CN116909695A - Computing power task processing method and system of computing power network based on block chain - Google Patents
Computing power task processing method and system of computing power network based on block chain Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a system for processing a computing task of a computing network based on a blockchain, wherein the method comprises the following steps: establishing a computing task processing blockchain network based on a computing network; resolving the computing power demand to generate a corresponding computing power task, establishing a hierarchical structure model matched with the computing power task and the resource nodes, matching the computing power task with each resource node, and determining a target resource node for executing the computing power task; constructing an environment container of the computing task, and storing an information file of the computing task according to the environment container and a preset storage mode; the management node sends the information file of the calculation task to the target resource node so that the target resource node can complete the calculation task according to the information file configuration task environment; after the target resource node finishes the calculation task, broadcasting the completion information of the calculation task, and judging whether the completion information meets preset completion conditions or not by the management node; if yes, determining the completion rewarding information of the target resource node.
Description
Technical Field
The embodiment of the invention relates to the technical fields of a computational power network, a block chain and safety, in particular to a computational power task processing method and a system of the computational power network based on the block chain.
Background
With the advent of the 5G era, digital economy has been rapidly developed, the amount of information data generated by each scene and service has been increased in a burst manner, and demands for data collection, storage, calculation, analysis and the like have been continuously increased. Different types of data centers, nodes and gateways with computing capability are also accessed into the Internet from all directions, the whole computing resource presents the development trend of distributed deployment, and a computing network is generated.
The computing power network deeply fuses computing power resources and network resources so as to achieve the effect of integrating computing power and network. The core purpose of the computing power network is to process massive ubiquitous computing power tasks generated in real time, so that the computing power demand party and the computing power provider are in butt joint, and the timely supply and the efficient utilization of computing power resources are realized. The computational effort task is used as a key medium for distributing and dynamically calculating the effort resources, and the safety and the reliability of the computational effort task are very important. Because the computing power task relates to a large number of resource devices and network nodes in different regions, the computing power task is easily subject to network attack of malicious nodes, so that a computing power provider cannot obtain due rewards, the task cannot be effectively performed, information is leaked, and the like, and a complete computing power task processing and safety guarantee mechanism is urgently needed.
Aiming at the problems of processing and reliability of calculation tasks in a calculation network, the prior art adopts the following modes:
1) The related files of the computing task are configured at the network node, but the safety and reliability problems in the processing process of the computing task are not considered, network attacks caused by malicious nodes cannot be avoided, and the computing task completion condition and the environment configuration files can be damaged.
2) And judging the calculation force request broadcasted by the calculation force entrusting node, and broadcasting reply information to the calculation force request when the calculation force request is determined to meet the bearing condition. And after receiving the selection confirmation information broadcast by the calculation power entrusting node, pulling the task mirror image and running. Because the computing power request comprises the computing power task and the task mirror image, the task mirror image is broadcast, so that a plurality of nodes perform operations such as collection, a large amount of computing resources are consumed, the time consumption is long, and the working efficiency is low.
The safety problem is not considered in the above processes, the task information cannot be ensured not to be leaked in the process of arranging the calculation task, and the task processing process is not attacked and interfered by external malicious nodes. Moreover, the scattered and distributed characteristics of the power calculation demand side and the supply side of the power calculation task enable the task supervision and management to be time-consuming and labor-consuming in the whole process, and cannot achieve higher working efficiency.
Disclosure of Invention
In view of the foregoing, embodiments of the present invention have been developed to provide a method and system for processing a computing task in a blockchain-based computing network that overcomes or at least partially solves the foregoing problems.
According to an aspect of the embodiment of the invention, there is provided a method for processing a computing task of a computing network based on a blockchain, the method comprising:
establishing a computing task processing blockchain network based on a computing network; wherein the blockchain network comprises resource nodes and management nodes; the resource node is used for executing the calculation task; the management node is used for information management of the calculation task and management of the execution result of the calculation task;
resolving the computing power demand to generate a corresponding computing power task, establishing a hierarchical structure model matched with the computing power task and the resource nodes, matching the computing power task with each resource node, and determining a target resource node for executing the computing power task;
constructing an environment container of the computing task, and storing an information file of the computing task according to the environment container and a preset storage mode; the management node sends the information file of the calculation task to the target resource node so that the target resource node can complete the calculation task according to the information file configuration task environment;
After the target resource node finishes the calculation task, broadcasting the completion information of the calculation task, and judging whether the completion information meets preset completion conditions or not by the management node; the completion information comprises environment information when the task is completed;
if yes, determining the completion rewarding information of the target resource node.
According to another aspect of an embodiment of the present invention, there is provided a system for processing a computational power task of a blockchain-based computational power network, the system including: a computing power network, a blockchain network; the blockchain network comprises a resource node and a management node; the resource node is used for executing the calculation task; the management node is used for information management of the calculation task and management of the execution result of the calculation task;
the computing power network is used for: resolving the computing power demand to generate a corresponding computing power task, establishing a hierarchical structure model matched with the computing power task and the resource nodes, matching the computing power task with each resource node, and determining a target resource node for executing the computing power task; constructing an environment container of the computing task, and storing an information file of the computing task according to the environment container and a preset storage mode;
the blockchain network is used to: the management node sends the information file of the calculation task to the target resource node; the target resource node configures a task environment to complete a computing task according to the information file; after the target resource node finishes the calculation task, broadcasting the completion information of the calculation task, and judging whether the completion information meets preset completion conditions or not by the management node; the completion information comprises environment information when the task is completed; if yes, determining the completion rewarding information of the target resource node.
According to yet another aspect of an embodiment of the present invention, there is provided a computing device including: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the computing task processing method of the computing network based on the block chain.
According to yet another aspect of an embodiment of the present invention, there is provided a computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to a method for processing a computing task of a blockchain-based computing network as described above.
According to the power computing task processing method and system based on the power computing network, the power computing network is used for establishing the power computing task processing block chain network based on the power computing network, different power computing demands are disassembled into different power computing tasks, environment containers are constructed for the different power computing tasks, accurate configuration of the environment is ensured, meanwhile, information files of the power computing tasks in the environment containers are recorded point to point between a management node and a target resource node in the block chain network, further supervision and management of power computing environment deployment are achieved, and safety and traceability of a power computing task processing flow are improved. Further, a hierarchical structure model with the computing power task matched with the resource nodes is constructed, the matched target resource nodes are determined through hierarchical analysis, automatic pairing of the resource nodes and the computing power task is achieved, and working efficiency is improved. After the target resource node finishes the calculation task, the management node judges whether the completion condition is met according to the completion information to determine corresponding completion rewarding information, the whole process is processed in a block chain network in a linking way, the reliability and reliability of the calculation task matching and the controllable and manageable task completion process are ensured, and the safety and traceability of the calculation task processing process are improved.
The foregoing description is only an overview of the technical solutions of the embodiments of the present invention, and may be implemented according to the content of the specification, so that the technical means of the embodiments of the present invention can be more clearly understood, and the following specific implementation of the embodiments of the present invention will be more apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 illustrates a flow diagram of a method of processing a computing task of a blockchain-based computing network in accordance with an embodiment of the invention;
FIG. 2 is a schematic diagram of an information file storage structure of a computing task;
FIG. 3 shows a schematic diagram of a computational power network and a blockchain network architecture;
FIG. 4 illustrates a schematic diagram of a power task processing system of a blockchain-based power network in accordance with an embodiment of the invention;
FIG. 5 illustrates a schematic diagram of a computing device, according to one embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
FIG. 1 illustrates a flow chart of a method of processing a computing task of a blockchain-based computing network, as shown in FIG. 1, according to an embodiment of the invention, the method including the steps of:
step S101, a computing task processing block chain network is established based on the computing network.
In this embodiment, a power computing task processing blockchain network is established for the power computing network, and the power computing network deeply merges the trusted power computing resource with the network resource so as to achieve the effect of integrating the power computing network. The computing network may be deployed in different types of networks such as IP metropolitan area networks, mobile internetworks, cloud service networks, and so on. A computational effort task processing blockchain network is built at a computational effort management layer of the computational effort network, and the blockchain network comprises resource nodes and management nodes. The resource node is used for executing the computing power task, and the trusted computing power resource is adopted as the resource node; the management node is used for information management of the calculation task and management of the execution result of the calculation task, has the capabilities of storage and duplex communication, can perform information interaction and file transmission with the resource node, and is used for supervising and managing information files of the calculation task, execution completion conditions of the calculation task and the like.
For the resource nodes, the resource nodes can be classified according to hardware performance and the like provided by the resource nodes, different uplink rules are formulated, and the weight reduction of the block chain is realized. Specifically, the resource node includes a trusted computing resource provider that passes identity, computing power and other verification in a computing power network, such as a personal computer with idle computing power, an enterprise or company with cloud server, a computing node in an IP metropolitan area network, an institution department and the likeCenter, etc. The resource node has the capabilities of calculation, storage and duplex communication, keeps regular communication with the power computing network, and can send heartbeat signals to the power computing management platform within a preset fixed period so as to ensure that the resource node is online and has no faults. The resource node can be up-linked to become the resource node after each computing resource is registered, registered and checked. And after receiving the registration application of the computing power resource, acquiring the hardware information of the computing power resource to verify and then grading the resource node. The registration application of the computing power resource requires submitting evidence information such as identity, computing power capability and the like, and the computing power network performs verification according to the acquired hardware information, wherein the hardware information comprises a chip type x with computing power i Number k, hard disk storage capacity Ca, number R of reads/writes per second of hard disk, network bandwidth B, access delay D, and the like. The computing power management layer of the computing power network confirms that the computing power resources passing the verification can be used as resource nodes by verifying hardware information and the like, and if the verification is not passed, the computing power resources are required to be subjected to registration application again. Calculating according to the hardware information to obtain the performance P of the resource node, wherein the performance P is as follows:
wherein f 1 (x) For chip type measurement mapping function, q is redundant computing power of equipment, alpha 1 、α 2 、α 3 、α 4 、α 5 For the preset coefficient, the corresponding coefficient of influence of each hardware performance can be determined according to the calculation force requirements under different situations, and the preset coefficient is specifically set according to the implementation situation, and is not limited herein.
After the performance P of the resource node is calculated, the level information of the resource node can be truly obtained according to the performance P, and the reputation value H of the resource node can be initialized. The level information includes, for example, a first level, a second level, and a third level, and the hierarchy may be as follows:
wherein beta is 1 、β 2 The performance level threshold is determined according to the overall computing power resource performance under different situations, specifically set according to implementation conditions, and is not limited herein. s is(s) 1 I.e., a first level, which includes all nodes, can synchronously record each block information of the blockchain network, s 2 I.e. second level, s 3 The third level, the second level and the third level comprise light nodes, can synchronously record the block information of preset height in the blockchain network, such as the information of the latest block of the 2/3 part of the total block height, and the third level synchronously records the information of the latest block of the 1/3 part of the total block height, thereby relieving the storage pressure of the node with lower hardware performance. After the resource nodes are determined, the number of the management nodes is not less than 1/3 of the number of the resource nodes.
Step S102, resolving the computing power demand to generate a corresponding computing power task, establishing a hierarchical structure model of matching the computing power task with the resource nodes, matching the computing power task with each resource node, and determining a target resource node for executing the computing power task.
The service providing layer in the computing power network receives computing power resource demands from users in the IP metropolitan area network, the service arrangement layer and the computing power management layer in the computing power network can disassemble the computing power demands to generate different types of computing power tasks, and the types of the generated computing power tasks comprise computing power tasks such as logic operation types, parallel computing types, neural network acceleration types and the like.
When searching matched resource nodes for the computing task, the generated computing task can trigger the computing task matching intelligent contract of the blockchain network, the computing task and the resource node are matched for hierarchical analysis, and the best matching with the computing task is searched according to the performance, credibility, routing and other conditions of the resource node, so that the matching mode is more easily adjusted according to the requirements of users by adopting the hierarchical analysis mode, and the personalized requirements of the users are met. If the timeliness requirement of the user on the processing of the calculation task is higher, when the hierarchical structure model establishes a judgment matrix, the influence weight of the matching factors such as routing efficiency is set to be higher than other matching factors, so that the higher efficient task processing speed and the like are achieved.
Specifically, a hierarchical structure model of matching the computing task with the resource node is established, hierarchical analysis is carried out on the matching of the computing task with the resource node, and a target resource node for executing the computing task is determined. The target layer is used for determining the resource node with the highest adaptation degree with the computing task. The hierarchical structure model comprises a target layer, a criterion layer and a resource layer. The resource layer is used for matching idle resource nodes meeting the demands of computing power tasks, the criterion layer comprises matching factors of the computing power tasks, and the matching factors comprise familiarity g of an environment container and computing capacity C of the resource nodes b Reputation value H, liveness L, routing efficiency w, etc. Wherein the resource node calculates the capability C b Calculated according to the following formula:
k a the total number of chips required for the resource node Fu Gesuan force task type, f 1 (x) For chip type measurement mapping function, q is redundant computing power of equipment, x i Is a chip type with computing power.
Based on the matching factors of the criterion layer, constructing a judging matrix A for the resource nodes determined by the resource layer, and marking the comparison result among the matching factors of the computing tasks by the judging matrix, wherein the comparison result is as follows:
wherein a is ij A comparison result value of the matching factor representing the ith computational task with respect to the jth matching factor, and a ij ＝a ji . Here, a can be carried out according to the requirement characteristics of the calculation task by adopting the assignment range of 1-9 ij Is determined by the above-described method. n represents the total number of matching factors of the calculation tasks included in the criterion layer, and in this embodiment, n=5 is taken as an example for explanation, and the number of matching factors can be specifically adjusted according to the implementation situation, which is not limited herein.
And (3) carrying out normalization processing on each column of the judgment matrix A, wherein the normalization processing is as follows:
calculating the average value of each row according to the judgment matrix after normalization processing to obtain the matching factor weight omega i And a corresponding matching factor feature vector Ω, as follows:
according to the judgment matrix A and the matching factor weight omega i The corresponding matching factor characteristic vector omega is calculated to obtain a consistency ratio C R To determine whether the consistency ratio is less than a preset ratio threshold. The method comprises the following steps:
wherein lambda is max As the maximum characteristic root, C I (Consistency Index) is a consistency index, C R (Consistency Ratio) is a uniformity ratio, R I (Random Index) is a Random consistency Index, and the value of the Random consistency Index is a query value used in the consistency test process of the analytic hierarchy process and is set according to the implementation condition. Preset ratio thresholdCan be set to be as 0.1 if C R <And 0.1, judging that the detection is passed, otherwise, judging that the detection is not passed, and reconstructing a judgment matrix according to the matching factor feature vector and the consistency ratio of the processing calculation resource nodes until the consistency ratio is smaller than a preset ratio threshold value.
After the judgment and the inspection are passed, calculating and obtaining the fitness z of the resource node and the calculation task according to the characteristic vector omega of the matching factor of the resource node and each matching factor i The resource node with the highest adaptation degree is screened to be used as a target resource node for executing the computational power task, and the method is as follows:
maxz i ＝(g,C b ,H,L,w)Ω
step S103, an environment container of the computing task is constructed, an information file of the computing task is stored according to the environment container in a preset storage mode, and the management node sends the information file of the computing task to the target resource node so that the target resource node can complete the computing task according to the information file configuration task environment.
In order to ensure the accurate and consistent deployment of the computing task environment, the embodiment adopts a container technology to construct an environment container of the computing task, and stores an information file of the computing task according to the environment container in a preset storage mode. If the container technology is used for packaging, an environment container is constructed, all information files of the computing task are stored in a preset storage mode, the preset storage mode can be a merck tree mode, all information files are stored in a refined mode through an independent merck tree, on one hand, required storage space is compressed, on the other hand, the whole process of environment deployment can be recorded, and safety and reliability of the environment can be guaranteed. Specifically, as shown in fig. 2, a root directory of the computing task file is created, file entry information of a corresponding position is recorded according to a tree leaf structure, such as a computing environment deployment file (the next leaf structure contains an environment variable configuration sub-file 1 … n), a computing task analysis file, a code script, a computing task example file and the like, and the computing environment deployment file (the next leaf structure contains the environment variable configuration sub-file 1 … n), namely, initial environment information of the computing task file, is exemplified, and can be specifically set according to implementation conditions, and is not limited herein.
Further, the management node can sort the merck tree of the information file of each computing task, generate a computing task processing record, and broadcast the processing record to the blockchain network. Other management nodes receive the broadcast of the calculation task processing records and store the broadcast into a self record pool, so that the follow-up verification is conveniently performed after the calculation task is completed.
After the matched target resource node is determined, the management node and the target resource node are in butt joint with the corresponding information file of the computing task, and the management node sends the information file of the computing task to the target resource node, wherein the information file of the computing task comprises an operation environment deployment file, a computing task analysis file, a code script, a computing task example file and the like as shown in fig. 2. And the target resource node receives the information file of the matched computing power task, and utilizes the environment container to configure the environment so as to complete the computing power task.
Step S104, after the target resource node completes the calculation task, the completion information of the calculation task is broadcast, and the management node judges whether the preset completion condition is met according to the completion information.
After the target resource node completes the computing task, the target resource node can broadcast the environmental parameters, files and the like used for completing the computing task to the blockchain network in a broadcast mode according to the mode of configuring the environment to generate the merck tree containing the environmental information when completing the task. And the management node judges whether the computing task accords with a preset completion condition according to the received completion information of the computing task returned by the target resource node. If the management node compares the merck tree of the environmental information when completing the task with the merck tree of the information file initially generated by the computing task recorded by the management node, if the environmental information is consistent with the environmental information in the information file of the computing task when completing the task, the computing task is judged to be in accordance with the preset completion condition, step S105 is executed, if the environmental information is inconsistent with the environmental information, the target resource node is required to reconfigure the environment, and the computing task is re-executed, namely step S106 is executed.
Step S105, determining the completion rewards information of the target resource node.
And when the judgment meets the preset completion condition, determining that the target resource node completes the calculation task, and rewarding the target resource node. Completing the reward includes updating the reputation value and liveness of the target resource node. The reputation value is updated according to the completion difficulty coefficient of the calculation task and a preset coefficient, and the liveness is determined according to the calculation task, as follows:
H＝H'+γ·y d
L＝L'+r
wherein H' is the node credit value before updating, gamma is a preset coefficient, y d The completion difficulty coefficient of the calculation task is obtained. L' is node liveness before updating, r is liveness rewarding value for successfully completing a single calculation task, and the liveness rewarding value is determined according to the calculation task.
Optionally, the present embodiment further includes the following steps:
and S106, updating the activity of the target resource node, and re-executing the computing task by the target resource node according to the information file configuration task environment.
The management node judges that the execution of the computing task fails, and the target resource node reconfigures the task environment according to the information file to execute the computing task.
Liveness represents the aggressiveness of the resource node's corresponding task needs, which is different from the reputation, when the target resource node participates in the calculation, whether the computing task is complete or not, rewards can be received to encourage more resource nodes to remain active, thus, after the target resource node performs the computing task, the liveness of the target resource node is updated.
L＝L'+r
Wherein L' is node liveness before updating, r is liveness rewarding value for successfully completing a single calculation task, and the liveness rewarding value is determined according to the calculation task.
Optionally, after executing the computing task and completing the rewarding to the target resource node, the embodiment further includes the following steps:
optionally, the present embodiment further includes the following steps:
step S107, each management node performs consensus according to a preset period, wherein the management node generates a calculation task processing record according to an information file of the calculation task, and generates a completion record of the calculation task according to the completion of the calculation task by the target resource node, and broadcasts the completion record to the blockchain network for other nodes to receive and store.
And in a preset period, all management nodes adopt PBFT (Practical Byzantine Fault Tolerance, practical Bayesian fault-tolerant algorithm) to carry out consensus. The management node generates a calculation task processing record according to the information file of the calculation task, and finishes the calculation task according to the target resource node to obtain a completion record of the calculation task, wherein the completion record comprises a calculation task number, a target resource node ID for finishing the calculation task, credit value updating, liveness updating, calculation task information (such as type, merck tree of environment information and the like), total time consumption of the calculation task execution and the like, and the calculation task processing record and the calculation task completion record are recorded into a self record pool. And storing the calculation task processing records in the management node self record pool and the completion records of the calculation tasks into the block in a preset period, broadcasting the block to the block chain network, and facilitating the receiving and storage of each node. After receiving the blocks and passing the verification, the other management nodes can store the blocks. After the resource node such as the first level full node receives the block verification, it can be directly added to the end of the own block chain, after the second level or third level light node receives and verifies the block, it first judges whether the number of blocks stored on the own block chain exceeds the number of blocks with preset height of the corresponding level, if so, it firstly deletes the block with the lowest block height, then adds the received new block to the end of the own block chain, if not, it directly adds it to the end of the own block chain. Resource nodes of different levels are according to different block uplink rules, so that the effect of light weight is achieved. Further, if a resource node in the blockchain network fails to verify a block, the block is discarded.
The consensus mechanism may be based on the performance and scale of most resource nodes of the blockchain network, or may be an algorithm such as a workload certification mechanism, a stock right certification mechanism, a Raft consensus, etc., which is not limited herein.
In this embodiment, the structures of the power calculation network and the blockchain network are shown in fig. 3, the power calculation network is disassembled at the service providing layer according to the power calculation demand interaction with the user to generate a power calculation task, the target resource node matched with the power calculation task is determined from the resource nodes 1 … m through the intelligent contract based on the blockchain network such as hierarchical analysis, and the computing environment is deployed by using a container technology. After the target resource node executes the calculation task, the management node (such as management node 1 … n) judges and determines that the calculation task is completed, and rewards the completion information of the target resource node. Recording the processing records of the computing power tasks, the completion records of the computing power tasks generated by the computing power tasks and the like into a block (such as a block 1 … n) and broadcasting, wherein other nodes can receive and store the processing records, so that the reliability and reliability of the matching of the computing power tasks and the controllable and manageable task completion process are ensured, and the safety and traceability of the processing process of the computing power tasks are improved.
According to the computing power task processing method based on the computing power network provided by the embodiment of the invention, the computing power task processing block chain network is established based on the computing power network, different computing power demands are disassembled into different computing power tasks, environment containers are constructed for the different computing power tasks, the accurate configuration of the environment is ensured, meanwhile, the information files of the computing power tasks in the environment containers are recorded point to point between the management node and the target resource node in the block chain network, the further supervision and management of the computing power environment deployment are realized, and the safety and traceability of the computing power task processing flow are improved. Further, a hierarchical structure model with the computing power task matched with the resource nodes is constructed, the matched target resource nodes are determined through hierarchical analysis, automatic pairing of the resource nodes and the computing power task is achieved, and working efficiency is improved. After the target resource node finishes the calculation task, the management node judges whether the completion condition is met according to the completion information to determine corresponding completion rewarding information, the whole process is processed in a block chain network in a linking way, the reliability and reliability of the calculation task matching and the controllable and manageable task completion process are ensured, and the safety and traceability of the calculation task processing process are improved.
Fig. 4 shows a schematic structural diagram of a computing task processing system of a blockchain-based computing network according to an embodiment of the present invention. As shown in fig. 4, the system includes: a computing power network 410, a blockchain network 420; blockchain network 420 includes resource nodes 421 and management nodes 422; the resource node 421 is used for executing the computing task; the management node 422 is used for information management of the computing task and management of the execution result of the computing task;
the power network 410 is used to: resolving the computing power demand to generate a corresponding computing power task, establishing a hierarchical structure model matched with the computing power task and the resource nodes, matching the computing power task with each resource node, and determining a target resource node for executing the computing power task; constructing an environment container of the computing task, and storing an information file of the computing task according to the environment container and a preset storage mode;
blockchain network 420 is used to: the management node sends the information file of the calculation task to the target resource node; the target resource node configures a task environment to complete a computing task according to the information file; after the target resource node finishes the calculation task, broadcasting the completion information of the calculation task, and judging whether the completion information meets preset completion conditions or not by the management node; the completion information comprises environment information when the task is completed; if yes, determining the completion rewarding information of the target resource node.
Optionally, the computing power network 410 is further configured to: receiving a registration application of the computing power resource, and acquiring hardware information of the computing power resource; checking the hardware information, and determining that the computing power resource passing the checking is a resource node 421; calculating the performance of the resource node according to the hardware information, and initializing the reputation value of the resource node according to the level information of the real resource node 421 of the performance; the level information comprises a first level, a second level and a third level; the first level comprises all nodes, and each block information of the block chain network is synchronously recorded; the second level and the third level comprise light nodes, and block information of preset height in the block chain network is synchronously recorded.
Optionally, the computing power network 410 is further configured to: establishing a hierarchical structure model of matching of the computing task and the resource node 421 according to the triggering computing task matching intelligent contract of the blockchain network, performing hierarchical analysis on the matching of the computing task and the resource node, and determining a target resource node for executing the computing task; the power calculation task matching intelligent contract is triggered according to the generated power calculation task; the hierarchical structure model comprises a target layer, a criterion layer and/or a resource layer; the resource layer is used for matching idle resource nodes which meet the demands of calculation tasks; the criterion layer comprises matching factors of calculation tasks; the target layer is used for determining the resource node with the highest adaptation degree with the computing task; the matching factors include: environmental container familiarity, resource node computing power, reputation value, liveness, and/or routing efficiency.
Optionally, the computing power network 410 is further configured to: constructing a judgment matrix for the resource nodes determined by the resource layer based on the matching factors of the criterion layer, normalizing each column of the judgment matrix, and obtaining matching factor weights and corresponding matching factor feature vectors according to the average value of each row after normalization; judging the comparison result among the matching factors of the matrix marking each calculation task; calculating to obtain a consistency ratio according to the judgment matrix, the matching factor weight and the corresponding matching factor feature vector, and judging whether the consistency ratio is smaller than a preset ratio threshold value or not; if yes, calculating according to the matching factor feature vector of the resource node and the matching factor to obtain the adaptation degree of the resource node and the computing task, and screening the resource node with the highest adaptation degree as a target resource node for executing the computing task; if not, reconstructing a judgment matrix, and calculating a matching factor feature vector and a consistency ratio of the resource nodes until the consistency ratio is smaller than a preset ratio threshold.
Optionally, each management node 422 performs consensus according to a preset period, wherein the management node 422 generates a calculation task processing record according to an information file of the calculation task, generates a completion record of the calculation task according to completion of the calculation task by the target resource node, and broadcasts the completion record to the blockchain network for other nodes to receive and store; the information files of the calculation tasks are stored in a preset storage mode; the preset storage mode comprises a merck tree mode.
Optionally, the management node 422 determines, according to the completion information of the computing task, whether the environmental information is consistent with the information file of the computing task when the completion of the task of the information is completed; if yes, meeting the preset finishing condition; if not, the preset finishing condition is not met.
Optionally, if the preset completion condition is not met, the management node 422 updates the activity of the target resource node, and the target resource node 421 performs the computing task again according to the task environment configured by the information file;
management node 422 determines the reputation value and liveness of update target resource node 421; the credit value is updated according to the completion difficulty coefficient of the calculation task and a preset coefficient; liveness is determined from the computational effort task.
The above descriptions of the modules refer to the corresponding descriptions in the method embodiments, and are not repeated herein.
The embodiment of the invention also provides a nonvolatile computer storage medium, and the computer storage medium stores at least one executable instruction, and the executable instruction can execute the computing task processing method of the blockchain-based computing network in any method embodiment.
FIG. 5 illustrates a schematic diagram of a computing device, according to an embodiment of the invention, the particular embodiment of which is not limiting of the particular implementation of the computing device.
As shown in fig. 5, the computing device may include: a processor 502, a communication interface (Communications Interface) 504, a memory 506, and a communication bus 508.
The method is characterized in that:
processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508.
A communication interface 504 for communicating with network elements of other devices, such as clients or other servers.
The processor 502 is configured to execute the program 510, and may specifically perform relevant steps in the above-described embodiments of the power task processing method of the power network based on the blockchain.
In particular, program 510 may include program code including computer-operating instructions.
The processor 502 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included by the computing device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
A memory 506 for storing a program 510. Memory 506 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
Program 510 may be specifically configured to cause processor 502 to perform the method of processing a computational task of a blockchain-based computational network in any of the method embodiments described above. The specific implementation of each step in the program 510 may refer to corresponding descriptions in the corresponding steps and units in the above-mentioned power task processing embodiment of the block chain-based power network, which are not repeated herein. It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and modules described above may refer to corresponding procedure descriptions in the foregoing method embodiments, which are not repeated herein.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It should be appreciated that the teachings of embodiments of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of preferred embodiments of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., an embodiment of the invention that is claimed, requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components according to embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). Embodiments of the present invention may also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the embodiments of the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Embodiments of the invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.
Claims (10)
1. A computing power task processing method of a computing power network based on a block chain is characterized by comprising the following steps:
establishing a computing task processing blockchain network based on a computing network; wherein the blockchain network includes resource nodes and management nodes; the resource node is used for executing a calculation task; the management node is used for information management of the calculation task and management of the execution result of the calculation task;
resolving the computational effort requirement to generate a corresponding computational effort task, establishing a hierarchical structure model matched with the computational effort task and resource nodes, matching the computational effort task with each resource node, and determining a target resource node for executing the computational effort task;
constructing an environment container of the computing task, and storing an information file of the computing task according to the environment container and a preset storage mode; the management node sends the information file of the power calculation task to the target resource node so that the target resource node can complete the power calculation task according to the information file configuration task environment;
after the target resource node finishes the power calculation task, broadcasting the completion information of the power calculation task, and judging whether the completion information accords with a preset completion condition or not by the management node; the completion information comprises environment information when the task is completed;
If yes, determining the finishing rewarding information of the target resource node.
2. The method according to claim 1, wherein the method further comprises:
receiving a registration application of an computing power resource, and acquiring hardware information of the computing power resource;
checking the hardware information, and determining that the computing power resource passing the checking is a resource node;
calculating the performance of the resource node according to the hardware information, and initializing the reputation value of the resource node according to the level information of the resource node which is truly obtained by the performance; the level information comprises a first level, a second level and a third level; the first level comprises full nodes, and each block information of the block chain network is synchronously recorded; the second level and the third level comprise light nodes, and block information of preset height in the block chain network is synchronously recorded.
3. The method of claim 1, wherein the building a hierarchical model of the computing task matching resource nodes, matching the computing task to each resource node, determining a target resource node to perform the computing task further comprises:
Establishing a hierarchical structure model matched with the computing task and the resource node according to the triggered computing task matching intelligent contract of the blockchain network, performing hierarchical analysis on the matching of the computing task and the resource node, and determining a target resource node for executing the computing task; the power calculation task matching intelligent contract is triggered according to the generated power calculation task; the hierarchical structure model comprises a target layer, a criterion layer and/or a resource layer; the resource layer is used for matching idle resource nodes which meet the demands of the computing task; the criterion layer comprises matching factors of the computing task; the target layer is used for determining a resource node with the highest fitness with the computing task; the matching factor includes: environmental container familiarity, resource node computing power, reputation value, liveness, and/or routing efficiency.
4. The method of claim 3, wherein the establishing a hierarchical model of the matching of the computing tasks to resource nodes according to the triggered computing task matching intelligent contracts of the blockchain network, performing hierarchical analysis on the matching of the computing tasks to the resource nodes, determining a target resource node to perform the computing tasks further comprises:
Constructing a judgment matrix for the resource nodes determined by the resource layer based on the matching factors of the criterion layer, carrying out normalization processing on each column of the judgment matrix, and obtaining matching factor weights and corresponding matching factor feature vectors according to the average value of each row after normalization processing; the judgment matrix marks the comparison results among the matching factors of each calculation task;
calculating to obtain a consistency ratio according to the judgment matrix, the matching factor weight and the corresponding matching factor feature vector, and judging whether the consistency ratio is smaller than a preset ratio threshold;
if yes, calculating according to the matching factor feature vector of the resource node and the matching factor to obtain the adaptation degree of the resource node and the computing task, and screening the resource node with the highest adaptation degree as a target resource node for executing the computing task;
if not, reconstructing a judgment matrix, and calculating the matching factor feature vector and the consistency ratio of the resource nodes until the consistency ratio is smaller than a preset ratio threshold.
5. The method according to claim 1, wherein the method further comprises:
each management node performs consensus according to a preset period, wherein the management node generates a calculation task processing record according to the information file of the calculation task, generates a completion record of the calculation task according to the completion of the calculation task by a target resource node, and broadcasts the completion record to the blockchain network for other nodes to receive and store; the information files of the calculation tasks are stored in a preset storage mode; the preset storage mode comprises a merck tree mode.
6. The method according to claim 1, wherein the determining, by the management node, whether the preset completion condition is met according to the received completion information of the computing power task returned by the target resource node is specifically: the management node judges whether the environment information is consistent with the information file of the computing task when the task is completed according to the completion information of the computing task; if yes, meeting the preset finishing condition; if not, the preset finishing condition is not met.
7. The method of claim 1, wherein if the determination is not met, the method further comprises:
updating the activity of the target resource node, and executing the computing power task by the target resource node again according to the information file configuration task environment;
the determining the completion rewards information of the target resource node further includes:
determining and updating the reputation value and the liveness of the target resource node; the reputation value is updated according to the completion difficulty coefficient of the computing task and a preset coefficient; and determining the liveness according to the power calculation task.
8. A system for processing a computational power task of a blockchain-based computational power network, the system comprising: a computing power network, a blockchain network; the blockchain network comprises a resource node and a management node; the resource node is used for executing a calculation task; the management node is used for information management of the calculation task and management of the execution result of the calculation task;
The computing power network is used for: resolving the computational effort requirement to generate a corresponding computational effort task, establishing a hierarchical structure model matched with the computational effort task and resource nodes, matching the computational effort task with each resource node, and determining a target resource node for executing the computational effort task; constructing an environment container of the computing task, and storing an information file of the computing task according to the environment container and a preset storage mode;
the blockchain network is to: the management node sends the information file of the power calculation task to the target resource node; the target resource node configures a task environment to complete the computing task according to the information file; after the target resource node finishes the power calculation task, broadcasting the completion information of the power calculation task, and judging whether the completion information accords with a preset completion condition or not by the management node; the completion information comprises environment information when the task is completed; if yes, determining the finishing rewarding information of the target resource node.
9. A computing device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
The memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the method for processing a computing task of a blockchain-based computing network as in any of claims 1-7.
10. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the method for processing a computational task of a blockchain-based computational network of any of claims 1-7.
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