CN113055497B - Method, device and system for uplink of data outside block chain network - Google Patents
Method, device and system for uplink of data outside block chain network Download PDFInfo
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Abstract
The disclosure provides an off-link data uplink method for a block chain network, and belongs to the technical field of block chains. The method is applied to a prediction machine network, wherein the prediction machine network comprises M prediction machine nodes and comprises the following steps: receiving a data uplink request initiated by a predictive engine contract in response to invocation of the user contract; the president contract is deployed in the blockchain network, and the user contract is a data query request initiated by an intelligent contract in the blockchain network; processing downlink data acquired by the M prophetic machine nodes respectively responding to the data uplink request based on a share authorization certification mechanism to obtain final data; and feeding back the final data to the presbyope contract to feed back the final data to the user contract through the presbyope contract. The present disclosure also provides an off-link data uplink apparatus and system for a blockchain network, a talker node, and a computer-readable storage medium.
Description
Technical Field
The present disclosure relates to the field of blockchain technologies, and more particularly, to an off-link data uplink method, apparatus, and system for a blockchain network, and a talker node and a computer-readable storage medium.
Background
The blockchain is a deterministic and closed system, and an intelligent contract running on the blockchain cannot actively acquire real world data outside the chain and can only execute tasks in a closed and isolated environment. The predictive engine network may input the out-of-chain real data into the blockchain. It is important to ensure that the data transmitted from the predictive network to the blockchain network is truly valid.
Disclosure of Invention
In view of the above, the embodiments of the present disclosure provide an off-link data uplink method, an apparatus, and a system for a block chain network, a talker node, and a computer readable storage medium, which utilize a decentralized talker based on a DPoS common identification mechanism to perform data uplink, so as to ensure the authenticity and validity of off-link data to a certain extent.
In an aspect of the embodiments of the present disclosure, an off-link data uplink method for a blockchain network is provided, which is applied to a predictive machine network including M predictive machine nodes, where M is an integer greater than or equal to 2. The method comprises the following steps: receiving a data uplink request initiated by a predictive engine contract in response to invocation of the user contract; the forecast contract is deployed in the blockchain network, and the user contract is a data query request initiated by an intelligent contract in the blockchain network; processing downlink data acquired by the M prophetic machine nodes respectively responding to the data uplink request based on a share authorization certification mechanism to obtain final data; and feeding back the final data to the presbyope contract to feed back the final data to the user contract through the presbyope contract.
According to an embodiment of the present disclosure, the processing, by the certificate-based-authorization-certification mechanism, downlink data obtained by each of the M number of talker nodes in response to the data uplink request to obtain final data includes: the stakeholder nodes in the predictive machine network select any number of witness nodes from the predictive machine network; selecting N winning nodes from the predictive engine network by the witness nodes with any number in two rounds, wherein N is an integer larger than 1 and smaller than M; and obtaining the final data based on the downlink data acquired by the N winning nodes.
According to an embodiment of the disclosure, said selecting, by the any number of witness nodes, N winning nodes in two rounds of voting from the speaker network comprises: sorting M nodes of the prediction machine according to the performance from good to bad in a first round of screening based on a first parameter, and screening Q candidate nodes which are sorted at the top from the M nodes, wherein Q is an integer which is more than 1 and less than M; and sorting the Q candidate nodes from good to bad according to the performance in the second round of screening based on a second parameter, and screening N winner nodes which are sorted in the top way, wherein Q/2 is more than N and less than Q. Wherein the first parameter and the second parameter are different.
According to an embodiment of the present disclosure, the first parameter comprises a node weight; and the second parameter comprises a node status parameter.
According to an embodiment of the present disclosure, Q is 9 and N is 5. The obtaining the final data based on the downlink data obtained by the N winning nodes includes: obtaining the final data based on a weighted average of the downlink data of the 5 winning nodes.
According to an embodiment of the present disclosure, the processing, by the certificate-based-authorization-certification mechanism, downlink data obtained by each of the M number of talker nodes in response to the data uplink request to obtain final data includes: and each predicting machine node acquires data from a corresponding external data source, and adapts and unifies the acquired data to obtain the downlink data.
In another aspect of the embodiments of the present disclosure, an off-link data uplink apparatus for a block chain network is provided in a predictive speech machine network. The predictive speech machine network comprises M predictive speech machine nodes, wherein M is an integer greater than or equal to 2. The device comprises a receiving module, a DPoS processing module and a feedback module. The receiving module is used for receiving a data uplink request initiated by a prediction machine contract responding to the calling of the user contract; the president contract is deployed in the blockchain network, and the user contract is a data query request initiated by an intelligent contract in the blockchain network. The DPoS processing module is configured to process, based on a share authorization certification mechanism, downlink data acquired by the M talker nodes in response to the data uplink request, respectively, so as to obtain final data. The feedback module is used for feeding back the final data to the language predictive contract so as to feed back the final data to the user contract through the language predictive contract.
In another aspect of the disclosed embodiments, an off-link data uplink system for a blockchain network is provided, which includes an on-link system and an off-link system. The system on the chain is arranged in the block chain network. User contracts and president machine contracts are deployed in the on-chain system. The user contract is a data query request initiated by an intelligent contract in the block chain network and used for calling the president contract. The predicting machine contract is used for responding to the calling of the user contract to initiate a data uplink request and feeding back the acquired final data to the user contract. The system includes a predictive engine network. The predictive speaker network comprises M predictive speaker nodes, wherein M is an integer greater than or equal to 2. The predictive machine network is configured to: receiving the data uplink request initiated by the predictive engine contract; processing downlink data acquired by the M prophetic machine nodes respectively responding to the data uplink request based on a share authorization certification mechanism to obtain final data; and feeding back the final data to the presbyope contract to feed back the final data to the user contract through the presbyope contract.
In another aspect of the disclosed embodiments, a prolog node is provided. The propheter node comprises one or more memories, and one or more processors. The memory stores executable instructions. The processor executes the executable instructions to implement the method as described above.
Another aspect of the embodiments of the present disclosure provides a computer-readable storage medium having stored thereon computer-executable instructions for implementing the method as described above when executed.
Another aspect of embodiments of the present disclosure provides a computer program comprising computer executable instructions for implementing the method as described above when executed.
One or more of the above-described embodiments may provide the following advantages or benefits: the data under the chain can be transmitted to the block chain network by using the decentralized prediction machine based on the stock authorization certification mechanism (namely, the DPoS consensus mechanism), so that the defects that the node data of the decentralized prediction machine in the related technology is difficult to reach the agreement and is easy to attack are overcome, and the accuracy and the authenticity of the data sent to the block chain network are improved to a certain extent.
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The foregoing and other objects, features and advantages of the disclosure will be apparent from the following description of embodiments of the disclosure, which proceeds with reference to the accompanying drawings, in which:
fig. 1 schematically illustrates an example system architecture for an out-of-chain data uplink system for a blockchain network in accordance with an embodiment of the present disclosure;
fig. 2 schematically illustrates a flow diagram of an out-of-chain data uplink method for a blockchain network according to an embodiment of the present disclosure;
fig. 3 schematically illustrates a flowchart of processing, by a talker network, downlink data obtained by each talker node based on a DPoS mechanism according to an embodiment of the present disclosure;
FIG. 4 schematically illustrates a block diagram of a docking device for interfacing a propheter node with an external data source, according to an embodiment of the present disclosure;
fig. 5 schematically illustrates a block diagram of an off-link data uplink apparatus for a blockchain network according to an embodiment of the present disclosure; and
fig. 6 schematically illustrates a block diagram of a computer system suitable for implementing an off-link data uplink method for a blockchain network according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
Embodiments of the present disclosure provide an off-link data uplink method, apparatus, and system for a blockchain network, a talker node, and a computer-readable storage medium. According to the embodiments of the disclosure, the off-line data can be transmitted to the blockchain network by using the decentralized prediction machine based on the share authorization certification mechanism (i.e., the DPoS consensus mechanism), so that the defects that the node data of the decentralized prediction machine in the related art is difficult to reach the consistency and is easy to attack are overcome, and the accuracy and the authenticity of the data sent to the blockchain network are improved to a certain extent.
It should be noted that the method and apparatus for uplink of data outside a chain for a block chain network determined in the embodiments of the present disclosure may be used in the financial field, and may also be used in any field other than the financial field.
Fig. 1 schematically illustrates an example system architecture 100 for an off-link data uplink system for a blockchain network in accordance with an embodiment of the present disclosure.
As shown in fig. 1, the system architecture 100 may include an on-chain system 101, an off-chain system 102, and an external data source 104.
The on-chain system 101 may be disposed in a blockchain network. User contracts and predictive engine contracts are deployed in the on-chain system 101. The user contract is a data query request initiated by an intelligent contract in the block chain network, and the prediction mechanism is an interface interacting with the user contract.
The user contract is used to invoke a predictive engine contract.
The predicting machine contract is used for responding to the calling of the user contract, initiating a data uplink request to the predicting machine network and feeding back the acquired final data to the user contract.
In the system 101 on the chain, the user makes an adaptation of the user contract by querying data in the blockchain network, and then calls the president contract by the user contract.
The downlink system 102 includes a predictive engine network. The predictive speaker network may include M predictive speaker nodes, where M is an integer greater than or equal to 2. The predictive-machine network in the downlinker system 102 according to an embodiment of the present disclosure is a decentralized network of predictive-machine nodes. The nodes of the prediction machines respectively and independently acquire the downlink data from the external data source 104, and each node of the prediction machines can agree on the downlink data acquired by itself and other nodes of the prediction machines in the network of the prediction machines according to the DPoS consensus mechanism to obtain final data, and then pass the final data through the prediction machine contract of the system 101 on the chain. And finally, feeding back the contract to the user through a prediction machine contract, thereby transmitting the final data to the block chain network.
According to an embodiment of the present disclosure, the on-chain system 101 and the off-chain system 102 may constitute an off-chain data-on-chain system for a block-chain network. By means of the off-chain data uplink system for the block chain network, when an intelligent contract on the block chain network has an interaction demand for acquiring external real data, the prediction machine network can help the intelligent contract to collect external data outside the chain after receiving the demand, and the acquired data is fed back to the intelligent contract on the chain after verification.
The prediction machine network of the embodiment of the disclosure is a region-centered prediction machine based on a DPoS consensus mechanism. Wherein, DPoS is the abbreviation of deleted Proof of stamp, namely the certification authority mechanism. The DPoS share authorization certification mechanism is a consensus protocol, and solves the consensus problem in a fair and democratic way by using the power of agreeing voting of interest related parties.
Under the DPoS consensus mechanism, all network parameters, from the charging schedule to the block interval and the transaction size, can be adjusted through the selected representative. The deterministic selection of the block producer allows an average of only 1 second to confirm the transaction. Perhaps most importantly, the consensus protocol is intended to protect all participants from unnecessary regulatory interference.
DPoS is mainly divided into two parts: (1) voting by the stakeholders to select a group of block producers; and (2) the block producer schedules production according to turns. As with PoW, in DPoS, the rule of the final wins is still the longest chain wins. At any time, when an honest node sees a valid longest chain, it switches from the current branch to the longest chain, thereby making the longest chain longer and longer. Unlike PoW and PoS, however, DPoS can still operate robustly under most network conditions.
The block production process under the DPoS consensus scheme is briefly described as follows. In the normal production process, the block producer turns to flow out the blocks according to a certain time interval, and the blocks produced by any block-producing person outside the non-turn time are all regarded as invalid blocks, so that the longest effective chain can be generated as long as each block-producing person produces the blocks on time. When a malicious bifurcation attack of a few nodes is faced, the block-out speed of the few nodes is smaller than that of the majority of nodes, so that honest majority of nodes generate the longest chain and bifurcation is invalid. Network outages are a challenge for many blockchain networks, and in the case of network outages, there may be a few blockmen per fork. However, after the network is connected, the block-out person on each branch can switch to the longest chain to form the longest chain, and the branch is connected to the longest chain.
And a voting supervision process is provided under a DPoS consensus mechanism. In the DPoS consensus mechanism, a very important mechanism is that a supervision position is added. In the DPoS, a stakeholder (Token holder) can eliminate non-honest chunky people by voting and select honest chunky people, so that the stable operation of a network is ensured.
For example, when the number of the block-out nodes in the network is insufficient, the stakeholder nodes of the network may select a new group of block-out nodes by voting, and recover the participation degree of the network, and the chain formed by the new block-out nodes will form the longest chain due to the highest participation degree of the network. Similarly, when multiple out-of-block nodes diverge simultaneously, it is also possible to substitute the offender's outings by voting, and the chain determined by the honest node will form the longest chain.
On the other hand, because the number of block producers in the DPoS consensus mechanism is selected and determined in advance, in order to prevent cheating caused by mutual recognition between different block output nodes, the system can reintegrate the block output sequence every time a round of block output is carried out, and only one branch is ensured to be the longest chain finally through the shuffling.
Additionally, a docking device 103 may also be included in the system architecture 100. Each prediction machine node can acquire data from a corresponding external data source 104 through the docking device 103 docked with the prediction machine node, and adapt and unify the acquired data to obtain the downlink data. In an embodiment, each talker node may respectively interface with one docking device 103, interface with an external data source 104 through the docking device 103, perform encryption transmission to each talker node after adapting and unifying the format of the data source data. The docking device 103 may be an electronic device that communicates with the talker node, or may be provided in the talker node and become a component of the talker node. An exemplary structure of the docking device 103 may be referred to in relation to the description of fig. 4 below.
The external data sources 104 may include URLs (Uniform resource locators) in the network, IPFS (Internet file system), search engine, cross-chain data connecting different blockchains, DApps (decentralized applications), or other data sources.
The method for uplink of data out of a block chain network according to the embodiment of the present disclosure may be performed by the predictive machine network 102, for example, the method according to the embodiment of the present disclosure may be performed by each predictive machine node in the predictive machine network 102, so as to implement data consensus based on the DPoS mechanism in the predictive machine network 102. Accordingly, the off-link data uplink apparatus for the blockchain network according to the embodiment of the present disclosure may be disposed in at least one talker node in the talker network 102.
It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
Fig. 2 schematically shows a flowchart of an off-link data uplink method for a blockchain network according to an embodiment of the present disclosure.
As shown in fig. 2, the method for uplink data outside the block chain network according to this embodiment may include operations S210 to S230, which may be applied to a predictive network in the downlink system 102.
In operation S210, a data uplink request initiated by a predictive engine contract in response to a user contract invocation is received. The prediction machine contract is deployed in the block chain network, and the user contract is a data query request initiated by an intelligent contract in the block chain network.
In operation S220, downlink data acquired by each of the M talker nodes in response to the data uplink request is processed based on the share grant certification mechanism to obtain final data.
In operation S230, the final data is fed back to the predictive machine contract, so that the final data is fed back to the customer contract through the predictive machine contract. The prediction machine contract can receive final data obtained by processing one or more prediction machine nodes in the prediction machine network based on the DPoS mechanism, aggregate the final data into single data, feed the single data back to a user contract, and finally transmit the single data to an intelligent contract in the block chain network.
The block chain is a closed environment, and real world data outside the chain cannot be actively acquired on the chain. Mainly because the blockchain cannot actively initiate Network call and the intelligent contract on the chain passively receives data. Secondly, smart contracts are not really fully intelligent, and they only reach a program in a triggered state if corresponding conditions are met. In view of this, the embodiment of the present disclosure uses a decentralized prognostics machine based on a DPoS consensus mechanism of a share authorization certification mechanism, calls a prognostics machine contract through a user contract, then initiates a request to a prognostics machine network through the prognostics machine contract, obtains data from the outside based on a node of the prognostics machine in the request, performs consensus agreement on the obtained data based on the DPoS mechanism, obtains final data, and transmits the final data to a block chain. In this way, the external information is written into the block chain, and the data intercommunication between the block chain and the real world is completed. Allowing a defined intelligent contract to react to an undefined outside world.
The embodiment of the disclosure utilizes the decentralized prediction machine based on the DPoS consensus mechanism, can overcome the defects that the node data of the decentralized prediction machine in the related technology is difficult to be consistent and is easy to be attacked, and improves the accuracy and the authenticity of the data sent into the block chain network to a certain extent.
Fig. 3 schematically shows a flowchart of processing, by the talker network, the downlink data obtained by each talker node based on the DPoS mechanism in operation S220 according to an embodiment of the present disclosure.
As shown in fig. 3, operation S220 may include operations S301 to S303 according to an embodiment of the present disclosure.
In operation S301, stakeholder nodes (Stakeholes also known as Stakeholders) in the predictive-machine network select any number of witness nodes from the predictive-machine network.
In operation S302, N winning nodes are selected in two rounds from the predictive machine network by any number of witness nodes, where N is an integer greater than 1 and less than M.
In the two-round selection, node screening can be carried out according to different parameters of the nodes of the prediction machine, and high-quality and reliable nodes of the prediction machine can be screened from the prediction machine network.
In one embodiment, the M predictor nodes may be first sorted from superior to inferior in performance in a first round of screening based on a first parameter, and Q candidate nodes ranked top may be screened from the M predictor nodes, where Q is an integer greater than 1 and less than M. And then, in the second round of screening, the Q candidate nodes are sorted from good to bad according to the performance based on the second parameter, and N winner nodes which are sorted in the top are screened out, wherein N is larger than Q/2 (namely more than half of the nodes). Wherein the first parameter and the second parameter are different.
For example, the first parameter may be a node weight and the second parameter may be a node status parameter.
In the decentralized talkback network, different talkback nodes can be set to have different node weights. The node weight for each predictive engine may be determined, for example, based on the trustworthiness level of the data collected by each predictive engine node during the historical provision of the data. Therefore, a group of prediction machine nodes with higher credibility can be screened out based on the first parameters.
The node status parameters may be, for example, parameters determined by integrating the stability of the node, whether the node is down currently, the current operating status, and/or historical down conditions. Therefore, through the second round of screening, a group of speaker nodes which are reliable and have better current states can be selected.
Therefore, through two rounds of screening, a reliable node with good performance state can be selected as a winning node.
Then, in operation S303, final data is obtained based on the downlink data obtained by the N winning nodes.
In one embodiment, Q may be 9 and N may be 5. That is, in the speaker network, the interest-related nodes select any number of witnesses and select 9 large speaker nodes in the first round. And summarizing and submitting the downlink data collected by the 9 big prediction machine nodes, then preferably selecting the data of 5 nodes (more than half of the nodes) in the second round of selection, performing weighted average, determining the data as final data, and providing the final data to the data requester.
Therefore, high-quality nodes can be screened from the prediction machine network through two rounds of screening by using a DPoS (delayed Proof of behaviour) share authorization certification mechanism, and the credibility of data transmitted to the block chain is effectively improved.
Fig. 4 schematically shows a block diagram of a docking device 103 for docking a propheter node with an external data source 104 according to an embodiment of the present disclosure. According to some embodiments of the present disclosure, the docking device 103 may be provided in a propheter node docked thereto, forming part of the propheter node.
As shown in fig. 4, the docking device 103 may include a data communication interface module 401, a signal processing module 402, a data adaptation format module 403, a data encryption module 404, and a talker interface module 405.
The data communication interface module 401 may be used to collect data from the external data source 104.
The signal processing module 402 is used to pre-process the acquired data, such as cleaning, denoising, and the like.
The data adapting format module 403 is configured to receive the data preprocessed by the signal processing module 402, and then perform adaptation and format unification.
The data encryption module 404 is used to encrypt data.
The predictive speaker interface module 405 is used to transmit encrypted data to the corresponding predictive speaker node.
Fig. 5 schematically shows a block diagram of an off-link data uplink apparatus 500 for a blockchain network according to an embodiment of the present disclosure.
As shown in fig. 5, the apparatus 500 for uplink of data out-of-link for block chain network may include a receiving module 510, a DPoS processing module 520, and a feedback module 530. The apparatus 500 may be disposed in one or more nodes of a predictive controller network, and is configured to implement the methods described in fig. 2 to 3.
The receiving module 510 may perform, for example, operation S210, for receiving a data uplink request initiated by a predictive engine contract in response to a call of a user contract; the prediction machine contract is deployed in the blockchain network, and the user contract is a data query request initiated by an intelligent contract in the blockchain network.
The DPoS processing module 520 may perform operation S220, for example, to process downlink data obtained by the M talker nodes responding to the uplink data request respectively based on the share grant certification mechanism, so as to obtain final data.
The feedback module 530 may, for example, perform operation S230 for feeding back the final data to the predictive-mechanical contract, so as to feed back the final data to the user contract through the predictive-mechanical contract.
Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least partially as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or by any other reasonable means of hardware or firmware for integrating or packaging a circuit, or by any one of or a suitable combination of any of software, hardware, and firmware. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.
For example, any plurality of the data communication interface module 401, the signal processing module 402, the data adaptation format module 403, the data encryption module 404, the talker interface module 405, the receiving module 510, the DPoS processing module 520, and the feedback module 530 may be combined in one module to be implemented, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the data communication interface module 401, the signal processing module 402, the data adaptation format module 403, the data encryption module 404, the predictive coder interface module 405, the receiving module 510, the DPoS processing module 520, and the feedback module 530 may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware by any other reasonable manner of integrating or packaging a circuit, or in any one of three implementations of software, hardware, and firmware, or in a suitable combination of any of them. Alternatively, at least one of the data communication interface module 401, the signal processing module 402, the data adaptation format module 403, the data encryption module 404, the predictive speaker interface module 405, the reception module 510, the DPoS processing module 520, and the feedback module 530 may be implemented at least in part as a computer program module that, when executed, may perform corresponding functions.
Fig. 6 schematically illustrates a block diagram of a computer system 600 suitable for implementing an off-link data uplink method for a blockchain network according to an embodiment of the present disclosure. The computer system 600 shown in fig. 6 is only one example and should not bring any limitations to the functionality or scope of use of the embodiments of the present disclosure. The computer system 600 may be located at one or more predictive-machine nodes in a predictive-machine network.
As shown in fig. 6, a computer system 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. Processor 601 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 601 may also include onboard memory for caching purposes. Processor 601 may include a single processing unit or multiple processing units for performing the different actions of the method flows according to embodiments of the present disclosure.
In the RAM603, various programs and data necessary for the operation of the system 600 are stored. The processor 601, the ROM 602, and the RAM603 are connected to each other via a bus 604. The processor 601 performs various operations of the method flows according to embodiments of the present disclosure by executing programs in the ROM 602 and/or RAM 603. It is to be noted that the program may also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.
According to an embodiment of the present disclosure, system 600 may also include an input/output (I/O) interface 605, input/output (I/O) interface 605 also connected to bus 604. The system 600 may also include one or more of the following components connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program, when executed by the processor 601, performs the above-described functions defined in the system of the disclosed embodiments. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium described above bears one or more programs which, when executed, implement a method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: 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), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, a computer-readable storage medium may include ROM 602 and/or RAM603 and/or one or more memories other than ROM 602 and RAM603 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method provided by the embodiments of the present disclosure, when the computer program product is run on an electronic device, the program code being adapted to cause the electronic device to carry out the method provided by the embodiments of the present disclosure.
The computer program, when executed by the processor 601, performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure. The above described systems, devices, modules, units, etc. may be implemented by computer program modules according to embodiments of the disclosure.
In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted in the form of a signal on a network medium, distributed, downloaded and installed via the communication section 609, and/or installed from a removable medium 611. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.
Claims (8)
1. An off-link data uplink method for a block chain network is applied to a predictive machine network, wherein the predictive machine network comprises M predictive machine nodes, and M is an integer greater than or equal to 2; the method comprises the following steps:
receiving a data uplink request initiated by a predictive engine contract in response to a call by a user contract; the president contract is deployed in the blockchain network, and the user contract is a data query request initiated by an intelligent contract in the blockchain network;
processing downlink data acquired by the M prophetic machine nodes respectively responding to the data uplink request based on a share authorization certification mechanism to obtain final data; and
feeding back the final data to the presbyope contract to feed back the final data to the user contract through the presbyope contract;
wherein,
the processing, by the grant certification based on shares, downlink data obtained by each of the M talker nodes in response to the data uplink request to obtain final data includes:
the nodes of interest-related parties in the predictive machine network select any number of witness nodes from the predictive machine network;
selecting N winning nodes from the speaker prediction network by the witness nodes with any number in two rounds, wherein N is an integer larger than 1 and smaller than M; wherein,
in the first round of screening, sorting the M nodes of the prediction machines from good to bad according to performance based on a first parameter, and screening out Q candidate nodes which are sorted in the front, wherein Q is an integer which is larger than 1 and smaller than M; and
in the second round of screening, Q candidate nodes are sorted from good to bad according to the performance based on a second parameter, N winner nodes which are sorted in the top are screened out,
wherein Q/2 is more than N and less than Q; wherein the first parameter and the second parameter are different; and
and obtaining the final data based on the downlink data obtained by the N winning nodes.
2. The method of claim 1, wherein,
the first parameter comprises a node weight; and
the second parameter comprises a node status parameter.
3. The method according to claim 1, wherein Q-9 and N-5, and the obtaining the final data based on the downlink data obtained by the N winning nodes comprises:
obtaining the final data based on a weighted average of the downlink data of the 5 winning nodes.
4. The method according to any one of claims 1 to 3, wherein the processing, by the certificate-based-authority mechanism, downlink data acquired by each of the M propheter nodes in response to the data uplink request to obtain final data comprises:
and each prediction machine node acquires data from a corresponding external data source, adapts and unifies the format of the acquired data, and obtains the downlink data.
5. An out-of-chain data uplink device for a blockchain network is arranged in a predictive speech machine network, wherein the predictive speech machine network comprises M predictive speech machine nodes, and M is an integer greater than or equal to 2; the device comprises:
a receiving module, configured to receive a data uplink request initiated by a predictive engine contract in response to a user contract invocation; the president contract is deployed in the blockchain network, and the user contract is a data query request initiated by an intelligent contract in the blockchain network;
a DPoS processing module, configured to process, based on a share authorization certification mechanism, downlink data obtained by each of the M propheter nodes in response to the data uplink request, so as to obtain final data, where the DPoS processing module is configured to:
the nodes of interest-related parties in the predictive machine network select any number of witness nodes from the predictive machine network;
selecting N winning nodes from the speaker prediction network by the witness nodes with any number in two rounds, wherein N is an integer larger than 1 and smaller than M; the method comprises the steps that M nodes of the prediction machine are sorted from good to bad according to performance in a first round of screening based on a first parameter, and Q candidate nodes which are sorted in the top are screened out, wherein Q is an integer which is larger than 1 and smaller than M; and sorting the Q candidate nodes from good to bad according to the performance in the second round of screening based on a second parameter, and screening N winner nodes which are sorted in the top way, wherein Q/2 is more than N and less than Q; wherein the first parameter and the second parameter are different; and
obtaining the final data based on the downlink data obtained by the N winning nodes;
and the feedback module is used for feeding back the final data to the prediction machine contract so as to feed back the final data to the user contract through the prediction machine contract.
6. An out-of-chain data uplink system for a blockchain network, comprising:
the system on the chain is arranged in the block chain network; a user contract and a president machine contract are deployed in the on-chain system, wherein:
the user contract is a data query request initiated by an intelligent contract in the block chain network and is used for calling the president contract;
the predicting machine contract is used for responding to the calling of the user contract to initiate a data uplink request and feeding back the obtained final data to the user contract;
an under-link system comprising a predictive-machine network comprising M predictive-machine nodes, wherein M is an integer greater than or equal to 2, the predictive-machine network configured to:
receiving the data uplink request initiated by the predictive engine contract;
processing downlink data acquired by the M prophetic machine nodes respectively responding to the data uplink request based on a share authorization certification mechanism to obtain final data; and
feeding back the final data to the presbyope contract to feed back the final data to the user contract through the presbyope contract;
wherein,
the processing, by the grant certification based on shares, downlink data obtained by each of the M talker nodes in response to the data uplink request to obtain final data includes:
the nodes of interest-related parties in the predictive machine network select any number of witness nodes from the predictive machine network;
selecting N winning nodes from the speaker prediction network by the witness nodes with any number in two rounds, wherein N is an integer larger than 1 and smaller than M; wherein,
in the first round of screening, sorting the M nodes of the prediction machines from good to bad according to performance based on a first parameter, and screening out Q candidate nodes which are sorted in the front, wherein Q is an integer which is larger than 1 and smaller than M; and
in the second round of screening, Q candidate nodes are sorted from good to bad according to the performance based on a second parameter, N winner nodes which are sorted in the top are screened out,
wherein Q/2 is more than N and less than Q; wherein the first parameter and the second parameter are different;
and
and obtaining the final data based on the downlink data obtained by the N winning nodes.
7. A propheter node, comprising:
one or more memories storing executable instructions; and
one or more processors executing the executable instructions to implement the method of any one of claims 1-4.
8. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 4.
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