CN110750355B - Control system, control method and device - Google Patents
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Abstract
The disclosure relates to a control system, a control method and a control device, wherein the control system of the embodiment of the disclosure comprises: the system comprises a plurality of first nodes, a plurality of second nodes and a block chain system, wherein each second node corresponds to a plurality of first nodes, and the first nodes corresponding to different second nodes are different from each other; the first node is used for submitting tasks to a second node corresponding to the first node; the second node is used for determining a first node for processing the task from the first nodes corresponding to the second node according to the received task and the characteristics of each first node corresponding to the second node when the task is received, and issuing the task to the determined first node so that the first node receiving the task processes the task and returns a task processing result; and the blockchain system is used for recording all the events of the interaction between the plurality of first nodes and the plurality of second nodes. Therefore, the task distribution can be more objective and fair, and the task distribution process is transparent.
Description
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a control system, a control method, and an apparatus.
Background
In a system composed of a plurality of nodes, the system may send a task generated by a certain node to other nodes in the system, which have better computational capability than the node, process the task by the other nodes, and return a task processing result (for example, a task generated by a node may be represented as a task for performing a security test on the node, or a task for performing a computation on data stored by the node, etc.). In the related art, the system developer selects other nodes for processing the task for the node, the subjective factor is large, and other nodes most suitable for the processing task may not be selected, so that resource mismatching or resource waste is caused.
Disclosure of Invention
In view of this, the present disclosure provides a control system, a control method and a device.
According to an aspect of the present disclosure, there is provided a control system including: the system comprises a plurality of first nodes, a plurality of second nodes and a block chain system, wherein each second node corresponds to a plurality of first nodes, and the first nodes corresponding to different second nodes are different from each other;
the first node is used for submitting tasks to a second node corresponding to the first node;
the second node is used for determining a first node for processing the task from the first nodes corresponding to the second node according to the received task and the characteristics of each first node corresponding to the second node when the task is received, and issuing the task to the determined first node so that the first node receiving the task processes the task and returns a task processing result;
the block chain system is used for recording all the events of mutual interaction between the plurality of first nodes and the plurality of second nodes.
In a possible implementation manner, the second node is further configured to determine whether the received task processing result is correct, and send an award to the first node that returns the correct task processing result.
In a possible implementation manner, determining, according to a received task and characteristics of each first node corresponding to a second node, a first node for processing the task from the first nodes corresponding to the second node includes:
determining a task characteristic vector corresponding to the task;
determining a node feature vector of each first node corresponding to the second node, wherein the node feature vector has the same dimension as the task feature vector;
aiming at each first node corresponding to the second node, determining the adaptability degree of the first node to the task according to the task feature vector and the node feature vector of the first node;
and taking the first node with the adaptive degree meeting a first preset condition as a first node for processing the task.
In a possible implementation manner, determining an adaptation degree of a first node to a task according to a task feature vector and a node feature vector of the first node includes:
a function of
Performing gradient descent processing as an objective function to obtain the minputWherein p isutFeature vector, p, being the degree of adaptation of the first node u to the task tutThe element in (1) is a variable of the function y when putFetch the minputIn time, the value of the function y can be minimized, ruIs a node feature vector of the first node u, qtThe task feature vector is a task t;
will internally accumulate the minput·qtAs the degree of adaptation of the first node u to the task t.
In one possible implementation, the node feature vector includes any one or more of the following feature dimensions:
bandwidth of the first node, computing resources of the first node, online duration of the first node, number of times the first node accepts tasks, number of times the first node is rewarded, average duration of processing tasks by the first node, network latency of the first node.
In one possible implementation, the task feature vector includes any one or more of the following feature dimensions:
bandwidth required by the task, computing resources required by the task, online time required by the task, and network delay.
In a possible implementation manner, determining, according to the received task and the characteristics of each first node corresponding to the second node, a first node for processing the task from the first nodes corresponding to the second node, further includes:
and taking the first node corresponding to the second node, wherein the number of times of receiving the task meets a second preset condition, as the first node for processing the task.
In one possible implementation form of the method,
if the second node judges that the received task processing result is correct, recording the first node submitting the task processing result as a legal node, and taking the legal node as an alternative object when the first node for processing the task is determined next time;
and if the second node judges that the received task processing result is incorrect, recording the first node submitting the task processing result as an illegal node, and not issuing the task to the illegal node.
In one possible implementation form of the method,
the second node is further configured to store proof of concept POC data;
when the first node needs to call the POC data of the corresponding second node, the first node sends a call instruction to the second node to call the POC data stored by the second node.
In one possible implementation, all events handled by the second nodes are exchanged between the second nodes.
According to another aspect of the present disclosure, there is provided a control method, which is used in the second node of the above control system, and includes:
when the second node receives the task, determining a first node for processing the task from the first nodes corresponding to the second node according to the received task and the characteristics of each first node corresponding to the second node;
the second node issues the task to the determined first node so that the first node receiving the task processes the task and returns a task processing result;
and the second node records all the events interacted between the second node and the plurality of first nodes corresponding to the second node through a block chain system.
According to another aspect of the present disclosure, there is provided a control apparatus including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform the above method.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the above-described method.
According to the control system in the above embodiment, when receiving a task submitted by a first node, a second node determines, according to the received task and characteristics of each first node corresponding to the second node, a first node for processing the task from the first nodes corresponding to the second node, and issues the task to the determined first node, so that the first node receiving the task processes the task and returns a task processing result, so that the first node most suitable for processing the task can be flexibly selected based on task content, which results in less resource mismatch or resource waste.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a schematic diagram illustrating a control system according to an exemplary embodiment.
FIG. 2 is a flow chart illustrating a control method according to an exemplary embodiment.
Fig. 3 is a functional block diagram of a second node shown according to an application example.
Fig. 4 to 6 are comparative diagrams illustrating the effect of allocating tasks and randomly allocating tasks by using the control method according to the embodiment of the present disclosure according to an application example.
FIG. 7 is a block diagram illustrating a control device according to an exemplary embodiment.
FIG. 8 is a block diagram illustrating a control device according to an exemplary embodiment.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
FIG. 1 is a schematic diagram illustrating a control system according to an exemplary embodiment. As shown in fig. 1: the control system may include: a plurality of first nodes 10, a plurality of second nodes 11 and a blockchain system, wherein each second node 11 corresponds to a plurality of first nodes 10, and the first nodes 10 corresponding to different second nodes 11 are different from each other;
the first node 10 is configured to submit a task to a second node 11 corresponding to the first node 10;
the second node 11 is configured to, when receiving a task, determine, according to the received task and characteristics of each first node 10 corresponding to the second node 11, a first node 10 used for processing the task from the first nodes 10 corresponding to the second node 11, and issue the task to the determined first node 10, so that the first node 10 receiving the task processes the task and returns a task processing result;
the blockchain system (not shown in the figure) is configured to record all events of the interaction between the plurality of first nodes 10 and the plurality of second nodes 11.
In the embodiment of the present disclosure, a control system may be constructed in a mode of fog computing, where the fog computing may be represented as a distributed computing infrastructure facing to the internet of things, in a system adopting the fog computing mode, computing capability and data analysis application of the system may be extended to a network edge device, and direct communication may be established between nodes in the fog computing system, so that each node in the fog computing system may analyze and manage data locally, and data transfer between each node has extremely low latency.
As an example of the present embodiment, as shown in fig. 1, the control system may include a first-layer network structure and a second-layer network structure, where the first-layer network structure may include a plurality of first nodes 10, the second-layer network structure may include a plurality of second nodes 11, the plurality of second nodes 11 may establish communication connections with each other, each second node 11 may correspond to a plurality of first nodes 10, each second node 11 may establish communication connections with the plurality of first nodes 10 corresponding to the second node 11, and the first nodes 10 corresponding to different second nodes 11 may be different from each other, that is, there is no intersection between the first nodes 10 corresponding to different second nodes 11. The control system may further include: a blockchain system (not shown).
The task may be a task generated by the first node 10, for example, the task generated by the first node 10 may be a security test performed on the first node 10; as another example, the task generated by the first node 10 may be a computational task. The characteristics of the first node 10 may include one or more of a bandwidth of the first node, a computing resource of the first node, an online time of the first node, a number of times the first node accepts tasks, a number of times the first node is rewarded, an average time for the first node to process tasks, a network delay of the first node.
When a task is generated, the first node 10 may submit the task to a second node 11 corresponding to the first node 10, and when the second node 11 receives the task, computing resources (an example of characteristics of the first node) required for processing the task may be estimated, where the computing resources may include any one or more of CPU resources, memory resources, hard disk resources, and network resources required for processing the task; then, the second node 11 may determine one or more first nodes 10 from the first nodes 10 corresponding to the second node 11 as the first nodes 10 for processing the task according to the computing resources required for processing the task and the computing resources of each first node 10 corresponding to the second node 11, where the determined computing resources of the one or more first nodes 10 are matched with the computing resources required for processing the task. Then, the second node 11 may issue the task to the determined one or more first nodes 10, so that the first node 10 receiving the task processes the task and returns a task processing result (for example, a safety test result performed on the first node 10 waiting for a safety test), where an event of interaction between each first node 10 and each second node 11 may be recorded in a blockchain system where the control system is located.
It should be noted that the security test on the node is only one example of the task of the present disclosure, and the computing resource of the first node is also only one example of the feature of the first node, and the present disclosure is not limited thereto.
According to the control system in the above embodiment, when receiving a task submitted by a first node, a second node determines, according to the received task and characteristics of each first node corresponding to the second node, a first node for processing the task from the first nodes corresponding to the second node, and issues the task to the determined first node, so that the first node receiving the task processes the task and returns a task processing result, so that the first node most suitable for processing the task can be flexibly selected based on task content, which results in less resource mismatch or resource waste.
In a possible implementation manner, the first node corresponding to the second node may be dynamically changed, for example, a first node corresponding to a certain second node may be converted into a first node corresponding to another second node. In a possible implementation manner, the first node may participate in task distribution candidate of the second node by establishing a communication connection with the second node, and the first node may also quit task distribution candidate of the second node by disconnecting the communication connection with the second node. Therefore, the control system of the embodiment of the disclosure has stronger openness and more flexible system architecture.
In a possible implementation manner, determining, according to the received task and the characteristics of each first node corresponding to the second node, a first node for processing the task from the first nodes corresponding to the second node may include:
determining a task characteristic vector corresponding to the task; determining a node feature vector of each first node corresponding to the second node, wherein the node feature vector has the same dimension as the task feature vector; aiming at each first node corresponding to the second node, determining the adaptability degree of the first node to the task according to the task feature vector and the node feature vector of the first node; and taking the first node with the adaptive degree meeting a first preset condition as a first node for processing the task.
In one possible implementation, a task feature vector of a task may be represented as a set composed of a plurality of feature dimensions of the task, and the task feature vector may include any one or more of the following feature dimensions: the bandwidth required by the task (where the size of the bandwidth required by the processing task may be reflected by a numerical value, for example, multiple bandwidth size sections may be preset, each section corresponds to one score, and the score corresponding to the section to which the size of the bandwidth required by the processing task belongs is taken as the bandwidth required by the processing task), the computing resource required by the task (where the size of the computing resource required by the processing task may be reflected by a numerical value, for example, multiple computing resource numerical sections may be preset, each section corresponds to one score, and the score corresponding to the section to which the size of the bandwidth required by the processing task belongs is taken as the bandwidth required by the processing task), the online time required by the task, and the network delay. It should be noted that, other applicable factors may be selected as the feature dimension of the task feature vector as needed, which is not limited in the embodiment of the present disclosure.
In one possible implementation manner, the node feature vector of the first node may be represented as a set composed of a plurality of feature dimensions of the first node, and the node feature vector of the first node may include any one or more of the following feature dimensions: the bandwidth of the first node (where the bandwidth of the first node may be reflected by a numerical value, for example, a plurality of bandwidth numerical intervals may be preset, each interval corresponds to a score, and the score corresponding to the interval to which the bandwidth of the first node belongs is used as the bandwidth of the first node), the computing resource of the first node (where the computing resource of the first node may be reflected by a numerical value, for example, a plurality of computing resource numerical intervals may be preset, each interval corresponds to a score, and the score corresponding to the interval to which the computing resource of the first node belongs is used as the computing resource of the first node), the online duration of the first node, the number of times that the first node receives tasks, the number of times that the first node is rewarded, the average duration of processing tasks of the first node, and the network delay of the first node. It should be noted that, other applicable factors may be selected as the feature dimension of the node feature vector as needed, which is not limited in the embodiment of the present disclosure.
For example, if the task received by the second node is task t, the second node may determine that the task feature vector corresponding to task t is qt＝{t1,t2,t3,t4,t5,t6Where t is1May be a value representing the amount of bandwidth required to process a task t, t2May be a value representing the size of the memory resource required to process a task t, t3May be a value representing the size of the hard disk resource required to process a task t, t4May be a value, t, representing the size of the CPU resource required to process a task t5May be a value representing the online time period required to process a task t, t6May be a value representing the average network delay length of the network system in which the node is located.
The second node may determine a node feature vector for each first node to which the second node corresponds. For example, the second node may obtain and update the node feature vector of the first node corresponding to the second node at a preset frequency; for another example, the second node may also determine, when receiving the task, a current node feature vector of each first node corresponding to the second node.
For example, the second node may determine that the node feature vector of the first node u may be ru＝{r1,r2,r3,r4,r5,r6Wherein r is1May be a value, r, representing the bandwidth size of the first node u2May be a value, r, representing the size of the memory resource of the first node u3May be a value, r, representing the size of the hard disk resource of the first node u4May be a value, r, representing the CPU resource size of the first node u5May be a value, r, representing the online duration of the first node u6May be a value representing the length of the network delay of the network in which the first node u is located.
Then, the second node may determine, for each first node corresponding to the second node, an adaptation degree of the first node to the task according to the task feature vector and the node feature vector of the first node, for example, the second node may apply a function to the task
Performing gradient descent processing as an objective function to obtain the minputAnd internally accumulating the minput·qtAs the degree of adaptation of the first node u to the task t. Wherein p isutFeature vector, p, being the degree of adaptation of the first node u to the task tutThe element in (1) is a variable of the function y when putFetch the minputIn time, the value of the function y can be minimized, ruIs a node feature vector of the first node u, qtIs the task feature vector of task t. The second node may take the first node having the degree of adaptation greater than a preset threshold (an example of a first preset condition) as the first node processing the task. This facilitates a more accurate determination of the section for which the computational power is more closely matched to the task to be processedAnd (4) point. It should be noted that, an applicable gradient descent algorithm may be selected according to needs, and the specific form of the gradient descent algorithm is not limited in the embodiments of the present disclosure.
In addition, the first preset condition may be a plurality of values, may also be one interval value, and may also be a ranking of the adaptation degree, and the specific form of the first preset condition is not limited in the embodiment of the present disclosure.
Therefore, the content-based recommendation algorithm can be formed based on the characteristics of the tasks to be processed and the computing power of each first node corresponding to the second node, so that a proper node processing task can be selected according to different tasks, and the probability of the occurrence of the phenomena that the task processing fails due to the fact that the node cannot bear the task due to insufficient computing power, the resource waste is caused due to the fact that the computing power of the node is excessive and the like is effectively reduced.
In a possible implementation manner, the first node corresponding to the second node, which receives the task for a number of times that meets a second preset condition, may also be used as the first node for processing the task.
For example, the second node may determine the number of times that each first node corresponding to the second node receives the task, and may use the first node that receives the task whose number is 10 bits from the last as the first node that processes the task. Therefore, the probability of receiving the tasks by the first node can be more equal, the deficiency of the recommendation algorithm can be made up, the fairness of task allocation is further improved, the participation sense of the nodes with weak computing resources is improved, and the task distribution and the node resource distribution tend to be in a positive correlation.
In a possible implementation manner, the second node is further configured to determine whether the received task processing result is correct, and send an award to the first node that returns the correct task processing result. In a possible implementation manner, if the second node issues tasks to the plurality of first nodes and receives task processing results returned by the plurality of first nodes, the second node may determine whether the number of the same task processing results exceeds half of the total number of the task processing results, and if the second node determines that the number of the same task processing results exceeds half (or may account for, for example, 80% or 90% of the total number), the second node may determine that the more than half task processing results are correct, determine that other different task processing results are incorrect, and send rewards to the first nodes returning correct task processing results; if the second node determines that the number of the identical task processing results is less than half, the second node may determine that all of the plurality of first nodes return wrong task processing results. For example, if the second node issues tasks to 20 first nodes and receives task processing results returned by the 20 first nodes, and the second node determines that 15 task processing results are equal to each other and more than half of the task processing results, the second node may determine that the 15 identical task processing results are correct, determine that the remaining 5 task processing results are incorrect, and send an award to the first node that returns the 15 task processing results. For example, if the second node issues tasks to 20 first nodes and receives task processing results returned by the 20 first nodes, and the second node determines that 3 task processing results are equal to each other and do not exceed half of the task processing results, the second node may determine that all the 20 first nodes return wrong task processing results. Therefore, the enthusiasm of correctly processing the task nodes can be enhanced, and the nodes with stronger computing power can be stimulated to continuously participate in the processing task.
In a possible implementation manner, if the second node determines that the received task processing result is correct, the first node submitting the task processing result may be recorded as a legal node, and the legal node is still used as an alternative object when the first node for processing the task is determined next time; if the second node judges that the received task processing result is incorrect, the first node submitting the task processing result can be recorded as an illegal node, and the task is not issued to the illegal node. Therefore, nodes with insufficient computing power or malicious nodes can be effectively removed, and the task can be distributed to the more appropriate first node for processing by the second node.
In one possible implementation, the second node is further configured to store proof of concept POC data;
when the first node needs to call the POC data of the corresponding second node, the first node sends a call instruction to the second node to call the POC data stored by the second node.
In one possible implementation, POC (Proof of concept, which may also be referred to as Proof of concept), may be represented as a short and incomplete implementation to a specific assumption to prove its feasibility, demonstrating its principles, with the purpose of verifying some concepts or theories. For example, if the task received by the second node is to perform security testing on the operating system of a certain first node, the second node may pre-store POC data related to the security testing, and the first node determined by the second node as the processing task may acquire the POC data from the second node and perform security testing on the first node to be tested according to the acquired POC data. Therefore, the second node can provide basic support for the control system to store the POC, and the first node participating in the processing task does not need to store the POC data in advance, so that the redundancy degree of the control system is effectively reduced.
In one possible implementation, all events handled by the second nodes are exchanged between the second nodes. Therefore, the information of the first node can be updated in real time by the second node, and basic support is provided for intelligent chain operation.
FIG. 2 is a flow chart illustrating a control method according to an exemplary embodiment. As shown in fig. 2, the method may include:
200, when a second node receives a task, determining a first node for processing the task from first nodes corresponding to the second node according to the received task and the characteristics of each first node corresponding to the second node;
With regard to the method in the above-described embodiment, the specific contents of the respective steps have been described in detail in the embodiment related to the control system, and will not be elaborated herein.
Due to the example
As shown in fig. 1, the control system may include a first-layer network structure and a second-layer network structure, wherein the first-layer network structure may include a plurality of first nodes (also referred to as common nodes), the second-layer network structure may include a plurality of second nodes (also referred to as fog nodes), each of the second nodes may correspond to a plurality of first nodes, and the first nodes corresponding to different second nodes are different from each other.
Fig. 3 is a functional block diagram of a second node shown according to an application example. As shown in fig. 3, each second node may include a data preprocessing module 31, a node selection module 32, and a node reward punishment module 33, where the data preprocessing module may include a node preprocessing module 311 and a task preprocessing module 312.
The node preprocessing module 311 may collect and update node feature information of the first node corresponding to the second node at a preset frequency during the system operation to form a node feature vector of each first node, where the node feature information of the first node may include: the bandwidth value of the node, the computing resource of the node, the online time of the node, the times of receiving tasks by the node, the times of being rewarded by the node, the average time of processing tasks by the node, the network delay of the node and the like.
The task pre-processing module 312 may be configured to determine feature information of a task received by the second node, form a task feature vector for the task,
the second nodes may share information, for example, the information stored in each second node may be synchronized at a preset frequency between the second nodes. When a certain node submits a task to an adjacent second node, the second node selects a proper node according to a node selection algorithm. If the task report submitted by the first node is judged to be incorrect, the node is considered to have improper behavior, and the second node can record the mainboard serial number and the hard disk serial number of the first node, add the mainboard serial number and the hard disk serial number into a blacklist and no longer provide service or distribute tasks for the first node.
As shown in fig. 3, each second node may include a data preprocessing module 31, a node selection module 32, and a node reward and punishment module 33, where the data preprocessing module may include a node preprocessing module 311 and a task preprocessing module 312, and the node preprocessing module 311 may be configured to extract feature information of each first node corresponding to the second node to form a feature vector corresponding to each first node. The node preprocessing module 311 may be configured to extract a feature index of each first node corresponding to the second node, and form a feature vector corresponding to each first node.
The task preprocessing module 312 may be configured to extract feature information of the task received by the second node to form a task feature vector.
The node selection module 32 may include a recommendation selection module 321 and a random selection module 322:
the recommendation selecting module 321 may select a function according to each first node corresponding to the second node
Performing gradient descent processing as an objective function to obtain the minputAnd internally accumulating the minput·qtAs the degree of adaptation of the first node u to the task t. Wherein p isutFeature vector, p, being the degree of adaptation of the first node u to the task tutThe element in (1) is a variable of the function y when putFetch the minputIn time, the value of the function y can be minimized, ruIs a node feature vector of the first node u, qtIs the task feature vector of task t. The second node may take a first node with the adaptation degree ranked 21 top (an example of a first preset condition) as a first node to process the task.
The node reward and punishment module 33 may be configured to determine whether a task processing result (also referred to as a task report) submitted by the first node is correct, and select the first 21 nodes that submit the correct task report earliest to be rewarded by the node reward and punishment module to accumulate an integral for the other nodes that submit the correct task report. The node reward and punishment module 33 may also be configured to determine and record a motherboard serial number and a hard disk serial number of the first node that returns the error task processing result, add the motherboard serial number and the hard disk serial number to the blacklist, and no longer provide service or allocate a task to the first node that is pulled into the blacklist.
In addition, the second node may pre-store POC data, from which the first node determined by the second node to be a processing task may obtain POC data when it is needed.
Fig. 4 to 6 are comparative diagrams illustrating the effect of allocating tasks and randomly allocating tasks by using the control method according to the embodiment of the present disclosure according to an application example. In order to verify the reasonableness of the algorithm, two groups of control experiments are designed, wherein one group of experiments adopt a random mode to distribute tasks, and the other group of experiments adopt the control system disclosed by the invention to distribute tasks. And setting each second node to manage 1000 first nodes, wherein 30 first nodes are selected for processing tasks in each round of task, and the second node can reward the first 21 first nodes which submit correct task reports earliest. The computing power of each first node can be scored according to a computing power dividing standard, the higher the computing power of the first node is, the higher the score is, and the computing power scores of the first nodes are preset to be in normal distribution. Through 100 rounds of task distribution, the number of the first nodes selected in each round of task distribution and the number of the first nodes rewarded can be counted, and the times of the first nodes with different computing power scores are counted.
As shown in fig. 4, the coverage of the first node selected by the control system to allocate the task according to the present disclosure is wider than the coverage of the first node selected by allocating the task in a random manner, so that the control system according to the embodiment of the present disclosure may have a wider node selection range; as shown in fig. 5, the number of the first nodes rewarded for allocating the tasks in a random manner is much smaller than the number of the first nodes rewarded for allocating the tasks by using the control system of the present disclosure, which indicates that the embodiment of the present disclosure can reward the first nodes that correctly complete the tasks more actively, so that the enthusiasm of the first nodes to participate in completing the tasks can be better mobilized; as shown in fig. 6, when the tasks are distributed in a random manner, the first node with higher computing power is selected to process the tasks with higher chance, and the first node with lower computing power is selected with little or no chance, in contrast, when the control system distributes the tasks according to the embodiment of the present disclosure, the number of times that each node with a computing power score is selected is close to the normal distribution, and is close to the computing power score distribution of the first node.
Therefore, in the control system of the embodiment of the disclosure, the coverage of each round of node selection is more balanced, the overall participation sense of the nodes is improved, small resource nodes can be encouraged to be merged into the system, the resources of large resource nodes are fully utilized, and the node resources are effectively prevented from being abused and vacant.
FIG. 7 is a block diagram illustrating a control device according to an exemplary embodiment. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.
Referring to fig. 7, the apparatus 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operations at the apparatus 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The multimedia component 808 includes a screen that provides an output interface between the device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed status of the device 800, the relative positioning of components, such as a display and keypad of the device 800, the sensor assembly 814 may also detect a change in the position of the device 800 or a component of the device 800, the presence or absence of user contact with the device 800, the orientation or acceleration/deceleration of the device 800, and a change in the temperature of the device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium, such as the memory 804, is also provided that includes computer program instructions executable by the processor 820 of the device 800 to perform the above-described methods.
FIG. 8 is a block diagram illustrating a control device according to an exemplary embodiment. For example, the apparatus 1900 may be provided as a server. Referring to FIG. 8, the device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by the processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The device 1900 may also include a power component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to a network, and an input/output (I/O) interface 1958. The device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the apparatus 1900 to perform the above-described methods.
The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: 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 Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
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 instructions, which comprises one or more executable instructions for implementing the specified logical function(s). 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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (11)
1. A control system, comprising: the system comprises a plurality of first nodes, a plurality of second nodes and a block chain system, wherein each second node corresponds to a plurality of first nodes, and the first nodes corresponding to different second nodes are different from each other;
the first node is used for submitting tasks to a second node corresponding to the first node;
the second node is used for determining a first node for processing the task from the first nodes corresponding to the second node according to the received task and the characteristics of each first node corresponding to the second node when the task is received, and issuing the task to the determined first node so that the first node receiving the task processes the task and returns a task processing result;
the block chain system is used for recording all the events of mutual interaction between the plurality of first nodes and the plurality of second nodes;
determining a first node for processing the task from the first nodes corresponding to the second node according to the received task and the characteristics of each first node corresponding to the second node, comprising:
determining a task characteristic vector corresponding to the task;
determining a node feature vector of each first node corresponding to the second node, wherein the node feature vector has the same dimension as the task feature vector;
aiming at each first node corresponding to the second node, determining the adaptability degree of the first node to the task according to the task feature vector and the node feature vector of the first node;
taking a first node with the adaptation degree meeting a first preset condition as a first node for processing the task;
determining the adaptability degree of the first node to the task according to the task feature vector and the node feature vector of the first node, wherein the method comprises the following steps:
a function of
Performing gradient descent processing as an objective function to obtain the minputWherein p isutFeature vector, p, being the degree of adaptation of the first node u to the task tutThe element in (1) is a variable of the function y whenputFetch the minputIn time, the value of the function y can be minimized, ruIs a node feature vector of the first node u, qtThe task feature vector is a task t;
will internally accumulate the minput·qtAs the degree of adaptation of the first node u to the task t.
2. The control system of claim 1,
and the second node is also used for judging whether the received task processing result is correct or not and sending rewards to the first node returning the correct task processing result.
3. The control system of claim 1, wherein the node feature vector comprises any one or more of the following feature dimensions:
bandwidth of the first node, computing resources of the first node, online duration of the first node, number of times the first node accepts tasks, number of times the first node is rewarded, average duration of processing tasks by the first node, network latency of the first node.
4. The control system of claim 1, wherein the task feature vector comprises any one or more of the following feature dimensions:
bandwidth required by the task, computing resources required by the task, online time required by the task, and network delay.
5. The control system according to claim 1, wherein the first node for processing the task is determined from the first nodes corresponding to the second node according to the received task and the characteristics of each of the first nodes corresponding to the second node, further comprising:
and taking the first node corresponding to the second node, wherein the number of times of receiving the task meets a second preset condition, as the first node for processing the task.
6. The control system of claim 1,
if the second node judges that the received task processing result is correct, recording the first node submitting the task processing result as a legal node, and taking the legal node as an alternative object when the first node for processing the task is determined next time;
and if the second node judges that the received task processing result is incorrect, recording the first node submitting the task processing result as an illegal node, and not issuing the task to the illegal node.
7. The control system of claim 1,
the second node is further configured to store proof of concept POC data;
when the first node needs to call the POC data of the corresponding second node, the first node sends a call instruction to the second node to call the POC data stored by the second node.
8. The control system of claim 1, wherein all events handled by each second node are interchanged between each second node.
9. A control method for use in a second node according to any of claims 1 to 8, the method comprising:
when the second node receives the task, determining a first node for processing the task from the first nodes corresponding to the second node according to the received task and the characteristics of each first node corresponding to the second node;
the second node issues the task to the determined first node so that the first node receiving the task processes the task and returns a task processing result;
and the second node records all the events interacted between the second node and the plurality of first nodes corresponding to the second node through a block chain system.
10. A control device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
the method of claim 9 is performed.
11. A non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the method of claim 9.
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