CN116668450A - Block chain-based edge computing multidimensional trust evaluation method and system - Google Patents

Abstract

The present invention relates to a blockchain-based edge computing multi-dimensional trust evaluation method and system, including: determining a blockchain-based distributed IoT edge computing architecture; determining a blockchain-based distributed IoT edge computing architecture Based on this, a trust evaluation model is established, and the intra-domain trust evaluation and inter-domain trust fusion and reputation calculation are performed on the nodes that provide services after the service ends, and the final reputation value of each service provider node is obtained. The present invention uses the domain as a whole to perform multi-dimensional trust evaluation on the service provider nodes, obtains a lightweight and scalable trusted evaluation model suitable for the edge computing environment of the Internet of Things, and uses the uncertainty theory to evaluate feedback information and QoS performance in the domain It can not only accurately describe the performance of the service, but also describe the dynamics and uncertainty of the service performance. The present invention can be widely applied to the technical field of Internet of things.

Description

A blockchain-based edge computing multi-dimensional trust evaluation method and system

technical field

The invention relates to a block chain-based edge computing multi-dimensional trust evaluation method and system, belonging to the technical field of the Internet of Things.

Background technique

With the popularization of 5G technology, the number of IoT terminal nodes has increased dramatically, and due to the resource constraints of terminal nodes and the dynamic nature of the network environment, it is a huge challenge to establish one-to-one accurate trust evaluation in the IoT edge computing environment. challenge. Many researchers have proposed a blockchain-based trust evaluation model in the context of IoT, they consider trust as a whole, and trust values correspond to binary experiences (i.e., positive or negative), which in many cases may Can produce inaccurate assessment results and does not take into account the dynamic nature of the network environment. Some researchers claim that it is possible to provide more precise reasoning for decision-making by viewing trust as the synthesis of multiple trustworthy attributes. There are also some researchers who claim that a trusted service should meet the requirements of requesting nodes and its performance should be stable, that is, its time-series objective QoS data and subjective feedback ratings from requesting nodes should have a good central trend, narrow variation range and low frequency of change. However, in traditional IoT trust evaluation systems, it is difficult to cover the above three characteristics.

At present, existing trust evaluation models can be divided into centralized models and decentralized models. In the decentralized trust evaluation mechanism, end nodes evaluate the trust value of the nodes they interact with, increasing the burden on resource-constrained end nodes. The centralized trust management model usually relies on a third-party trust management center to evaluate and store the trust value of end nodes in the entire network, which may lead to opacity, delay, congestion and even single point of failure of trust evaluation.

Contents of the invention

In view of the above problems, the purpose of the present invention is to provide a multi-dimensional trust evaluation method and system for edge computing based on blockchain. Under the accurate trust requirements and resource constraints, the method constructs a dynamic IoT edge computing environment suitable for the following Blockchain is an interactive multi-dimensional trust evaluation model, which is of great significance for risk prevention, service selection, recommendation and decision-making.

To achieve the above object, the present invention takes the following technical solutions:

In the first aspect, the present invention provides a blockchain-based edge computing multi-dimensional trust evaluation method, comprising the following steps:

Determine the blockchain-based distributed IoT edge computing architecture;

Based on the determined blockchain-based distributed IoT edge computing architecture, a trust evaluation model is established, and the intra-domain trust evaluation and inter-domain trust fusion and reputation calculation are performed on the nodes that provide services after the service is over, and the information of each service provider node is obtained. Domain trust value and final reputation value.

Further, the blockchain-based distributed edge computing architecture of the Internet of Things includes: a domain node layer and an edge server layer;

The domain node layer is configured with a plurality of domains divided according to geographical locations, and each domain is configured with a domain management node and several domain nodes. The domain management node and each domain node are connected through an overlay network protocol or an underlying network protocol Communicate with each other; the domain management node is used to regularly collect subjective feedback rating information and objective QoS values in the domain, and after processing these data, obtain trust data and send it to the edge server layer; the domain node is used to provide services to the domain management node Provide the subjective feedback rating information of the node; the service providing node is an edge server or a domain node that can provide services;

Several edge servers and blockchains are configured in the edge server layer, and the edge servers are used to provide services to domain nodes and maintain the normal operation of the blockchain.

Further, based on the determined blockchain-based distributed IoT edge computing architecture, a trust evaluation model is established, and intra-domain trust evaluation and inter-domain trust fusion and reputation calculation are performed on nodes providing services after the service ends, and various The service provides the final reputation value of the node, including:

Based on the expressiveness and stability of the service attribute of the service provider node in each domain, the trust degree of the service provider node in each domain is calculated;

Based on the trust degree of the service provider node in each domain, the final reputation value of the service provider node is calculated.

Further, the calculation of the trust degree of the service providing node in each domain based on the performance and stability of the service attribute of the service providing node in each domain includes:

According to the commitment performance level of the service provider node sp _j and the monitoring performance level of the domain service node, the actual performance level of the attribute of the service provider node sp _j is calculated;

Integrate the collected information on the actual performance level of each attribute, and calculate the performance and stability of each service attribute of the service provider node in the entire domain;

An adaptive attribute weight mechanism is constructed, and based on the performance and stability of each service attribute of the service provider node in the entire domain, the intra-domain trust degree of the service provider node is calculated.

Further, the integration of the collected information on the actual performance level of each attribute, and the calculation of the performance and stability of each service attribute of the service provider node in the entire domain include:

Use probabilistic language elements to represent the performance of each attribute of the service provider node in the entire domain;

Based on the representation of each attribute performance of the service provider node in the entire domain, calculate the attribute expressiveness of the service provider node;

Based on the information entropy, the calculation service provides the attribute stability of the node.

Further, the calculation of the final reputation value of the service provider node based on the trust degree of the service provider node in each domain includes:

Calculate the weight information based on the number of interactions of the service provider in each domain;

According to the weight information, inter-domain trust fusion is performed on the trust degree of the service provider node in each domain;

Query the blockchain to obtain the reputation value of the service provider node in the previous time window, and calculate the final reputation value of the service provider node in the hth time window.

Further, the hth time window service provides the final reputation value of the node for:

in, and /> Indicates the final reputation value of the h-th time window and the h-1th time window service provider node; T ^h (A( _xi ), sp _j ) means that the service provider sp _j in the h-th time window, in domain A ( _xi ) trust degree; /> Indicates the weight information of the trust value of each domain when inter-domain trust fusion; |sp _j →A(xi ₎ | ^h indicates the number of interactions between sp _j and nodes in domain A(xi ₎ in the hth time window; μ ₁ , 1-μ ₁ represent the weight of the trust calculated in the current time window and the weight of the reputation value at the previous moment, respectively.

In the second aspect, the present invention provides a blockchain-based edge computing multi-dimensional trust evaluation system, including:

The architecture determination module is used to determine the blockchain-based distributed IoT edge computing architecture;

The trust evaluation module is used to establish a trust evaluation model based on the determined blockchain-based distributed IoT edge computing architecture, and perform intra-domain trust evaluation and inter-domain trust fusion and reputation calculation for the nodes that provide services after the service ends. The final reputation value of each service provider node is obtained, which is used for the service request node to select a better service provider node.

In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to execute the described any of the methods.

In a fourth aspect, the present invention provides a computing device, including: one or more processors, memory and one or more programs, wherein one or more programs are stored in the memory and configured as the one or more executed by a processor, the one or more programs including instructions for performing any of the methods.

The present invention has the following advantages due to the adoption of the above technical scheme:

(1) The present invention proposes to conduct multi-dimensional trust evaluation on service provider nodes by taking the domain as a whole, and realizes a lightweight and scalable trust evaluation model suitable for the edge computing environment of the Internet of Things.

(2) The present invention uses uncertainty theory (hesitation fuzzy set theory) to process and integrate evaluation feedback information and QoS performance levels in the domain, and measure service credibility from two indicators of performance and stability, which can accurately describe The performance of the service can also describe the dynamics and uncertainty of the service performance.

(3) The present invention proposes an adaptive attribute weight mechanism, which associates the weight of each attribute with the number of feedback times of the attribute by nodes in the domain, and more accurately measures the overall performance of the service provider node

(4) With the help of blockchain smart contract technology, the present invention realizes rapid verification of node identity data, tamper-proof trust evidence, cross-domain sharing of trust data and fusion of inter-domain trust data.

Therefore, the present invention can be widely applied to the technical field of the Internet of Things.

Description of drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiment. The drawings are only for the purpose of illustrating a preferred embodiment and are not to be considered as limiting the invention. Throughout the drawings, the same reference numerals are used to refer to the same parts. In the attached picture:

Fig. 1 is an architecture diagram based on block chain in the embodiment of the present invention;

Fig. 2 is a framework diagram of edge computing trust evaluation in an embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the following will clearly and completely describe the technical solutions of the embodiments of the present invention in conjunction with the drawings of the embodiments of the present invention. Apparently, the described embodiments are some, not all, embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention belong to the protection scope of the present invention.

It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and/or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and/or combinations thereof.

In a heterogeneous IoT edge computing environment, the diversity of service types leads to the diversity of evaluation attributes, which is a huge workload for building a trust evaluation model that includes multiple attributes. In some embodiments of the present invention, a blockchain-based edge computing multi-dimensional trust evaluation method is provided, which adopts an evaluation method combining centralized and decentralized trust evaluation, and uses blockchain technology to realize node identity authentication and trust data automatic evaluation and sharing. First, terminal nodes with similar locations are divided into a domain, and the domain as a whole is used to evaluate the performance of service-providing nodes. Each domain selects a node with strong resource capability as the domain administrator (DA), which regularly collects the performance data of each attribute of the service provider node in the domain (the subjective feedback of the requesting node and the actual performance level of QoS), Then it is converted into the form of probabilistic linguistic elements (PLEs), which considers both qualitative variables and their distribution attributes, which can better reflect the dynamics and uncertainty of service performance, and then calculate the service provision The expression degree of each attribute of the node in this domain, and calculate the stability of each attribute based on the information entropy theory, and measure the performance of each attribute from the two indicators of expression degree and stability. Secondly, an adaptive attribute weight mechanism is proposed, based on The feedback times of each attribute of the service provider node in the domain determines the weight of each attribute, and calculates the trust value of the service provider node in each domain. Finally, the trust value of the service provider node in each domain is weighted, and the blockchain is queried to obtain the reputation value of the service provider node at the previous moment, and finally the current reputation value of the service provider node is obtained.

Correspondingly, other embodiments of the present invention provide a blockchain-based edge computing multi-dimensional trust evaluation system, device and storage medium.

Example 1

As shown in Figure 1 and Figure 2, this embodiment provides a blockchain-based edge computing multi-dimensional trust assessment method, which includes the following steps:

1) Determine the blockchain-based distributed IoT edge computing architecture.

As shown in FIG. 1 , the distributed IoT edge computing architecture adopted in this embodiment is divided into an edge server layer and a domain node layer. Among them, the edge server layer is configured with a number of edge servers and the blockchain maintained by the edge server; the domain node layer is configured with a number of domains divided according to geographical location, and each domain is configured with a domain management node (DA) And several domain nodes; the domain management node and each domain node communicate with each other through the overlay network protocol or the underlying network protocol.

Specifically, the four components involved in the architecture, namely edge server, domain node, domain management node and blockchain are introduced respectively below.

Domain Node: Refers to a fixed or mobile node requesting service within a specific geographic location. Due to resource constraints, these domain nodes act as clients of the blockchain, keeping only the Merkle root of the blockchain. After interacting with the service providing node, the domain node provides the subjective feedback rating information of the service providing node to the domain management node. Among them, the service provider node refers to a node that can provide services, including edge servers and domain nodes with strong resource capabilities that can provide services, and can provide services within a domain or across domains.

Domain management node (DA): refers to a fixed node with strong computing power and storage capacity in the domain. It acts as a full node of the blockchain and is also the management node of the entire domain. It is responsible for regularly collecting subjective feedback rating information and objective QoS in the domain (quality of service, quality of service) value, and then process these trust data and submit it to the blockchain for further processing. In addition to this, it is also responsible for QoS performance monitoring within the domain.

Edge server: refers to a fixed server with powerful computing and storage capabilities. These edge servers are usually located near the base station, can provide services to other requesting nodes, and are responsible for maintaining the normal operation of the blockchain. They act as full nodes of the blockchain and are responsible for verify.

Blockchain: Blockchain has the advantage of high reliability due to its consensus mechanism and the same distributed storage copy, and this invention applies blockchain technology to the distributed edge computing architecture of the Internet of Things, thereby significantly enhancing the edge computing network security.

In a certain period of time, the trust data submitted by all domains are stored in a block, that is to say, the trust data of this period of time is placed in this block, and the trust data of the next period of time is placed in the next block, forming a block chain. The format of various transaction data in the blockchain is shown in Table 1 below. ID represents the transaction number, and the transaction type consists of TE (trust evidence), QC (QoS performance), IR (identity registration), and LTV (local trust value update). In addition to smart contracts, various transactions are packaged into blocks through the data format shown in Table 1 for storage. Once these transactions are packaged into blocks, they cannot be tampered with or deleted.

Table 1 Transaction data format

2) Based on the determined blockchain-based distributed IoT edge computing architecture, a trust evaluation model is established, and the intra-domain trust evaluation and inter-domain trust fusion and reputation calculation are performed on the nodes that provide services after the service ends, and the results of each service provider are obtained. The final reputation value of the node is used for the service request node to select a better service provider node.

As shown in Figure 2, the trust evaluation model established in this embodiment is divided into two layers. The first layer is intra-domain trust evaluation, which can be calculated from two indicators of performance and stability; the other layer is cross-domain trust fusion and Reputation evaluation, that is, integrate the trust value of the service provider node in each domain in the hth time window, and then query the blockchain to obtain the reputation value of the service provider node in the previous time window, and obtain the final reputation of the hth time window value.

2.1) Calculate the trust degree of the service provider node in each domain based on the performance degree and stability degree of the service attribute of the service provider node in each domain.

In order to measure service credibility more accurately, the present invention constructs two indicators to evaluate the trust of service providing nodes. The first is expressiveness, which is mainly used to measure the performance of each attribute, and the second is stability, which is mainly used to measure the dynamics and uncertainty of each attribute. The specific evaluation process is as follows:

2.1.1) According to the commitment performance level of the service provider node sp _j and the monitoring performance level of the domain management node, the actual performance level of the attribute of the service provider node sp _j is calculated.

By comparing the attribute monitoring performance level of the service provider node sp _j with the commitment performance level of the service provider node, the actual performance level of the attribute provided by the service provider node is calculated, and the calculation formula is:

in, Indicates the monitoring performance level of the attribute when the service provider node sp _j provides service to the domain node A( _xi ,y _k ) in the hth time window;/> Indicates the performance level promised by the service provider node sp _j to the domain node A( _xi ,y _k );/> Indicates the actual performance level of the attribute that the service providing node sp _j provides service to the domain node A( _xi , _yk ) in the hth time window.

2.1.2) Integrate the actual performance level information of each attribute collected in step 2.1.1), and calculate the performance and stability of each service attribute of the service provider node in the entire domain.

Specifically, the following steps are included:

2.1.2.1) Use probabilistic language elements to express the performance of each attribute of the service provider node in the entire domain.

In order to accurately aggregate the feedback information of each requesting node in the domain, while considering its qualitative variables and their distribution characteristics, the present invention adopts Probabilistic Language Elements (PLEs) to represent the representation of service attributes provided by service providing nodes. Probabilistic Language Elements (PLEs) are defined as follows:

Definition 1. Suppose S={s _α |α=1,2,...,τ} is a set of linguistic terms, and the probabilistic linguistic elements (PLEs) are Where s ^l (p ^l ) is the language term variable s ^l and the corresponding probability p ^l , #L(p) is the number of language terms in L(p).

Definition 2. Suppose S=(s _α |α=1,2,...,τ} is a set of language terms, for probabilistic language variables L(p)=(s ^l (p ^(l) )|s ^l ∈ S , l=1, ..#L(p)}, the expected value of L(p) is:

where f ^l is the subscript of the linguistic term s ^l .

Therefore, the performance of each attribute of a service provider node in the entire domain can be expressed as:

Among them, |s ^l | represents the number of requesting nodes in the domain that provide feedback ratings of s ^l on a certain attribute of sp _j .

2.1.2.2) Based on the representation of each attribute performance of the service provider node in the entire domain, calculate the attribute expressiveness of the service provider node.

Among them, the performance vector of each attribute of the service provider sp _j in the domain A( _xi ) in the hth time window is:

in, Indicates that the service provider node spj behaves in the qth attribute in domain A( _xi ) in the hth time window. In order to facilitate subsequent calculations, the attribute representation represented by the PLE method is converted into a numerical representation using formula (1), as shown in the following formula

2.1.2.3) Based on the information entropy, calculate the attribute stability of the service provider node.

Information entropy is used as a measurement tool because it is suitable for measuring the uncertainty of information expressed in probability, and the information expressed in PLE meets these conditions exactly. Information entropy represents the measurement of the order degree of the system, the greater the uncertainty of the variable, the greater the information entropy.

Definition 3. Suppose the probabilistic language elements are: The information entropy of L(p) is defined as

Among them, z is set to 1.28.

The formula for calculating the stability is

st(L(p))=τ*(1-H(L(p))) (7)

Among them, τ represents an adaptive adjustment factor, depending on the size of E(L(p), it can prevent some service provider nodes with high stability but poor performance from obtaining high trust values. 0≤β≤1 is used to control the value of τ The minimum value, when β is fixed, the closer E(L(p) is to 1, the larger the τ value. When calculating the local trust value, when the proportion of malicious services is high or the network environment is unstable, it can be adjusted by adjusting β Increase the weight of the stability. Δ>0 represents a constant used to adjust the decline rate of the function curve. Therefore, it can be obtained It represents the stability of the qth attribute of sp _j in the domain A( _xi ) in the hth time window.

2.1.3) Build an adaptive attribute weight mechanism, and calculate the intra-domain trust degree of the service provider node based on the performance and stability of each service attribute of the service provider node in the entire domain.

Among them, the trust degree of service provider sp _j in domain A( _xi ) in the hth time window is expressed as:

Among them, σ ₁ and (1-σ ₁ ) represent the weights of performance degree and stability degree respectively, Indicates the weight of the qth attribute in the hth time window. The basic idea is that the more times a domain evaluates an attribute, the more attention it is paid to the requesting nodes in the domain.

in, Indicates the number of feedbacks of the qth attribute submitted by A( _xi ) to sp _j in the hth time window.

2.2) Calculate the final reputation value of the service provider node based on the trust degree of the service provider node in each domain.

Specifically, the following steps are included:

2.2.1) Calculate the weight information according to the interaction times of the service provider in each domain;

2.2.2) According to the weight information, inter-domain trust fusion is performed on the trust degree of the service provider node in each domain;

2.2.3) Query the blockchain to obtain the reputation value of the service provider node in the previous time window, and calculate the final reputation value of the hth time window.

In the hth time window, the reputation calculation expression of the service providing node sp _j is

in, and /> Indicates the final reputation value of the hth time window and the h-1th time window service provider node; /> Indicates the weight information of the trust value of each domain when inter-domain trust fusion; |sp _j →A(xi ₎ | ^h indicates the number of interactions between sp _j and nodes in domain A(xi ₎ in the hth time window; μ ₁ , 1-μ ₁ represent the weight of the trust calculated in the current time window and the weight of the reputation value at the previous moment respectively.

Example 2

Embodiment 1 above provides a multi-dimensional trust evaluation method for edge computing based on blockchain, and correspondingly, this embodiment provides a multi-dimensional trust evaluation system for edge computing based on blockchain. The system provided in this embodiment can implement the blockchain-based edge computing multi-dimensional trust evaluation method of Embodiment 1, and the system can be implemented by software, hardware, or a combination of software and hardware. For example, the system may include integrated or separate functional modules or functional units to execute corresponding steps in the methods of Embodiment 1. Since the system of this embodiment is basically similar to the method embodiment, the description process of this embodiment is relatively simple. For relevant information, please refer to the part of the description of Embodiment 1. The embodiment of the system provided by this embodiment is only illustrative .

The blockchain-based edge computing multi-dimensional trust evaluation system provided in this embodiment includes:

The architecture determination module is used to determine the blockchain-based distributed IoT edge computing architecture;

The trust evaluation module is used to establish a trust evaluation model based on the determined blockchain-based distributed IoT edge computing architecture, and perform intra-domain trust evaluation and inter-domain trust fusion and reputation calculation for the nodes that provide services after the service ends. The domain trust value and final reputation value of each service provider node are obtained, which are used for the service request node to select a better service provider node.

Example 3

This embodiment provides a processing device corresponding to the blockchain-based edge computing multi-dimensional trust evaluation method provided in Embodiment 1. The processing device may be a processing device for a client, such as a mobile phone, a notebook computer, a tablet computer, Desktop computer etc., to carry out the method of embodiment 1.

The processing device includes a processor, a memory, a communication interface and a bus, and the processor, the memory and the communication interface are connected through the bus to complete mutual communication. A computer program that can run on the processor is stored in the memory, and the processor executes the blockchain-based edge computing multi-dimensional trust evaluation method provided in Embodiment 1 when running the computer program.

In some embodiments, the memory may be a high-speed random access memory (RAM: Random Access Memory), and may also include a non-volatile memory, such as at least one disk memory.

In some other embodiments, the processor may be a central processing unit (CPU), a digital signal processor (DSP) and other types of general-purpose processors, which are not limited herein.

Example 4

The blockchain-based multi-dimensional trust evaluation method for edge computing in Embodiment 1 can be embodied as a computer program product, and the computer program product can include a computer-readable storage medium loaded with a method for executing the method described in Embodiment 1. Computer-readable program instructions for a blockchain-based edge computing multi-dimensional trust assessment method.

A computer readable storage medium may be a tangible device that holds and stores instructions for use by an instruction execution device. A computer readable storage medium may be, for example, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination of the above.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the present invention can still be Any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention shall fall within the protection scope of the claims of the present invention.

Claims (10)

1. A blockchain-based edge computing multidimensional trust evaluation method, characterized in that it comprises the following steps: Determine the blockchain-based distributed IoT edge computing architecture; Based on the determined blockchain-based distributed IoT edge computing architecture, a trust evaluation model is established, and the intra-domain trust evaluation and inter-domain trust fusion and reputation calculation are performed on the nodes that provide services after the service is over, and the information of each service provider node is obtained. Domain trust value and final reputation value. 2. A blockchain-based edge computing multi-dimensional trust evaluation method as claimed in claim 1, wherein the blockchain-based distributed IoT edge computing architecture includes: a domain node layer and an edge server layer; The domain node layer is configured with a plurality of domains divided according to geographical locations, and each domain is configured with a domain management node and several domain nodes. The domain management node and each domain node are connected through an overlay network protocol or an underlying network protocol Communicate with each other; the domain management node is used to regularly collect subjective feedback rating information and objective QoS values in the domain, and after processing these data, obtain trust data and send it to the edge server layer; the domain node is used to provide services to the domain management node Provide the subjective feedback rating information of the node; the service providing node is an edge server or a domain node that can provide services; Several edge servers and blockchains are configured in the edge server layer, and the edge servers are used to provide services to domain nodes and maintain the normal operation of the blockchain. 3. A blockchain-based edge computing multi-dimensional trust evaluation method as claimed in claim 2, wherein the trust evaluation is established based on the determined blockchain-based distributed IoT edge computing architecture In this model, intra-domain trust evaluation and inter-domain trust fusion and reputation calculation are performed on the nodes that provide services after the service ends, and the final reputation value of each service provider node is obtained, including: Based on the expressiveness and stability of the service attribute of the service provider node in each domain, the trust degree of the service provider node in each domain is calculated; Based on the trust degree of the service provider node in each domain, the final reputation value of the service provider node is calculated. 4. A blockchain-based edge computing multi-dimensional trust evaluation method as claimed in claim 3, characterized in that, based on the expressiveness and stability of the service attributes of the service-providing nodes in each domain, the calculated service-providing node Trust in each domain, including: According to the commitment performance level of the service provider node sp _j and the monitoring performance level of the domain management node, the actual performance level of the attribute of the service provider node sp _j is calculated; Integrate the collected information on the actual performance level of each attribute, and calculate the performance and stability of each service attribute of the service provider node in the entire domain; An adaptive attribute weight mechanism is constructed, and based on the performance and stability of each service attribute of the service provider node in the entire domain, the intra-domain trust degree of the service provider node is calculated. 5. A blockchain-based edge computing multi-dimensional trust evaluation method as claimed in claim 4, characterized in that the collected information on the actual performance level of each attribute is integrated, and the service provider node in the entire domain Calculate the performance and stability of each service attribute, including: Use probabilistic language elements to represent the performance of each attribute of the service provider node in the entire domain; Based on the representation of each attribute performance of the service provider node in the entire domain, calculate the attribute expressiveness of the service provider node; Based on the information entropy, the calculation service provides the attribute stability of the node. 6. A blockchain-based edge computing multi-dimensional trust evaluation method as claimed in claim 3, wherein the final reputation value of the service provider node is calculated based on the trust degree of the service provider node in each domain, include: Calculate the weight information based on the number of interactions of the service provider in each domain; According to the weight information, inter-domain trust fusion is performed on the trust degree of the service provider node in each domain; Query the blockchain to obtain the reputation value of the service provider node in the previous time window, and calculate the final reputation value of the service provider node in the hth time window. 7. A blockchain-based edge computing multidimensional trust assessment method according to claim 6, wherein the hth time window service provides the final reputation value of the node for: in, and /> Indicates the final reputation value of the h-th time window and the h-1th time window service provider node; T ^h (A( _xi ), sp _j ) means that the service provider sp _j in the h-th time window, in domain A ( _xi ) trust degree; /> Indicates the weight information of the trust value of each domain when inter-domain trust fusion; |so _j →A(x _j )| ^h indicates the number of interactions between sp _j and nodes in domain A(x _i ) in the hth time window ; μ ₁ , 1-μ ₁ represent the trust weight calculated in the current time window and the weight of the reputation value in the previous moment respectively. 8. A blockchain-based edge computing multi-dimensional trust evaluation system, characterized in that it includes: The architecture determination module is used to determine the blockchain-based distributed IoT edge computing architecture; The trust evaluation module is used to establish a trust evaluation model based on the determined blockchain-based distributed IoT edge computing architecture, and perform intra-domain trust evaluation and inter-domain trust fusion and reputation calculation on the nodes that provide services after the service ends. Obtain the domain trust value and final reputation value of each service provider node. 9. A computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform Any one of the methods described in 1 to 7. 10. A computing device, comprising: one or more processors, memory, and one or more programs, wherein one or more programs are stored in the memory and configured as the one or more The one or more programs include instructions for executing any one of the methods as claimed in claims 1-7.