CN113704272B

CN113704272B - Digital object state expression method and device under man-machine-object fusion environment

Info

Publication number: CN113704272B
Application number: CN202111240623.2A
Authority: CN
Inventors: 黄罡; 罗超然; 马郓; 蔡华谦
Original assignee: Peking University
Current assignee: Peking University
Priority date: 2021-10-25
Filing date: 2021-10-25
Publication date: 2022-01-18
Anticipated expiration: 2041-10-25
Also published as: CN113704272A

Abstract

The application provides a digital object state expression method and a device under a man-machine-object fusion environment, which belong to the technical field of block chains, the embodiment of the application sets two digital objects which are updated simultaneously as similar digital objects by predicting the update time of the digital objects, and writing the state information of the similar digital objects into leaf nodes under the same sub-tree of the first state tree respectively, when the similar digital objects are updated at the same time, only one path from the same sub-tree to the tree root is changed, so that the similar digital objects are prevented from being dispersed under different sub-trees to cause the change of a plurality of paths, therefore, the hash calculation times and the corresponding storage overhead can be effectively reduced, the reconstruction time of the second state tree and the interval of the generation of the state blocks can be shortened, and further, the timeliness of the state information of the digital object is improved, and the time sequence change of the human-machine object digital object is effectively expressed and recorded.

Description

Digital object state expression method and device under man-machine-object fusion environment

Technical Field

The present application relates to the field of block chain technologies, and in particular, to a method and an apparatus for expressing a digital object state in a human-computer-object fusion environment.

Background

The digital Object architecture doa (digital Object architecture) is a software architecture proposed by professor robert-kan in the internet and awarded by the chariot awards, and solves the inter-operation between information system resources in open environment with digital Object as the center. The DOA abstracts the resources into digital objects and models the digital objects into three parts of description information, state information and data entities so as to shield the heterogeneity of the resources, and models the interaction behavior with the resources into three steps of searching, analyzing and accessing so as to reduce the complexity of interaction. The digital object is essentially data abstraction of a resource entity, the resource entity in the internet environment is mainly data resources such as files, base tables and the like in an information system, and the existing DOA realizes the expression of the data resource entity facing the internet environment.

The human-computer-object fusion environment is a novel environment formed by gradually blurring and fusing the boundaries between the human society, the physical world and the information system. The resources in the man-machine object fusion environment mainly comprise man entities and object entities, and the man-machine object resources are abstracted by using the man-machine object digital objects, so that the various and heterogeneous characteristics of the man entities and the object entities can be shielded.

In the man-machine-object fusion environment, different from a relatively stable data entity in the internet environment, a person entity and an object entity have time attributes, the states of the person entity and the object entity can naturally and continuously change along with the change of time, the time attributes of the person entity and the object entity cause that the corresponding man-machine-object digital objects have obvious time sequence change characteristics, and how to depict the time sequence change of the person entity and the object entity is the problem to be solved urgently by the DOA in the man-machine-object fusion environment.

Disclosure of Invention

The application provides a digital object state expression method and device in a man-machine-object fusion environment, which are used for solving the problem that the DOA in the man-machine-object fusion environment cannot effectively express and record the time sequence change of a man-machine-object digital object.

In order to solve the above problems, the present application adopts the following technical solutions:

in a first aspect, an embodiment of the present application provides a method for expressing a digital object state in a human-computer fusion environment, where the method includes:

obtaining a first state chain consisting of a plurality of state blocks; the state block comprises a state block head and a state block body, the state block body comprises a first state tree, and the state block head comprises a tree root of the first state tree and a Hash pointer of a preorder state block;

predicting the updating time of the digital object according to the updating rule of the digital object stored in the first state tree, and setting two digital objects which are updated simultaneously as similar digital objects;

respectively generating a first hash value and a second hash value corresponding to the similar digital object according to the state information of the similar digital object; respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into leaf nodes where the similar digital objects originally exist, so as to obtain a reconstructed second state tree;

obtaining current state information of any similar digital object, and generating a third hash value according to the current state information; replacing the third hash value with the corresponding hash value corresponding to the similar digital object to obtain an updated third state tree;

and writing the tree root of the third state tree and the hash pointer of the corresponding preorder state block into the corresponding block head according to a first preset time interval to obtain an updated second state chain.

In an embodiment of the present application, the step of predicting an update time of the digital object according to an update rule of the digital object stored in the first state tree, and setting two digital objects that are updated simultaneously as similar digital objects includes:

obtaining an updating rule of the digital object according to the historical updating time and the historical updating frequency of the digital object;

predicting the updating time of the digital object by adopting a prediction model according to the updating rule of the digital object;

and setting the two digital objects which are updated simultaneously as similar digital objects according to the updating time.

In an embodiment of the present application, the step of writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects originally exist, so as to obtain the reconstructed second state tree includes:

predicting the first Hash calculation times required by the updating of the similar digital object in a preset updating period of the first state tree according to the updating rule;

predicting a second Hash calculation frequency required by the second state tree for updating the similar digital object in the preset updating period and a third Hash calculation frequency required by the reconstruction of the first state tree into the second state tree according to the updating rule;

subtracting the second hash calculation times and the third hash calculation times from the first hash calculation times respectively to obtain a reconstruction income;

and under the condition that the reconstruction yield is greater than zero, respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of a first state tree, and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects are originally located to obtain a reconstructed second state tree.

In an embodiment of the present application, after the step of writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree respectively to obtain the reconstructed second state tree, the method further includes:

writing the root of the second state tree into a corresponding state block head according to the second state tree to obtain an updated state block;

and broadcasting the updated state block in a state chain to realize consensus.

In an embodiment of the present application, the step of obtaining current state information of any of the similar digital objects includes:

and receiving the current state information of the similar digital objects uploaded by the owner of any similar digital object according to the updating rule, or taking the current access result of the visitor of any similar digital object as the current state information of the similar digital objects.

In a second aspect, based on the same inventive concept, an embodiment of the present application provides an apparatus for expressing a digital object state in a human-computer fusion environment, where the apparatus includes:

the device comprises a first obtaining module, a second obtaining module and a state block generating module, wherein the first obtaining module is used for obtaining a first state chain consisting of a plurality of state blocks; the state block comprises a state block head and a state block body, the state block body comprises a first state tree, and the state block head comprises a tree root of the first state tree and a Hash pointer of a preorder state block;

the prediction module is used for predicting the updating time of the digital object according to the updating rule of the digital object stored in the first state tree and setting two digital objects which are updated simultaneously as similar digital objects;

the reconstruction module is used for respectively generating a first hash value and a second hash value corresponding to the similar digital object according to the state information of the similar digital object; respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into leaf nodes where the similar digital objects originally exist, so as to obtain a reconstructed second state tree;

the first updating module is used for obtaining the current state information of any similar digital object and generating a third hash value according to the current state information; replacing the third hash value with the corresponding hash value corresponding to the similar digital object to obtain an updated third state tree;

and the timing snapshot module is used for writing the tree root of the third state tree and the hash pointer of the corresponding preamble state block into the corresponding block head according to a first preset time interval so as to obtain an updated second state chain.

In an embodiment of the present application, the prediction module includes:

the rule obtaining submodule is used for obtaining an updating rule of the digital object according to the historical updating time and the historical updating frequency of the digital object;

the prediction submodule is used for predicting the updating time of the digital object by adopting a prediction model according to the updating rule of the digital object;

and the setting submodule is used for setting the two digital objects which are updated simultaneously as similar digital objects according to the updating time.

In an embodiment of the present application, the reconstruction module includes:

the first prediction sub-module is used for predicting the first hash calculation times required by the updating of the similar digital object in a preset updating period of the first state tree according to the updating rule;

the second prediction sub-module is used for predicting second Hash calculation times required by the updating of the similar digital objects of the second state tree in the preset updating period and third Hash calculation times required by the reconstruction of the first state tree into the second state tree according to the updating rule;

the profit calculation submodule is used for subtracting the second hash calculation times and the third hash calculation times from the first hash calculation times to obtain reconstruction profits;

and the reconstruction submodule is used for respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of a first state tree and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects originally exist under the condition that the reconstruction yield is greater than zero so as to obtain a reconstructed second state tree.

In an embodiment of the present application, the apparatus further includes:

a second updating module, configured to write a root of the second state tree into a corresponding state block header according to the second state tree, so as to obtain an updated state block;

and the consensus module is used for broadcasting the updated state block in the state chain to realize consensus.

In an embodiment of the present application, the first updating module includes:

and the information obtaining submodule is used for receiving the current state information of the similar digital object uploaded by the owner of any similar digital object according to the updating rule, or taking the current access result of the visitor of any similar digital object as the current state information of the similar digital object.

Compared with the prior art, the method has the following advantages:

the embodiment of the application provides a digital object state expression method under a human-computer fusion environment, by predicting the update timing of a digital object, setting two digital objects whose updates occur simultaneously as similar digital objects, and writing the state information of the similar digital objects into leaf nodes under the same sub-tree of the first state tree respectively, when the similar digital objects are updated at the same time, only one path from the same sub-tree to the tree root is changed, so that the similar digital objects are prevented from being dispersed under different sub-trees to cause the change of a plurality of paths, therefore, the hash calculation times and the corresponding storage overhead can be effectively reduced, the reconstruction time of the second state tree and the interval of the generation of the state blocks can be shortened, and further, the timeliness of the state information of the digital object is improved, and the time sequence change of the human-machine object digital object is effectively expressed and recorded.

Drawings

FIG. 1 is a block diagram illustrating the overall architecture of a digital object architecture in an embodiment of the present application;

FIG. 2 is a flowchart illustrating steps of a method for representing states of digital objects in an environment of human-computer object fusion according to an embodiment of the present application;

FIG. 3 is a schematic structural diagram of a Merkel tree in an embodiment of the present application;

FIG. 4 is a diagram illustrating a state representation of a digital object based on an update rule according to an embodiment of the present application;

fig. 5 is a functional module schematic diagram of a digital object state representation apparatus in a human-computer-object fusion environment in an embodiment of the present application.

Reference numerals: 200-a digital object state expression device in a man-machine-object fusion environment; 201-a first obtaining module; 202-a prediction module; 203-a reconstruction module; 204-a first update module; 205-timed snapshot module.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that, referring to fig. 1, an overall architecture diagram of a digital object architecture is shown, and an overall architecture of the DOA is divided into two parts, namely a data model and an interaction model.

In terms of data models, DOAs take digital objects, which are abstract representations of resources, as essential elements in their architecture. The identification is a unique identity mark of the digital object, and the identification does not change along with the change of the storage environment, the access environment and the content of the digital object. A complete digital object can be divided into three parts: the description information, the data entity and the state information establish an association relationship through the identification of the digital object and point to the same logic digital object. The description information represents metadata related to the digital object and the application and service, and is used for searching the required digital object according to the application requirement, for example: usage of the digital object, classification of the digital object, etc.; the entity represents the actual content of the digital object and is the real target of the interoperation; the state information represents the current state of the digital object, and is used for searching and verifying the digital object, and comprises the following steps: storage location of the digital object, ownership information, digital object Hash, etc. Taking a digital object of a music file as an example, the description information includes information such as music name, author, album to which the music file belongs, music style and the like; the entity is then the actual audio file, such as: xxx.mp 3; the status information includes the actual storage location of the audio file, the actual owner of the audio file, and the Hash value of the content of the audio file. In a man-machine-object fusion environment, the man-machine object resources can be abstracted by using the digital objects, and a uniform resource model is provided so as to shield the heterogeneity of the man-machine object resources.

In the aspect of interaction model, DOA proposes three components for three components of the digital object model: the digital object Registry (DO Registry), the digital object Repository (DO Repository), and the identity Resolution System (Identifier/Resolution System) are used to manage description information, entities, and status information, respectively. The digital object registry is used for managing description information of a digital object and providing index and search service of the digital object to the outside, the index service takes the description information and identification of the digital object as input, the registry establishes the index of the digital object according to the input information, and the search service retrieves the index of the digital object according to the input query keyword and returns a matched digital object identification; the digital object warehouse actually stores the digital object and provides access service of the digital object to the outside, and the access service comprises actions of increasing, deleting, modifying, checking and the like of the digital object; the identification/analysis system is responsible for managing the state information of the digital object, providing identification analysis service, returning the state information of the digital object according to the identification of the target digital object, and in addition, the identification analysis system is responsible for the identification distribution work of the digital object. DOA also makes two standard protocols to specify the interaction behavior of these three components, respectively: a digital Object Interface Protocol doip (digital Object Interface Protocol) for interacting with the digital Object registry, the digital Object repository, and an identity Resolution Protocol (Identifier Resolution Protocol) for interacting with the identity/Resolution system. The DOIP protocol standardizes the access behavior of the digital object, and can be used as abstraction and specification of the interoperation behavior of the man-machine object resources in the man-machine object environment so as to reduce the complexity of the interoperation behavior.

In the internet environment, digital objects are mainly generated in information systems, and are transformed from database tables, documents, pictures and other data already existing in the information systems, for example, the most widespread digital object application DOI currently assigns a unique identifier to a published paper and considers the paper as a digital object. In the aspect of digital object expression, in the existing DOA implementation, a digital object is regarded as a standard data serialization format and a minimum data unit, data is formatted into two parts, namely an attribute and an element, the attribute expresses metadata, actual data content is stored in an element field, and then the digital object is assigned with a unique identifier and is stored in a digital object warehouse uniquely. In the aspect of digital object access, a digital object warehouse generally takes a cloud server as a main part, provides access service of a digital object externally through a unique network entry, can acquire a service address of the warehouse where the digital object is currently located according to the identification resolver state information of the digital object, and further realizes the increasing, deleting, modifying and checking of the digital object through a DOIP protocol, wherein the access mode of the digital object warehouse is not essentially different from the access mode of the existing object database. In terms of access rights management, the manager of the digital object repository is also the owner of all locally stored digital objects, having the right to modify all digital objects.

It can be seen that, in the internet environment, a digital object is an abstract expression of data such as a library table, a document, a picture and the like of an entity in an internet information system, and the data is essentially a string of bit sequences and has the characteristics of easy movement, reproducibility and little static change. Therefore, the DOA-based data resource entity expression in the Internet environment can be effectively realized.

However, in the human-computer-object fusion environment, the human entity has an obvious time attribute, and the importance of the time attribute is reflected not only in the human-computer-object digital object itself but also in the access requirement for the human-computer-object digital object: the access requirements for a human-machine digital object include not only its current, up-to-date status, but may also require access to its historical status at some point, such as viewing the past ten days' air quality. Therefore, the man-machine object needs to be capable of representing the time sequence state change of the human entity. However, frequent time sequence changes of human and animal entities cause that it is almost impossible to completely record all historical states of the human and animal entities, so how to effectively depict the time sequence changes of the human and animal digital objects to describe the time attributes of the human and animal entities is one of the key problems to be solved by the DOA in the human and animal fusion environment.

Aiming at the problem that the time sequence change of a man-machine object digital object cannot be effectively expressed and recorded in the existing DOA, the embodiment of the application aims to provide an efficient and traceable digital object state expression method under a man-machine object fusion environment so as to effectively record the time sequence change of the digital object and optimize the state information management of an identification analysis system on the digital object. Therefore, the state tree is constructed based on the block chain technology to store the state information of the digital object, the highly efficient and traceable digital object time sequence expression is provided, the structure of the state tree is optimized according to the updating rule of the digital object, the reconstruction time of the state tree and the interval of state block generation are shortened, and the timeliness of the state information of the digital object is further improved.

Referring to fig. 2, a method for expressing a digital object state in a human-computer object fusion environment according to the present application is shown, which may include the following steps:

s101: obtaining a first state chain consisting of a plurality of state blocks; the state block comprises a state block head and a state block body, the state block body comprises a first state tree, and the state block head comprises a tree root of the first state tree and a Hash pointer of a preorder state block.

Referring to fig. 4, a digital object state representation diagram based on an update rule is shown, and referring to fig. 4 (a) therein, a digital object time sequence representation diagram based on a state chain is shown, it should be noted that, the construction of the first state chain may be completed on the basic structure of various block chains, a node in the first state chain may be composed of a plurality of state blocks, and each state includes a block header and a block body. Wherein the state zone block comprises a first state tree storing state information of the digital object; the state block header stores information such as the root of the first state tree, the hash pointer of the preamble state block, and the timestamp. The root of the first state tree is the block hash value of the state block, also called the hash value of the state block, and is placed in the head of the state block for data verification, and the hash pointer of the preamble state block is the hash value for pointing to the previous state block, and the state blocks are connected in sequence to form the first state chain in this embodiment through the front-back pointing relationship of the hash pointer of the preamble state block. The Hash (Hash) is a function that maps data of any length into fixed-length data, and the fixed-length data is a Hash value finally obtained.

In this embodiment, the first state tree may be constructed based on a mekerr tree, which is also called a hash tree, and referring to fig. 3, a schematic structural diagram of the mekerr tree is shown, the mekerr tree is divided into two parts, namely a binary tree and a transaction sequence, the transaction sequence is used as a leaf node of the whole mekerr tree and corresponds to the leaf node of the binary tree one to one, and in this embodiment, the first state tree is used for storing state information of the digital object. And in the binary tree part, the values of the leaf nodes are the hash values of the state information of the digital object, and the father node of the tree is the hash value of the combination of the two leaf nodes. The characteristics of the Merkel tree are that any changes to the bottom nodes are transmitted to the father nodes to the tree root, and the changed leaf nodes are easy to locate, so the method is particularly suitable for the quick, effective and safe verification of the existence and the integrity of data. The use of the Merkel tree increases the data tampering difficulty and can realize effective recording of the time sequence change of the digital object.

S102: and predicting the updating time of the digital object according to the updating rule of the digital object stored in the first state tree, and setting two digital objects which are updated simultaneously as similar digital objects.

Continuing to refer to fig. 4, where fig. 4 (b) shows a schematic diagram of a state tree construction algorithm based on an update rule, where it is to be noted that, for a first state tree with a total number of leaf nodes of n, the total number of non-leaf nodes is n-1, which means that n-1 hash calculations are required to be performed when constructing the first state tree, an increase in the number of digital objects will increase the construction time of the first state tree, and an excessively long calculation time interval of the first state tree will decrease the timeliness of the state information of the digital objects.

Therefore, in this embodiment, in order to reduce the number of hash computations for constructing the first state tree, in this embodiment, two digital objects that are updated simultaneously are set as similar digital objects, and since the update rules are the same, when the two similar digital objects are updated simultaneously, only the change of the hash value of the parent node to which the two similar digital objects belong commonly is caused.

S103: respectively generating a first hash value and a second hash value corresponding to the similar digital object according to the state information of the similar digital object; and respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects are originally located, so as to obtain the reconstructed second state tree.

With reference to fig. 4 (b), in this embodiment, when the similar digital objects are updated synchronously, the state information of the similar digital objects is first mapped to a function of fixed-length data, where the fixed-length data are the first hash value and the second hash value corresponding to the similar digital objects, and the first hash value and the second hash value are respectively written into leaf nodes under the same sub-tree of the first state tree, it should be noted that the same sub-tree is used as one of the branches of the first state tree, and leaf nodes under the same sub-tree correspond to the same parent node, which means that when the similar digital objects are updated simultaneously, only a change on one path from a parent node corresponding to the leaf node to the tree root is caused, so that the similar digital objects are prevented from being scattered under different sub-trees to cause changes of multiple paths, thereby effectively reducing the number of hash computations and the corresponding storage costs, the method and the device realize efficient reconstruction of the second state tree in massive digital objects, shorten reconstruction time of the second state tree and intervals generated by state blocks, further improve timeliness of state information of the digital objects, and simultaneously reduce the size of the state block after the leaf nodes are recombined according to an updating rule, and reduce corresponding storage overhead.

In this embodiment, a preset update period or a plurality of fixed time points may be set to reconstruct the second state tree, and in one example, the preset update period may be set to 0:00 based on the update rule of the digital object stored in the previous first state tree, the structure of the first state tree is adjusted and reconstructed to obtain a second state tree with an optimized structure.

S104: obtaining the current state information of any similar digital object, and generating a third hash value according to the current state information; and replacing the third hash value with the corresponding hash value corresponding to the similar digital object to obtain an updated third state tree.

In this embodiment, based on the reconstructed second state tree, the current state information of any similar digital object may be obtained at a second preset time interval, and in an example, the current state information of any similar digital object may be obtained every ten seconds, and the hash value is replaced in the corresponding leaf node, so that the current state information of the similar digital object is stored in the third state tree.

With continued reference to fig. 4 (a), in the present embodiment, preferably, an update strategy combining active publishing and passive recording is employed to obtain the current status information of any similar digital object. Specifically, the owner of any similar digital object uploads the current state information of the similar digital object according to the update rule, or the current access result of the visitor of any similar digital object is taken as the current state information of the similar digital object. It should be noted that, because the time sequence change frequency differences of different people and physical entities are large, for the owner of the similar digital object, the current state of the similar digital object can be actively uploaded or issued to the identifier resolution system at regular intervals or at any time according to the held update rule of the similar digital object, and the identifier resolution system receives and stores the current state corresponding to the similar digital object; in addition, the access result generated by the visitor to the similar digital object during the access updates the current access result to the identification resolution system as the current state of the similar digital object, in one example, the visitor accesses the state information of the similar digital object five times in one minute, and for the identification resolution system, the fifth access result of the visitor updates as the current state of the similar digital object.

S105: and writing the tree root of the third state tree and the hash pointer of the corresponding preorder state block into the corresponding block head according to the first preset time interval to obtain an updated second state chain.

In this embodiment, the current state information of the similar digital object stored in the third state tree is published in a form of writing the tree root of the third state tree and the hash pointer of the corresponding preamble state block into the corresponding block header according to the first preset time interval, and then the updated second state chain is obtained on the basis of the first state chain.

In one example, a similar digital object is vehicle speed information of a corresponding vehicle, the identifier resolution system acquires the vehicle speed information of the vehicle every ten seconds, the first preset time interval is set to one minute, that is, the vehicle speed information is continuously acquired within the time interval of one minute, after the interval of one minute, the vehicle speed information of the vehicle acquired for the sixth time is stored in the third state tree as the latest current vehicle speed information and the tree root is written into the corresponding block header, and the tree root is published in the original first state chain in a snapshot manner to inform other state blocks of the latest vehicle speed information, so that consensus is realized, and the updated second state chain is obtained.

It should be noted that, in this embodiment, the selection of the first preset time interval may be correspondingly set in combination with factors such as an update rule of the digital object itself and/or a precision requirement of the data record, that is, the embodiment does not specifically limit the digital object, and only needs to meet a requirement of an actual application scene.

In a possible embodiment, the specific steps of S102 may be:

s102-1: obtaining an updating rule of the digital object according to the historical updating time and the historical updating frequency of the digital object;

in this embodiment, the update rule of the digital object can be known from the history update time and the history update frequency of the digital object. For a digital object with relatively fixed update frequency, if equipment needing to be checked regularly or weather forecast data issued regularly, the time for the next check can be determined according to the corresponding check interval or issue interval; for digital objects with relatively frequent updating frequency, such as pulse information of a human body, the digital objects can be uploaded to an identification analysis system for storing the pulse information according to a preset uploading interval after the digital objects detect the pulse information through equipment such as a bracelet and the like; and for the digital objects which are discretely distributed to a certain extent at the updating moment, updating and predicting by adopting a prediction model so as to obtain an accurate updating rule to the maximum extent.

S102-2: predicting the updating time of the digital object by adopting a prediction model according to the updating rule of the digital object;

in this embodiment, preferably, a prediction model may be constructed from existing historical update data samples based on a regression algorithm to predict the update time of the digital object. And as time goes on, the samples are increased, the prediction result of the prediction model is more accurate, and the structure of the reconstructed state tree is continuously optimized.

S102-3: according to the updating time, two digital objects which are updated simultaneously are set as similar digital objects.

In this embodiment, two digital objects that are updated simultaneously are set as similar digital objects according to the prediction result of the prediction model, and it should be noted that the two digital objects that are updated simultaneously may be set with update precision according to actual needs, that is, in a case where both the two digital objects are updated within a preset update time interval, the two digital objects may be determined as similar digital objects, where the preset update time interval may be set according to actual precision requirements.

In a feasible implementation manner, in S103, the step of writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into leaf nodes where similar digital objects originally exist, so as to obtain the reconstructed second state tree may include:

s103-1: and predicting the first hash calculation times required by the updating of the similar digital object of the first state tree in a preset updating period according to the updating rule.

S103-2: and predicting the second Hash calculation times required by the similar digital objects of the second state tree in a preset updating period and the third Hash calculation times required by the reconstruction of the first state tree into the second state tree according to the updating rule.

S103-3: and respectively subtracting the second hash calculation times and the third hash calculation times from the first hash calculation times to obtain the reconstruction income.

S103-4: and under the condition that the reconstruction yield is greater than zero, respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects originally are located to obtain the reconstructed second state tree.

In the embodiment, it is considered that the reconstruction of the first state tree is accompanied by the generation of the corresponding reconstruction overhead, so that the corresponding input-output ratio needs to be considered before the reconstruction of the first state tree, and unnecessary resource waste is avoided.

In one example, the first state tree is set to be adjusted once per day at 0:00, and the number of third hash computations required to reconstruct the first state tree into the second state tree is predicted according to a regression algorithm during adjustment. And meanwhile, respectively calculating the first hash calculation times and the second hash calculation times required by the updating of the similar digital objects in the first state tree and the second state tree in a preset updating period from 0:00 of the current day to 0:00 of the next day according to the updating rule of the similar digital objects. And finally, subtracting the second hash calculation times and the third hash calculation times from the first hash calculation times respectively to obtain the reconstruction income which can be obtained by the reconstructed second state tree. It should be noted that the reconstruction benefits include, in addition to the reduced hash calculation times, a corresponding reduced storage overhead, where the storage overhead is equal to the product of the reduced hash calculation times and the storage size of the leaf node. And under the condition that the reconstruction yield is greater than zero, respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects originally are located to obtain the reconstructed second state tree, so that the reconstructed second state tree can obtain corresponding yield, the reconstruction as required is realized, and the resource waste is avoided.

In a possible embodiment, after the step S103, the method may further include the steps of:

s106: and writing the root of the second state tree into the corresponding state block head according to the second state tree to obtain the updated state block.

S107: and broadcasting the updated state block in the state chain to realize consensus.

In this embodiment, for the reconstructed second state tree, the state information of the similar digital object is stored in leaf nodes under the same sub-tree of the second state tree, and then the change of the state information of the similar digital object is transmitted to the sub-tree corresponding to the leaf node, i.e. the same parent node, through hash calculation, and the parent node is transmitted to the tree root along the update path; writing the root of the second state tree into the corresponding state block head to obtain an updated state block; and finally, broadcasting the updated state block in the state chain, and informing the latest state of the digital object of other state blocks to realize consensus.

Based on the same inventive concept, referring to fig. 5, a digital object state expression apparatus 200 in a human-computer object fusion environment according to an embodiment of the present application is shown, where the digital object state expression apparatus 200 in the human-computer object fusion environment includes:

a first obtaining module 201, configured to obtain a first state chain composed of a plurality of state blocks; the state block comprises a state block head and a state block body, the state block body comprises a first state tree, and the state block head comprises a tree root of the first state tree and a Hash pointer of a preorder state block;

a prediction module 202, configured to predict an update time of a digital object according to an update rule of the digital object stored in the first state tree, and set two digital objects that are updated simultaneously as similar digital objects;

the reconstruction module 203 is configured to generate a first hash value and a second hash value corresponding to the similar digital object according to the state information of the similar digital object; respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree, and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects are originally located to obtain a reconstructed second state tree;

the first updating module 204 is configured to obtain current state information of any similar digital object, and generate a third hash value according to the current state information; replacing the third hash value with the corresponding hash value corresponding to the similar digital object to obtain an updated third state tree;

the timing snapshot module 205 is configured to write the tree root of the third state tree and the hash pointer of the corresponding preamble state block into the corresponding block header according to a first preset time interval, so as to obtain an updated second state chain.

In one possible implementation, the prediction module 202 includes:

the rule obtaining submodule is used for obtaining the updating rule of the digital object according to the historical updating time and the historical updating frequency of the digital object;

In one possible implementation, the reconstruction module 203 includes:

the first prediction submodule is used for predicting the first hash calculation times required by the updating of the similar digital objects of the first state tree in a preset updating period according to the updating rule;

the second prediction submodule is used for predicting the second Hash calculation times required by the updating of the similar digital objects of the second state tree in a preset updating period and the third Hash calculation times required by the reconstruction of the first state tree into the second state tree according to the updating rule;

the profit calculation submodule is used for subtracting the second hash calculation times and the third hash calculation times from the first hash calculation times to obtain reconstructed profits;

and the reconstruction submodule is used for respectively writing the first hash value and the second hash value into leaf nodes under the same subtree of the first state tree and writing the original hash values of the leaf nodes into the leaf nodes where the similar digital objects are originally located under the condition that the reconstruction yield is greater than zero so as to obtain the reconstructed second state tree.

In a possible embodiment, the apparatus further comprises:

the second updating module is used for writing the root of the second state tree into the corresponding state block head according to the second state tree to obtain an updated state block;

In one possible implementation, the first updating module 204 further includes:

To sum up, the digital object state expression apparatus 200 in the human-computer fusion environment according to the embodiment of the present application, wherein the prediction module 202 predicts the update time of the digital object according to the update rule of the digital object, and sets two digital objects that are updated simultaneously as similar digital objects; the reconstruction module 203 writes a first hash value and a second hash value corresponding to the similar digital object into leaf nodes under the same sub-tree of the first state tree respectively under the condition that the profit is greater than the reconstruction overhead, so as to obtain a reconstructed second state tree, so that when the similar digital objects are updated simultaneously, only the change of one path from the same sub-tree to the tree root is caused, and the similar digital objects are prevented from causing the changes of a plurality of paths under different sub-trees in a dispersed manner; the first updating module 204 is configured to obtain and update the current state information of the similar digital object in real time, so as to implement effective recording of time sequence change of the similar digital object; the snapshot timing module 205 is configured to publish current state information of the similar digital object in a snapshot manner, and notify other state blocks of the latest state information. The digital object state expression device 200 in the human-computer object fusion environment provided by the embodiment of the application can optimize and reconstruct the state tree according to actual requirements, the optimized state tree can effectively reduce the hash calculation times and corresponding storage overhead, the reconstruction time of the second state tree and the interval generated by the state blocks are shortened, further the timeliness of digital object state information is improved, and the time sequence change of the human-computer object is effectively expressed and recorded.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.

Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.

The method and the device for expressing the digital object state in the man-machine-object fusion environment provided by the invention are described in detail, specific examples are applied in the method to explain the principle and the implementation mode of the invention, and the description of the examples is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. A method for expressing the state of a digital object in a man-machine-object fusion environment is characterized by comprising the following steps:

2. The method of claim 1, wherein the step of predicting the update time of the digital object according to the update rule of the digital object stored in the first state tree, and setting two digital objects that are updated simultaneously as similar digital objects comprises:

3. The method according to claim 1, wherein the step of writing the first hash value and the second hash value into leaf nodes under a same sub-tree of a first state tree, respectively, and writing original hash values of the leaf nodes into leaf nodes where the similar digital objects originally exist, so as to obtain a reconstructed second state tree comprises:

4. The method of claim 1, wherein after the step of writing the first hash value and the second hash value into leaf nodes under a same sub-tree of the first state tree to obtain the reconstructed second state tree, the method further comprises:

and broadcasting the updated state block in a state chain to realize consensus.

5. The method of claim 1, wherein the step of obtaining current state information for any of the similar digital objects comprises:

6. A digital object state representation apparatus in a human-computer-object fusion environment, the apparatus comprising:

7. The apparatus of claim 6, wherein the prediction module comprises:

8. The apparatus of claim 6, wherein the reconstruction module comprises:

9. The apparatus of claim 6, further comprising:

10. The apparatus of claim 6, wherein the first update module comprises: