CN111275420B - Micro-computing power scheduling system oriented to heterogeneous environment - Google Patents

Micro-computing power scheduling system oriented to heterogeneous environment Download PDF

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CN111275420B
CN111275420B CN202010062054.6A CN202010062054A CN111275420B CN 111275420 B CN111275420 B CN 111275420B CN 202010062054 A CN202010062054 A CN 202010062054A CN 111275420 B CN111275420 B CN 111275420B
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王堃
孙雁飞
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Nanjing University of Posts and Telecommunications
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Abstract

A micro computational power scheduling system oriented to a heterogeneous environment comprises a node alliance constructed in a block chain network, wherein the node alliance comprises selected representative nodes; the rest nodes in the node alliance are connected with the representative node, and the representative node is in communication connection with the external blockchain network to perform data exchange; the representative node divides the calculation tasks according to the calculation resources of each node in the node alliance, dynamically adjusts the calculation task distribution of each node according to the use state of the calculation resources of each node, and then performs reward distribution according to the calculation amount contributed by each node. The system can reasonably organize and distribute tasks for the micro-computing power nodes, so that the micro-computing power nodes can more easily obtain benefits in the computing power competition of the block chain system, and the effective utilization of computing power resources is promoted.

Description

Micro-computing power scheduling system oriented to heterogeneous environment
Technical Field
The invention belongs to the technical field of block chains, and particularly relates to a micro-computing power scheduling system oriented to a heterogeneous environment.
Background
The core idea of the traditional block chain consensus mechanism is to ensure data consistency and consensus security by introducing the computational competition (Proof of workload of-word, poW) of distributed nodes. In the block chain system, each node (i.e. miner) jointly solves a SHA256 mathematical problem (i.e. mining) which is complex to solve but easy to verify based on the mutual competition of respective computer computing power, and the node which solves the problem the fastest obtains block accounting weight and the yield generated by the system automatically. A consensus mechanism based on computational competition is the current block chain mainstream solution, which has the feature of "Winner-takes-all". This feature results in monopoly revenue for high computational power nodes but no revenue for low computational power nodes, and thus low computational power nodes participate in the blockchain activity very rarely. Due to the characteristic of node computing power heterogeneity in large-scale distributed resource management, reasonable benefits of low-computing power nodes in the large-scale distributed resource management are difficult to obtain by adopting a traditional block chain consensus mechanism. It is necessary to solve these problems.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art, and provide a micro computing power scheduling system oriented to the heterogeneous environment, which can realize reasonable organization and task allocation of micro computing power nodes, so that the micro computing power nodes can more easily obtain benefits in computing power competition of a block chain system, and the effective utilization of computing power resources is promoted.
The invention provides a micro-computing power scheduling system oriented to a heterogeneous environment, which comprises a node alliance constructed in a block chain network, wherein the node alliance comprises a selected representative node; the rest nodes in the node alliance are connected with the representative node, and the representative node is in communication connection with the external blockchain network to perform data exchange; the representative node divides the calculation tasks according to the calculation resources of each node in the node alliance, dynamically adjusts the calculation task allocation of each node according to the use state of the calculation resources of each node, and then performs reward allocation according to the calculation amount contributed by each node.
As a further technical scheme of the invention, the node alliance consists of nodes within a geographically set distance or nodes within the same unit or organization.
Further, the representative node may extend or prune the nodes in the node federation.
Further, the representative node employs the recent contribution partition mechanism and the current contribution partition mechanism to perform reward distribution on the nodes in the node alliance.
Further, the near contribution partitioning mechanism is specifically: after the node alliance obtains the reward, the representative node divides the reward according to the calculated amount contributed by each node in the set time, and if any node exits the node alliance before division of the reward, the node alliance divides the reward according to the calculated amount contributed by the node.
Further, the node obtains the reward according to the recent contribution dividing mechanism as follows:
Figure BDA0002373478580000021
wherein i is the corresponding node, T 0 And T 1 Respectively calculating the starting time and the ending time of the node task; MHPS (t) is the computational power level of node i at t,
Figure BDA0002373478580000022
rewards earned for a federation of nodes.
Further, the current contribution partitioning mechanism is specifically: the representative node predicts the rewards that will be available at a set time in the future and then pre-pays the rewards based on the current computing power of each node in the federation of nodes.
Further, the node receives the following rewards based on the current contribution partitioning mechanism:
Figure BDA0002373478580000023
wherein i is the corresponding node, T 0 And T 1 Respectively calculating the starting time and the ending time of the node task; MHPS (t) is the computational power level of node i at t,
Figure BDA0002373478580000024
predicting node alliance to T for representative node 1 The prize earned at that moment.
According to the invention, by utilizing the calculation task division and the reward division, low-computation-force nodes can be effectively scheduled in a heterogeneous environment, and more resources are provided for distributed resource management based on block chains; reasonable organization and task distribution of the micro computing power nodes are realized, so that the micro computing power nodes can obtain benefits in the computing power competition of the block chain system more easily, and the effective utilization of computing power resources is promoted.
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FIG. 1 is a schematic diagram of the system of the present invention.
Detailed Description
In a distributed network, there are a large number of large servers and workgroup computers, as well as a vast number of personal computers, which are all computational resources in the distributed network; with the development of blockchain networks, these computing resources are being utilized in the computing competition of blockchain systems to obtain block accounting rights and system benefits, such as benefits of bitcoins and related digital virtual currencies, in a manner that provides proof of workload. In the block chain system, compared with the micro computational resources provided by a personal computer, a large server and a workgroup computer which have strong computational resources have obvious operation speed advantages, and because a consensus mechanism based on computational competition has the characteristic that winners have a general popularity, namely, firstly, a node dug to a mine obtains all benefits of the mine, and later, an ore machine node dug to the mine does not generate any benefits any more, so that the micro computational node hardly obtains the benefits in the computational competition.
In order to enable the micro-computing power nodes to be actively added into the block chain system, a large amount of idle computing power resources in the network are fully utilized, and the micro-computing power is scheduled by distributing proper rewards for the low-computing power nodes, wherein the rewards are obtained by the micro-computing power node alliance participating in external computing power competition.
Referring to fig. 1, the present embodiment provides a micro-computing scheduling system oriented to a heterogeneous environment, including a node federation constructed in a blockchain network, where the node federation includes a selected representative node; the rest nodes in the node alliance are connected with the representative node, and the representative node is in communication connection with the external blockchain network to perform data exchange; the representative node divides the calculation tasks according to the calculation resources of each node in the node alliance, dynamically adjusts the calculation task allocation of each node according to the use state of the calculation resources of each node, and then performs reward allocation according to the calculation amount contributed by each node.
A federation of nodes consists of nodes within a geographically set distance or within the same unit or organization.
The representative node may augment or tailor the nodes in the node federation. And adding the new node into the node alliance.
And the representative node adopts a recent contribution dividing mechanism and a current contribution dividing mechanism to carry out reward distribution on the nodes in the node alliance.
The near contribution dividing mechanism is specifically as follows: after the node alliance obtains the rewards, the representative node divides the rewards according to the calculated amount contributed by each node in the set time, and if any node exits the node alliance before dividing the rewards, the representative node divides the rewards according to the calculated amount contributed by the node.
The rewards obtained by the nodes according to the recent contribution division mechanism are as follows:
Figure BDA0002373478580000041
wherein i is the corresponding node, T 0 And T 1 Respectively calculating the starting time and the ending time of the node task; MHPS (t) is the computational power level of node i at t,
Figure BDA0002373478580000042
rewards earned for a federation of nodes.
The current contribution division mechanism is specifically as follows: the representative node predicts the rewards that can be obtained in a set time in the future and then pre-pays the rewards according to the current computing power of each node in the node union.
The node obtains the reward according to the current contribution and division mechanism as follows:
Figure BDA0002373478580000043
wherein i is the corresponding node, T 0 And T 1 Respectively calculating the starting time and the ending time of the node task; MHPS (t) is the computational power level of node i at t,
Figure BDA0002373478580000044
predicting node alliance-to-T for representative node 1 The prize earned at that moment.
When the computational competition of the node union lags behind other mining nodes in the blockchain network and does not reach the estimated reward value, namely
Figure BDA0002373478580000045
The partition method can still ensure the reward of the low-calculation-power nodes, and the income obtained by the low-calculation-power nodes is superior to the recent contribution partition; if the league exceeds the predicted reward, i.e.
Figure BDA0002373478580000046
The partitioning method partitions the excess rewards to the representative nodes as rewards for distributing computing tasks, and the low-computing-power nodes obtain lower income than the latest contribution partitioning.
By means of calculation task division and reward division, low-calculation-force nodes can be effectively scheduled in a heterogeneous environment, and more resources are provided for distributed resource management based on block chains; reasonable organization and task distribution of the micro computing power nodes are realized, so that the micro computing power nodes can obtain benefits in the computing power competition of the block chain system more easily, and the effective utilization of computing power resources is promoted.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are intended to further illustrate the principles of the invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention, which is intended to be protected by the appended claims. The scope of the invention is defined by the claims and their equivalents.

Claims (7)

1. The micro-computing power scheduling system oriented to the heterogeneous environment is characterized by comprising a node alliance constructed in a block chain network, wherein the node alliance comprises selected representative nodes; the rest nodes in the node alliance are connected with the representative node, and the representative node is in communication connection with an external blockchain network to perform data exchange; the representative node divides the calculation tasks according to the calculation resources of each node in the node alliance, dynamically adjusts the calculation task allocation of each node according to the use state of the calculation resources of each node, and then performs reward allocation according to the calculation amount contributed by each node;
the node federation consists of nodes within a geographically set distance or within the same unit or organization.
2. The system of claim 1, wherein the representative node can extend or reduce nodes in a node federation.
3. The system of claim 1, wherein the representative node employs a recent contribution partitioning mechanism and a current contribution partitioning mechanism to allocate rewards to nodes in the node federation.
4. The system according to claim 3, wherein the recent contribution partitioning mechanism is specifically: after the node alliance obtains the rewards, the representative node divides the rewards according to the calculated amount contributed by each node in the set time, and if any node exits the node alliance before dividing the rewards, the representative node divides the rewards according to the calculated amount contributed by the node.
5. The system according to claim 4, wherein the rewards obtained by the nodes according to the recent contribution partitioning mechanism are:
Figure FDA0003753171310000011
wherein i is the corresponding node, T 0 And T 1 Respectively calculating the starting time and the ending time of the node task; MHPS i (t) is the computational power level of node i at t,
Figure FDA0003753171310000013
rewards earned for a federation of nodes.
6. The system according to claim 3, wherein the current contribution partitioning mechanism is specifically: the representative node predicts the rewards that will be available at a set time in the future and then pre-pays the rewards based on the current computing power of each node in the federation of nodes.
7. The system according to claim 6, wherein the rewards obtained by the nodes according to the current contribution partitioning mechanism are:
Figure FDA0003753171310000012
wherein i is the corresponding node, T 0 And T 1 Respectively calculating the starting time and the ending time of the node task; MHPS i (t) is the computational power level of node i at t,
Figure FDA0003753171310000021
predicting node alliance-to-T for representative node 1 The prize earned at that moment.
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