CN113379416A - Method and system for realizing similar biological groups with consistent memory but different behaviors - Google Patents
Method and system for realizing similar biological groups with consistent memory but different behaviors Download PDFInfo
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Abstract
The invention discloses a similar biological group method for realizing memory consistency but different behaviors, which comprises the steps of establishing a defined behavior empty transaction, filling transaction contents, signing and submitting to a block chain; processing the transaction, and storing the behaviors after all checks are passed; performing an action, checking the action type; execution is done according to different types of completion behaviors. The invention also provides a biology group-like system for realizing memory consistency but different behaviors, which comprises a consensus manager, a data manager and a behavior manager, thereby realizing the function of personalized behaviors on the premise of data consistency and solving the problem of systematic risks caused by behavior consistency due to requirement information consistency.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to a method and a system for realizing similar biological groups with consistent memory but different behaviors.
Background
In the future of continuous and rapid development of informatization, the isolation barrier of information becomes weaker and weaker until all people have completely consistent information. Information is the main reason for driving people to do behaviors, and when all people have consistent information, the convergence of human behaviors is also caused. In the current environment with highly centralized information monopoly, these central authorities often use the information monopoly advantage to drive people to perform certain behaviors, and once the ability is not well mastered or is utilized maliciously, the central authorities may cause bad influence or even cause social retreat. For example, the central authority may give a piece of information to a group and then give another group information in full opposition, which, through long lasting guidance and stacking of information, would result in a conflict between the two groups in the desired aspect of the authority. As another example, assuming a honest organization that advocates and propagates what they really believe is beneficial to society, society will gradually conform to the trends desired by the organization over the long-term persistence under the stack and guidance of this information, but once the environment of the whole society changes, the ability to resist the risks in the societies that tend to be consistent will approach zero, which may lead to a systematic risk or even breakdown of the society, resulting in a retirement of the society. However, if there is no central organization to concentrate monopolizing information and make centralized guidance, the information flooding causes the power consumption of social development to be in the inner consumption, and the social development is difficult to continue. Therefore, how to realize that information can be intensively guided and cannot be maliciously utilized, participants can also perform personalized behaviors, and the different behaviors cannot cause internal consumption, so that a social infrastructure which is uniform, ordered, personalized, risk-resistant and continuously developed is provided for the society, and the problem which needs to be solved urgently is provided.
Disclosure of Invention
The invention aims to provide a method and a system for realizing the biology-like group with consistent memory but different behaviors, and designs the concept of the biology-like group, wherein the core thought of the method is to put data of all participants on a block chain, separate consensus data and service data, and each node on the block chain has different algorithms, so that each node can implement different behaviors on the basis of the same data, thereby realizing the function of personalized behaviors on the premise of data consistency and solving the problem of systematic risks caused by behavior consistency in order to require information consistency.
A method and system for achieving a consistent memory but behaviourally diverse biolike population, the method comprising:
s1, creating a defined behavior null transaction, filling in behavior content, signing and submitting to a block chain;
s2, starting to process the transaction, and storing the behavior to the local after all the checks are passed;
s3, starting to perform an action and checking the action type;
and S4, executing behaviors according to different behavior types.
Further, the process of processing the transaction in step S2 includes:
s21, extracting transaction content;
s22, verifying the validity of the transaction, and discarding the transaction if the validity of the transaction is not correct;
s23, checking whether the behavior algorithm exists or not, and if so, discarding the transaction;
and S24, analyzing algorithm.
Further, the process of executing the action in step S4 includes:
s41, if the behavior belongs to the consensus behavior, extracting a behavior algorithm defined by the transaction, and if the behavior belongs to the personalized behavior, extracting a local personalized behavior algorithm;
s42, acquiring input data required by the algorithm;
s43, transmitting the input into an algorithm for execution;
and S44, obtaining an execution result, and submitting the execution result to the block chain if the execution result is the consensus behavior.
The invention also provides a biology-like group system for realizing memory consistency and different behaviors on the basis of the biology-like group method for realizing memory consistency and different behaviors, which comprises
A consensus manager: a consensus mechanism for managing the current network;
a data manager: the system is used for managing traditional block chain data and formula data and personalized data at the same time;
a behavior manager: for managing the behavior of the nodes.
The system creates a defined behavior null transaction through a behavior manager, fills in transaction content, signs and submits the transaction content to a block chain, processes the transaction, passes all inspection and analysis algorithms, the data manager stores the behavior to the local, the behavior manager starts to perform a behavior, inspects the behavior type, executes the behavior by a consensus manager or a behavior manager, the data manager obtains an execution result, and the consensus manager, the data manager and the behavior manager are in cross mesh connection with each other and can access data mutually.
Further, the consensus manager comprises:
a rule management module: the consensus rules are used for defining and managing the current network support;
a consensus execution module: the rule management module is used for executing the rule according to a formula rule defined in the rule management module;
an extended consistent module: the method is used for bringing the extension functions and the transactions defined in the extension manager into a consensus range when the extension manager is used in the current network.
Further, the data manager includes:
a data storage module: the system is used for storing consensus data and personalized data in the current network environment and providing a basis for later inquiry;
a data query module: data for providing a specific condition;
a data interface module: for interfacing with external services.
Further, the behavior manager includes:
a behavior definition module: algorithms for defining the types of various behaviors, and the types of behaviors;
a behavior execution module: and the system is used for executing the algorithm behind the behavior according to the definition of the behavior type, providing data input for the execution of the algorithm and collecting feedback execution results after the execution is finished.
Compared with the prior art, the invention has the following advantages:
(1) the invention realizes the function of personalized behavior on the premise of ensuring consistent data, thereby leading the information to be intensively guided and not to be maliciously utilized;
(2) the invention solves the problem of systematic risk caused by consistent behaviors due to consistent information requirements, and enhances the risk resistance of the society;
(3) the personalized behavior in the invention can be modified or upgraded even in the actual operation process of the block chain, thereby solving the problem of service development delay caused by the unchangeable consensus mechanism of the block chain in the actual application.
Drawings
FIG. 1 is a schematic flow chart of the method for achieving memory consistency but different behavior of the biology-like groups according to the invention;
FIG. 2 is a flow diagram of a process for processing transactions according to the present invention;
FIG. 3 is a flow diagram of the execution behavior process of the present invention;
FIG. 4 is a schematic diagram of the components of the biobased system of the present invention for achieving memory consistency but varying behavior;
FIG. 5 is a schematic diagram of the consensus manager of the present invention;
FIG. 6 is a schematic diagram of the data manager according to the present invention;
FIG. 7 is a schematic diagram of the behavior manager according to the present invention;
wherein: 100 a consensus manager; 200 a data manager; 300 a behavior manager; 101 a rule management module; 102 a consensus execution module; 103 extending the consistent module; 201 a data storage module; 202 a data query module; 203 a data interface module; 301 a behavior definition module; 302 behavior execution module
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples. It should be noted that the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In the current environment with highly concentrated information, a central mechanism often guides people to perform certain behaviors by using the information monopoly advantage, but the risk resistance of the society is greatly weakened under the social collective condition that the behaviors tend to be consistent, but if no central mechanism guides the monopoly information, the society is difficult to develop well due to information inundation, so that the invention provides a similar biological group method for realizing the consistency of memory and different behaviors on the premise of ensuring the action of personalized behaviors, and in order to realize the method, the method specifically comprises the following technical steps:
the method comprises two main links, wherein the first is to define a behavior, create a null transaction of the defined behavior and fill in the behavior content, and store the null transaction of the defined behavior to the local after all checks are passed, and the second is to execute the behavior, check the behavior type and execute the behavior according to different types to obtain an execution result, as shown in fig. 1:
s1, creating a defined behavior null transaction and filling in behavior content, including a behavior name and a behavior algorithm, signing and then submitting to a block chain;
s2, starting to process the transaction, and storing the behavior to the local after all the checks are passed;
s3, starting to perform an action and checking the action type;
and S4, executing behaviors according to different behavior types.
As shown in fig. 2, in the present embodiment, the process of processing the transaction described in step S2 includes:
s21, extracting transaction content;
s22, verifying the validity of the transaction, and discarding the transaction if the validity of the transaction is not correct;
s23, checking whether the behavior algorithm exists or not, and if so, discarding the transaction;
and S24, analyzing algorithm.
As shown in fig. 3, in the present embodiment, the process of performing actions described in step S4 includes:
s41, if the behavior belongs to the consensus behavior, extracting a behavior algorithm defined by the transaction, and if the behavior belongs to the personalized behavior, extracting a local personalized behavior algorithm;
s42, acquiring input data required by the algorithm;
s43, transmitting the input into an algorithm for execution;
and S44, obtaining an execution result, and submitting the execution result to the block chain if the execution result is the consensus behavior.
As shown in fig. 4, the present invention also provides a biobased system with consistent memory but different behaviors, which comprises the following components:
the consensus manager 100: the consensus mechanism for managing the current network is the basis for the nodes to join the whole network and the most basic behavior basis for the nodes to participate in the network. In the invention, the consensus manager adds consistency extension support about external behavior constraint on the basis of the consensus manager of the traditional block chain, when some external behavior requirements are required to be consistent for all participants, the requirements of the behavior are added into consensus through the consensus manager, if the requirements of individual participants are required to participate in the consensus, the consensus manager is removed from the consensus manager, and the specific addition and removal are realized by specific upper-layer applications. Here, the specific part of the consensus rule is also defined in advance by the provider of the upper layer application;
the data manager 200: the system comprises a common identification data management module, a common identification data management module and a data processing module, wherein the common identification data management module is used for managing traditional blockchain data and also managing common identification data and personalized data, the common identification data is the basis for carrying out a common identification protocol and belongs to one part of the traditional blockchain data in some cases, and the common identification data is used as independent common identification data to be processed and stored in a common identification expansion behavior; for personalized data, the data is often generated by node behaviors, the data is often unrelated to a consensus mechanism but is the basis for driving the node behaviors, the data is input into a node behavior algorithm, under different upper-layer applications and different intelligence requirements, the managed data are different in scale, and for logic processing which can be completed by a common inspection algorithm, the data volume is far smaller than that of a block chain, but when the data at the artificial intelligence level is required, data storage in a larger scale is realized;
the behavior manager 300: the method is used for managing the behaviors of the nodes, wherein the behaviors comprise consensus behaviors and personalized behaviors, the consensus behaviors are used for driving a consensus manager to join a network and reach agreement with the network on data, in the personalized behaviors, personalized calculation is carried out on the data provided by the data manager, the behavior of the user is obtained, and meanwhile, the result of the behavior still meets the most basic requirement of a consensus mechanism. Because the personalized behavior does not belong to a part of the consensus mechanism, the block chain can be randomly upgraded or modified even in the actual operation process, so that the problem that the service development of the block chain cannot follow up due to the immutable consensus mechanism in the actual application is solved.
The specific workflow of the system comprises the following steps:
the system creates a defined behavior null transaction through the behavior manager 300, signs and submits the transaction to a block chain after filling transaction content, processes the transaction, all checks pass through a post-analysis algorithm, the data manager 200 saves the behavior to the local, the behavior manager 300 starts to perform a behavior, checks the type of the behavior, and executes the behavior by the consensus manager 100 or the behavior manager 300, the data manager 200 obtains an execution result, and the consensus manager 100, the data manager 200 and the behavior manager 300 are connected in a cross-mesh manner, so that data access can be performed mutually.
As shown in fig. 5, preferably, the consensus manager 100 comprises:
the rule management module 101: the consensus rule is used for defining and managing the current network support, and at least one rule needs to be provided for realizing the consensus rule, wherein the rule is defined in the form of codes before the network is online;
the consensus execution module 102: the rule management module is used for executing according to the consensus rule defined in the rule management module, and according to the difference of upper-layer services, the rule may be defined as a formula or an unchangeable rule written by a code initially;
the extended conformance module 103: when the extension manager is used in the current network, the extension functions and transactions defined in the extension manager are brought into a consensus scope, and the consensus at this time does not care about what specific extension functions and services are, but only whether the input and output of the extension are consistent with other nodes. For supporting the constraint of behaviors in the behavior manager that require global consistency through consensus.
As shown in fig. 6, preferably, the data manager 200 includes:
the data storage module 201: the system is used for storing consensus data and personalized data in the current network environment and providing a basis for later inquiry. In data storage, a storage mode consistent with block chain data is used when the data size is small, and an external memory can be accessed when the data is stored in a large scale;
the data query module 202: the data comprises block chain related data and node personalized data, and when the node provides the personalized data, a query method for providing the data is required;
the data interface module 203: the data query module is used for receiving external services, submitting requests through the interface module when data needs to be provided externally, organizing and extracting the data through the data query module, and returning the data to a data requester, and the data interface module is an entrance for other modules to use the data.
As shown in fig. 7, preferably, the behavior manager 300 includes:
the behavior definition module 301: the algorithm used for defining various types of behaviors and the type behaviors, the algorithm is initially provided by a developer, and the behaviors of the non-consensus part can be dynamically defined at a later stage;
the behavior execution module 302: the method is used for executing the algorithm behind the behavior according to the definition of the behavior type, providing data input for the execution of the algorithm and collecting feedback execution results after the execution is finished.
Compared with the information monopolizing method of the existing central institution, the invention designs the concept of 'biology-like group', puts the data of all participants on the block chain as the basis of the memory of the participants, and separates the consensus data and the business data, thereby leading each node on the block chain to realize different behaviors on the premise of the same data basis, solving the problem of systematic risk caused by behavior consistency due to information consistency, and simultaneously avoiding extra internal consumption. It should be noted that although the present invention is described with respect to a blockchain scenario, the same approach can be applied to all scenarios where it is desirable to maintain participant personalization. Some of the ideas can also be applied to other business scenarios with the same principle.
The above-mentioned embodiments are only preferred embodiments of the present invention, and do not limit the technical scope of the present invention, so that the changes and modifications made by the claims and the specification of the present invention should fall within the scope of the present invention.
Claims (7)
1. A method for achieving a consistent memory but behaviourally diverse biological population, the method comprising:
s1, creating a defined behavior null transaction, filling in behavior content, signing and submitting to a block chain;
s2, starting to process the transaction, and storing the behavior to the local after all the checks are passed;
s3, starting to perform an action and checking the action type;
and S4, executing behaviors according to different behavior types.
2. The method of claim 1, wherein the processing of the transaction in step S2 comprises:
s21, extracting transaction content;
s22, verifying the validity of the transaction, and discarding the transaction if the validity of the transaction is not correct;
s23, checking whether the behavior algorithm exists or not, and if so, discarding the transaction;
and S24, analyzing algorithm.
3. The method of claim 1, wherein the step of performing actions in step S4 comprises:
s41, if the behavior belongs to the consensus behavior, extracting a behavior algorithm defined by the transaction, and if the behavior belongs to the personalized behavior, extracting a local personalized behavior algorithm;
s42, acquiring input data required by the algorithm;
s43, transmitting the input into an algorithm for execution;
and S44, obtaining an execution result, and submitting the execution result to the block chain if the execution result is the consensus behavior.
4. A system for achieving memory consistency but behavioural diversity in a biolike population, said system comprising
A consensus manager: a consensus mechanism for managing the current network;
a data manager: the system is used for managing traditional block chain data and formula data and personalized data at the same time;
a behavior manager: for managing the behavior of the nodes.
The system creates a defined behavior null transaction through a behavior manager, fills in transaction content, signs and submits the transaction content to a block chain, processes the transaction, passes all inspection and analysis algorithms, the data manager stores the behavior to the local, the behavior manager starts to perform a behavior, inspects the behavior type, executes the behavior by a consensus manager or a behavior manager, the data manager obtains an execution result, and the consensus manager, the data manager and the behavior manager are in cross mesh connection with each other and can access data mutually.
5. The system of claim 4, wherein the consensus manager comprises:
a rule management module: the consensus rules are used for defining and managing the current network support;
a consensus execution module: the rule management module is used for executing the rule according to a formula rule defined in the rule management module;
an extended consistent module: the method is used for bringing the extension functions and the transactions defined in the extension manager into a consensus range when the extension manager is used in the current network.
6. The system of claim 4, wherein the data manager comprises:
a data storage module: the system is used for storing consensus data and personalized data in the current network environment and providing a basis for later inquiry;
a data query module: data for providing a specific condition;
a data interface module: for interfacing with external services.
7. The system of claim 4, wherein the behavior manager comprises:
a behavior definition module: algorithms for defining the types of various behaviors, and the types of behaviors;
a behavior execution module: and the system is used for executing the algorithm behind the behavior according to the definition of the behavior type, providing data input for the execution of the algorithm and collecting feedback execution results after the execution is finished.
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