An adaptive meta-universe system based on a modular blockchain

Abstract

The application relates to the technical field of metaverse, in particular to a self-adaptive metaverse system based on a modular blockchain.A self-adaptive metaverse system based on a modular blockchain comprises a modular blockchain, the modular blockchain automatically determines the most suitable consensus and account book according to the current state of the metaverse through a self-adaptive consensus protocol and a self-adaptive account book protocol; wherein the self-adaptive consensus protocol adopts a pre-trained self-adaptive consensus model to obtain the best consensus algorithm, and when an updated consensus is reached, the consensus algorithm is updated.The self-adaptive consensus model based on the modular blockchain realizes dynamic adaptation to the diversified environment of the metaverse; effectively integrates idle computing power to provide help for other nodes in urgent need of computing power, optimizes resource allocation; and the construction of a temporary trusted metaverse environment ensures that multiple users can safely interact in the metaverse system.

Description

Technical Field

[0001] This invention relates to the field of metaverse technology, and more specifically to an adaptive metaverse system based on modular blockchain. Background Technology

[0002] The concept of the metaverse was first introduced by Neal Stephenson in his 1992 science fiction novel *Avalanche*. In recent years, the metaverse has garnered increasing attention across fields ranging from technology to social sciences. Researchers and developers have been exploring related technologies to recreate the immersive and interactive virtual worlds described in the novel. The ultimate goal is to achieve a seamless integration of the virtual and physical worlds, enabling new forms of communication, collaboration, and creation. Therefore, the development of the metaverse has significant implications for industries such as gaming, education, and e-commerce, as well as for social and cultural practices.

[0003] Blockchain technology, due to its decentralization, transparency, and immutability, has achieved tremendous success in the cryptocurrency field and is widely considered one of the fundamental technologies for realizing the metaverse. The metaverse is a virtual reality world that allows users to interact with each other and their environment within a decentralized, open-source framework. Utilizing blockchain technology for secure transactions in the metaverse enables decentralized data storage and the creation of digital assets, which can be traded or shared securely and transparently among users. Numerous studies have explored the role of blockchain technology in the metaverse, emphasizing that blockchain is not merely a distributed ledger for recording data, but a core component of the metaverse, providing a trusted environment for untrusted users and thus enhancing the overall security of the metaverse ecosystem.

[0004] However, the complex and multifaceted nature of multi-user interactions within the metaverse requires substantial on-chain blockchain resources. Coupled with the inherent on-chain resource costs and significant transaction processing latency of blockchain, this undoubtedly places a heavy burden on users participating in the metaverse, hindering its growth and large-scale adoption. Specifically, it faces two main challenges: First, the incompatibility between the dynamic environment of the metaverse and a fixed consensus / ledger mechanism. Specifically, the scenarios and personnel distribution within the metaverse are constantly changing. For example, when most metaverse scenarios involve internal company work, users are familiar with and trust each other; however, when the scenario shifts to collaboration between different companies, users distrust each other, thus requiring a more secure and trustworthy interaction environment. Metaverse participants at different points in time have varying security requirements for the metaverse system. Second, the high computational power requirements of the metaverse increase the entry barrier for users. Specifically, many metaverse scenarios, including gaming and industrial manufacturing, require significant computational power to provide immersive experiences and accurate models. However, users lacking sufficient computational resources find it difficult to participate, creating a high entry barrier and hindering the widespread adoption of the metaverse. Currently, users can obtain computational power through hardware upgrades or server rental / sale. The former requires high asset requirements, while the latter enriches centralized service providers, exploits user trust, and stifles small computing power providers due to users' lack of confidence.

[0005] Patent application number CN202211583710.2 proposes a blockchain-based metaverse space system. This solution is designed based on pluggable components of the underlying blockchain. However, in the metaverse, users themselves do not understand the technical issues and therefore cannot participate in the replacement of the underlying pluggable components. If only developers can replace the underlying components, it means that the solution is not decentralized. In addition, the solution does not consider how users with limited computing power can participate in metaverse activities. Summary of the Invention

[0006] The purpose of this invention is to solve the aforementioned problems of existing blockchain-based metaverse systems, so as to meet the requirements of on-chain transactions and the computing power needs of metaverse participants.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is to provide an adaptive metaverse system based on modular blockchain, including a modular blockchain. The modular blockchain automatically determines the most suitable consensus and ledger according to the current state of the metaverse through an adaptive consensus protocol and a ledger protocol to provide a secure and reliable interactive environment. The adaptive consensus protocol uses a pre-trained adaptive consensus model to obtain the best consensus algorithm, and updates the consensus algorithm when an update consensus is reached.

[0008] Preferably, the adaptive ledger protocol employs a ledger plugin to enable the conversion between new and old ledgers; the ledger plugin is activated only after an upgrade consensus is reached, accepts sequential historical ledger blocks, and allows them to be used as successor blocks for multiple historical blocks.

[0009] Preferably, the adaptive metaverse system further includes non-fungible resources, which are virtualized device resources used for sharing or renting within the metaverse system; the non-fungible resources are registered on the blockchain in the form of tokens and used to complete transaction settlements.

[0010] Preferably, the device resources include large computers or small sensors; users integrate idle device resources into the device manager of the metaverse; the device manager virtualizes and abstracts the resources of a large number of heterogeneous devices, mapping the device's memory, storage, CPU / GPU to a shared resource space.

[0011] Preferably, the adaptive metaverse system further includes a trusted metaverse environment; the trusted metaverse environment uses a local trust model to create a trusted temporary environment for nodes participating in metaverse tasks; the nodes use the trusted metaverse environment to trade or use non-homogeneous resources.

[0012] Preferably, nodes in the local trust model select a trust evaluation algorithm based on a specific computing task to obtain a corresponding trust level; the trust evaluation process of the local trust model is recorded on the blockchain, and smart contracts allocate corresponding non-fungible resources to the local trust model based on its computing task and trust level.

[0013] Compared with the prior art, the present invention has the following beneficial effects:

[0014] (1) This invention proposes an adaptive decentralized metaverse system based on modular blockchain, emphasizing the importance of blockchain in building and protecting the metaverse;

[0015] (2) An adaptive consensus model based on modular blockchain is proposed, which realizes dynamic adaptation to the diverse environment of the metaverse. While ensuring the security of the metaverse, the model optimizes the resource consumption and execution speed in different metaverse environments.

[0016] (3) A method for renting computing resources in the metaverse is proposed, which effectively integrates idle computing power and provides assistance to other nodes that urgently need computing power, thereby optimizing the resource allocation of nodes in the metaverse.

[0017] (4) A method for constructing a temporary trusted metaverse environment was designed to ensure that multiple users can interact securely in the metaverse system. Attached Figure Description

[0018] Figure 1 This is the overall architecture of the adaptive metaverse system based on modular blockchain in this embodiment of the invention;

[0019] Figure 2 This is a schematic diagram of a local trust model;

[0020] Figure 3 This is a flowchart of the operation process for the Trusted Metaverse environment. Detailed Implementation

[0021] To facilitate understanding of the present invention, it will be described in more detail below with reference to the accompanying drawings and specific embodiments. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in this specification. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of the present invention.

[0022] like Figure 1 As shown, the architecture of the adaptive metaverse system provided by this invention is based on a modular blockchain design to support the operation of the metaverse. Users can participate in metaverse interactions through VR glasses and other devices.

[0023] I. Adaptive Consensus and Ledger of Modular Blockchain

[0024] First, considering the challenges posed by the ever-changing metaverse scenario to blockchain consensus and ledgers, this invention proposes an adaptive consensus / ledger protocol. This protocol automatically determines the most suitable consensus / ledger based on the current state of the entire metaverse and effectively improves the security of the metaverse and saves system resources through hot-swapping of the consensus / ledger. The entire design is based on a modular blockchain design, which helps reduce the cost of changing the consensus. Hot-swappable consensus / ledger replacement avoids the shortcomings of downtime updates. The introduction of an adaptive protocol with machine learning algorithms reduces interference from human factors and increases system security.

[0025] Before implementing the adaptive consensus protocol, constructing and pre-training the adaptive consensus model requires preparing a dataset and some machine learning algorithms. Specifically, based on a modular blockchain supporting hot-swappable consensus, this invention creates a dataset by testing the throughput and latency of various consensus algorithms under different network sizes, erroneous node ratios, and network latency. The dataset is labeled with various consensus algorithms, and its features include metrics such as network size, erroneous node ratio, and network latency. This invention can use various machine learning algorithms to train and test different adaptive consensus models, such as Random Forest, Gradient Boosting Decision Tree (GBDT), XGBoost, and LightGBM. Finally, the model with the highest accuracy is selected.

[0026] The entire execution process of the adaptive consensus protocol is as follows: First, the adaptive consensus model obtains the current network state at fixed intervals to determine the optimal consensus algorithm and compares it with the current consensus algorithm. If the consensus algorithm is the same, the update will end the batch processing. Otherwise, a special transaction tx containing the consensus name to be updated and the block height to be updated will be broadcast to the blockchain. Then, when a blockchain node receives the tx, this invention designs a voting system to verify the legality of the consensus change proposal. If the consensus change proposal is approved by the vote, it is stipulated that the transaction content will be automatically executed after the consensus update is successful, and other nodes will be notified that the update has been successful. If a node fails to complete the upgrade within the agreed time, the node will not be able to participate in subsequent consensus and will need to synchronize its state with other nodes. Of course, since the consensus algorithm library of the modular blockchain is not immutable, new consensus algorithms will be added. At this time, it is necessary to manually test and statistically analyze the metrics of the new consensus algorithm, update the dataset, and then retrain the adaptive consensus model.

[0027] This invention proposes an adaptive ledger design approach to enable the conversion between chained ledgers and DAG ledgers. Specifically, in an adaptive modular blockchain, the ledger implementation is designed to be upgradeable and require no hard forks. This invention allows newly constructed blockchain systems to choose a chained ledger for simplification in the initial stage without worrying about future needs, and to immediately utilize the latest ledger structure when a new one is proposed in the future. To this end, this invention designs a ledger plugin. For example, a DAG-based ledger plugin accepts sequential historical ledger blocks and allows it to be used as a successor block for multiple historical blocks. If a new node joins the blockchain network and verifies historical blocks, inactive plugins remain valid. This is similar to an Ethereum execution layer upgrade, except that the upgrade is applied after consensus rather than a centralized software update; that is, a new plugin is released, and the blockchain system has the right to apply or reject the new plugin, thus avoiding forks. After an upgrade decision is reached, the blockchain client retrieves the plugin binary from the peer-to-peer network and loads the plugin, activating it when the target number of blocks is reached. Compared to Ethereum's upgrade method, no manual operation is required, and the person running the client does not need to manually upgrade the client to keep it in the blockchain network. Note that the consensus process for plugin upgrades is the same as the consensus protocol update process.

[0028] II. Non-homogeneous resources

[0029] Users can virtualize idle resources based on Non-Fungible Resources (NFRs) and upload them to the Metaverse blockchain for rental. These devices can be large computers or small sensors, maximizing resource utilization. Furthermore, this invention proposes payment and incentive mechanisms related to NFRs to attract more users willing to participate in NFR transactions and maintain a better Metaverse ecosystem.

[0030] NFR enables resource virtualization and registration on the blockchain in the form of tokens. Specifically, users first need to obtain legitimate identity through the access control mechanism of the Metaverse system. Metaverse supports networking and computation in a zero-trust environment, thus requiring strict authentication of nodes (including users and devices) and fine-grained management of data access permissions and resource usage rights. For example, if user Alice needs to use user Bob's data for a task, Alice must have legitimate identity and obtain permission to use the data. Then, users integrate idle device resources into the Metaverse's Device Manager. The main function of the Device Manager is to virtualize and abstract the resources of a large number of heterogeneous devices. It maps the device's memory, storage, CPU / GPU, etc., to a shared resource space, abstracting a large number of heterogeneous devices into a giant computer. The blockchain records users' shared resource behavior and returns unique tokens to users. When users reclaim the corresponding resources, the final settlement can be completed through smart contracts using these tokens.

[0031] The above describes the registration process, with three additional key steps: leasing, settlement, and cancellation. These functions allow users to request tasks, complete settlements, and cancel NFRs respectively. This invention introduces a new NFR incentive mechanism in the metaverse that works in conjunction with these three steps. (1) First, in the leasing step, users submit computational tasks (e.g., machine learning, data sharing, and data processing) to a smart contract, specifying the task type, inputs, payment amount, expected output, etc. Each user is mapped to a unique address for network identification and verification. In addition, users have wallets and accounts to pay for or receive the rewards from computational tasks. (2) Then, after receiving the user's computational task, the smart contract is responsible for preprocessing the task, breaking it down under constrained conditions (e.g., task time limits, overhead limits, data security levels), specifying inputs and outputs, data storage locations, data boundaries, data flow directions, and resource constraints. Furthermore, the smart contract allocates reasonable resources for each task and calculates the task overhead as income. Since complex computational tasks often require the collaboration of multiple underlying devices and may require persistent data storage, the metaverse system should minimize bandwidth overhead caused by data flow while providing data security. (3) Finally, when the task is completed, the smart contract executes the settlement step and is responsible for settling the resources consumed. The corresponding NFR will be destroyed after successful settlement. Note that the owner of an NFR can execute a cancellation step, sending a request to the smart contract to actively cancel their NFR on the chain. The smart contract will verify the consistency of the signatures of the owner and the requester to cancel the corresponding NFR.

[0032] III. Credible Metaverse Environment

[0033] This invention proposes an On-Demand Trusted Metaverse Environment (TME) based on NFRs (Non-Fundamental Frames), allowing users to lease on-chain NFRs to address resource constraints. The main idea is to create a trusted temporary environment for nodes participating in metaverse tasks. In addition to purchasing and using NFRs, this invention equips the TME with enhanced security, reliability, and parallel processing capabilities through an improved local trust model and an on-demand trusted metaverse cluster. Users can join specific metaverse scenarios through the TME, such as social, NFT, and work scenarios. NFR transaction records are written to the blockchain to ensure correct execution of interactions between untrusted parties. A large amount of computation is performed off-chain to reduce on-chain resource consumption; only some TME state information needs to be recorded on-chain, such as Open, Run, Suspend, and Close.

[0034] This invention employs a Local Trust Model (LTM) and further refines the evaluation criteria and algorithms for assessing trustworthiness within LTM. The local nature of LTM means that nodes unrelated to the metaverse task do not need to be included in the task's trust evaluation. In fact, these unrelated nodes are unwilling to participate in other task subsets to consume excessive resources. Figure 2 As shown, this invention provides a symbolic expression for LTM. Specifically, the metaverse network is defined as a weighted hypergraph H = (V, E, W), where V represents the set of nodes, E represents the set of hyperedges, and W represents the set of weights. For example, Figure 2 This paper demonstrates four Levelly Transformers (LTMs) within a metaverse network consisting of six nodes (labeled {v1, v2, ..., v6}). LTM 3 comprises three nodes {v2, v3, v4} connected by hyperedges. The trust level of LTM 3 is determined by the degree of trust between {v2, v3, v4}, and factors considered depending on the specific computational task may include network size, message latency, and node history. This invention employs an oracle mechanism to aggregate metaverse network data to calculate trust. After obtaining accurate data, nodes in the LTM can select a suitable trust evaluation algorithm from the trust evaluation module based on the specific computational task and obtain the corresponding trust level. All interaction processes can be viewed as computational tasks, and different interaction processes require different evaluation dimensions. Therefore, different trust evaluation algorithms are selected. For example, interactions involving monetary transactions focus on assets and loan history, while interactions involving certain games focus on game account level and online time. Conventional trust evaluation algorithms include averaging, maximizing, and weighted averaging.

[0035] Note that the trust evaluation process of LTM, such as participating nodes, the selected trust evaluation algorithm, and the trust level, will be recorded on the blockchain. The smart contract will allocate corresponding non-fungible resources (NFR) to LTM based on its computational tasks and trust level.

[0036] Figure 3 Two TMEs, clusters P and Q, are demonstrated. From startup to shutdown, it can be observed that all clusters execute in parallel. The specific process of a TME is explained using P as an example. This invention uses vector C. State Cluster def The TME is represented by (CID, State, G, ΔT, NFR, Results), where CID is the unique identifier of the TME, State represents the current state of the TME (State∈{Open, Run, Suspend, Close}), G represents the participating node, and ΔT is a specified vector. The duration can be sustained, NFR represents the resource borrowing record of participating nodes, and Results is the vector. The set of results that need to be uploaded when attempting to close. Therefore, it can be used. Let G represent the initial state of cluster P. Specifically, multiple nodes form a cluster G. p Group, and Send to the blockchain to establish an on-demand trusted metaverse cluster P at time t, with a duration of δ. Note that this invention uses block height to measure δ to prevent G p The problem of participants' clocks being out of sync. If G p To borrow NFR resources, a sum of money needs to be deposited into a smart contract for final settlement. Then, users can send their requests, such as power consumption and time calculations, to the smart contract. The smart contract will then allocate NFR resources to the appropriate users and process them within the NFR... P Records in the middle.

[0037] After blockchain consensus, P from Become Participants can now begin interacting. Considering that the Metaverse mission may not require interaction or may need more NFRs for a period of time, to save computational resources, this invention sets a Suspend state in the TME and... Once participants decide to continue, they will change their status from... Change back P needs to be closed before t+δ, otherwise a penalty will be imposed (reduction of participants' cryptocurrency and reputation). Participants upload the results of their interactions to the blockchain, and miners successfully verify them. Then close P. The smart contract is based on NFR. PThe content will be settled in NFR and the excess amount will be refunded.

[0038] It is worth mentioning that NFR enables users with insufficient resources to join the metaverse scene using TME, lowering the threshold for entering the metaverse and fully embodying the human-centered metaverse design philosophy.

Claims

1. An adaptive metaverse system based on modular blockchain, comprising modular blockchain, characterized in that: The modular blockchain automatically determines the most suitable consensus and ledger based on the current state of the metaverse through an adaptive consensus protocol and an adaptive ledger protocol. The adaptive consensus protocol uses a pre-trained adaptive consensus model to obtain the optimal consensus algorithm, and updates the consensus algorithm when an update consensus is reached. The pre-trained adaptive consensus model is constructed as follows: a dataset is created by testing the throughput and latency of various consensus algorithms under different network sizes, error node ratios, and network latency using a modular blockchain that supports hot-swappable consensus. The dataset is labeled with various consensus algorithms, and its features include network size, error node ratio, and network latency. The model is trained using at least one machine learning algorithm selected from Random Forest, Gradient Boosting Decision Tree, XGBoost, or LightGBM, and the model with the highest accuracy is selected. The execution process of the adaptive consensus protocol includes: The adaptive consensus model obtains the current network state at fixed intervals to obtain the optimal consensus algorithm and compares it with the current consensus algorithm. If they are different, a special transaction containing the consensus name to be updated and the block height to be updated is broadcast to the blockchain; After receiving a special transaction, a blockchain node verifies the legality of the proposed change to the consensus through a voting system. If the vote is approved, the transaction will be automatically executed and other nodes will be notified that the update has been successful. If a node fails to complete the upgrade within the agreed time, it will be unable to participate in subsequent consensus and will need to synchronize its state with other nodes.

2. The system according to claim 1, characterized in that: The adaptive ledger protocol employs ledger plugins to enable the conversion between new and old ledgers; the ledger plugins are activated only after an upgrade consensus is reached, accept sequential historical ledger blocks, and allow them to be used as successor blocks for multiple historical blocks; the ledger plugins support the conversion between chained ledgers and graph ledgers.

3. The system according to claim 1, characterized in that, It also includes non-homogeneous resources: The non-fungible resources are virtualized device resources used for sharing or leasing within the metaverse system; non-fungible resources are registered on the blockchain in the form of tokens and used to complete transaction settlements. The device resources include large computers or small sensors; users integrate idle device resources into the Metaverse device manager; the device manager virtualizes and abstracts the resources of a large number of heterogeneous devices, mapping the device's memory, storage, CPU / GPU to a shared resource space; The use of non-fungible resources in the metaverse includes leasing, liquidation, and cancellation steps: Users submit computational tasks to smart contracts and specify the task type, inputs, payment amount, and expected output; the smart contract preprocesses the tasks and allocates reasonable resources to each task, calculating task expenses as income; when the task is completed, the smart contract executes the settlement step to settle the consumed resources, and the corresponding non-fungible resources are destroyed after successful settlement; the owner of the non-fungible resources executes the cancellation step by sending a request to the smart contract to actively cancel the non-fungible resources on the chain, and the smart contract verifies the consistency of the signatures of the owner and the requester to cancel the corresponding non-fungible resources.

4. The system according to claim 3, characterized in that, It also includes the credible metaverse environment: The Trusted Metaverse Environment uses the Local Trust Model (LTM) to create a trusted temporary environment for nodes participating in the metaverse task; the nodes use the Trusted Metaverse Environment to trade or use non-fungible resources. The local trust model defines the metaverse network as a weighted hypergraph H=(V,E,W), where V represents the set of nodes, E represents the set of hyperedges, and W represents the set of weights. Nodes in the local trust model select a trust evaluation algorithm based on a specific computational task to obtain a corresponding trust level. The trust evaluation process of the local trust model is recorded on the blockchain, and smart contracts allocate corresponding non-fungible resources to the local trust model based on its computational tasks and trust level.

5. The system according to claim 4, characterized in that: The Trusted Metaverse environment is implemented through the On-Demand Trusted Metaverse cluster TME. The state of TME is represented by the vector C_State = (CID, State, G, ΔT, NFR, Results), where State ∈ {Open, Run, Suspend, Close}. Multiple TME clusters execute in parallel. When a node group needs to borrow non-fungible resources, it deposits funds into a smart contract, which allocates the non-fungible resources and records them in the NFR. After blockchain consensus, TME changes from the Open state to the Run state, and participants begin to interact. TME closes before the agreed time δ. After miners verify the Close state, the cluster is closed. The smart contract settles and refunds excess amounts according to the NFR content. If it is not closed before t+δ, the participants' cryptocurrency and reputation are reduced as a penalty.

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