be provided for technical application and model training of artificial intelligence, block chains and the like.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure may be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions provided by this disclosure can be achieved, and are not limited herein.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A scheduling method based on a block chain is applied to a block chain node, and the method comprises the following steps:

obtaining flow data fed back by the nodes of the language predicting machine through the contract of the language predicting machine, and initiating a network scheduling transaction request according to the flow data;

and processing the network scheduling transaction request through the language predictive machine contract, determining a scheduling scheme according to the traffic data based on a scheduling strategy deployed in a block chain, and controlling the language predictive machine node to execute the scheduling scheme so as to send a scheduling instruction to the network to be scheduled.

2. The method of claim 1, wherein processing the traffic detection transaction request via a predictive engine contract to control a predictive engine node disposed outside the chain, collecting traffic data from the network to be scheduled comprises:

processing the flow detection transaction request through the presupposition machine contract to generate a detection event log which is recorded in a block; the detection event log is used for triggering the predictive controller node to acquire the flow detection transaction request and execute the flow detection transaction request when the detection event log is monitored by the predictive controller node;

correspondingly, processing a network scheduling transaction request through the prolog contract to determine a scheduling scheme according to the traffic data based on a scheduling policy deployed in a blockchain, and controlling the prolog node to execute the scheduling scheme includes:

processing a network scheduling transaction request through the president contract to generate a scheduling event log, and recording the scheduling event log in a block; and the scheduling event log is used for triggering the predictive controller node to acquire the scheduling scheme and execute the scheduling scheme when the scheduling event log is monitored by the predictive controller node.

3. The method of claim 2, further comprising:

broadcasting the detection event log or the scheduling event log.

4. The method of claim 1, prior to processing the traffic detection transaction request by the presupposition machine contract, further comprising:

timing by a timing trigger started by the prompter contract, and generating a flow detection transaction request when the timing reaches a set time condition; or

And receiving a flow detection transaction request initiated by a client through the forecast contract.

5. The method of claim 1, wherein obtaining traffic data fed back by the prophetic machine node through the prophetic machine contract comprises:

receiving a flow feedback transaction request initiated by a prediction machine node through a block chain client;

and calling the foresight machine contract to execute the flow feedback transaction request, acquiring flow data fed back by the foresight machine node from the flow feedback transaction request, and performing uplink storage.

6. The method of claim 5, invoking the presupposition machine contract to execute the traffic feedback transaction request, further comprising:

and verifying the signature of the preloader node.

7. The method of claim 1, after controlling the talker node to execute the scheduling scheme to send a scheduling instruction to the network to be scheduled, further comprising:

and obtaining a scheduling result fed back by the nodes of the prediction machine through the prediction machine contract.

8. The method of claim 7, wherein obtaining scheduling results of the predictive engine node feedback via the predictive engine contract comprises:

receiving a scheduling result transaction request initiated by a prediction machine node through a block chain client;

and calling the president contract to execute the scheduling result transaction request, acquiring a scheduling result fed back by the president node from the scheduling result transaction request, and performing uplink storage.

9. The method of claim 1, wherein the network to be scheduled is a software defined wide area network (WW AN) and the traffic data is bearer traffic of a VPN.

10. A scheduling method based on a block chain is applied to a predictive engine node, and the method comprises the following steps:

collecting flow data from a network to be scheduled according to the flow detection transaction request, and feeding the flow data back to the language predictive machine contract, so that the language predictive machine contract can determine a scheduling scheme according to the flow data based on a scheduling strategy deployed in a block chain;

11. The method of claim 10, wherein obtaining traffic detection transaction requests executed by a predictive engine contract deployed on a blockchain comprises:

if a detection event log is generated in a block chain, reading the flow detection transaction request from the block;

correspondingly, the obtaining of the scheduling scheme generated by the president contract comprises:

if the scheduling event log is generated in the block chain, the scheduling scheme is read from the block.

12. The method of claim 10, wherein feeding back the traffic data to the prognostics contract comprises:

and initiating a flow feedback transaction request carrying the flow data through a block chain client to request to call the presupposition machine contract to execute the flow feedback transaction request.

13. The method of claim 10, generating scheduling instructions according to the scheduling scheme, and after sending the scheduling instructions to the network to be scheduled, further comprising:

and acquiring a scheduling result from the network to be scheduled, and initiating a scheduling result transaction request carrying the scheduling result through the block chain client.

14. An apparatus for block chain based scheduling, configured at a block chain node, the apparatus comprising:

the detection transaction request processing module is used for processing the flow detection transaction request through a preplanning machine contract so as to control preplanning machine nodes arranged outside the chain and collect flow data from the network to be scheduled;

the traffic data acquisition module is used for acquiring traffic data fed back by the nodes of the language predictive controller through the contract of the language predictive controller and initiating a network scheduling transaction request according to the traffic data;

and the scheduling transaction request processing module is used for processing the network scheduling transaction request through the prompter contract, determining a scheduling scheme according to the flow data based on a scheduling strategy deployed in a block chain, and controlling the prompter node to execute the scheduling scheme so as to send a scheduling instruction to the network to be scheduled.

15. A blockchain-based scheduling apparatus configured at a talker node, the apparatus comprising:

the flow data feedback module is used for acquiring flow data from a network to be scheduled according to the flow detection transaction request and feeding the flow data back to the prediction machine contract so that the prediction machine contract can determine a scheduling scheme according to the flow data based on a scheduling strategy deployed in a block chain;

16. An electronic device, comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the blockchain based scheduling method of any one of claims 1-9 or 10-13.

17. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the blockchain based scheduling method of any one of claims 1-9 or 10-13.