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

Abstract

The application relates to a kind of multi-dimensional trust evaluation method and system based on edge computing of blockchain, comprising: determining the distributed Internet of Things edge computing architecture based on blockchain;Based on the determined distributed Internet of Things edge computing architecture based on blockchain, a trust evaluation model is established, the nodes providing services after service are evaluated within the domain, and the trust fusion and reputation calculation between domains are carried out, to obtain the final reputation value of each service providing node.The application carries out multi-dimensional trust evaluation on service providing nodes as a whole, obtains a lightweight and scalable trusted evaluation model suitable for the Internet of Things edge computing environment, processes and integrates the evaluation feedback information and QoS performance level within the domain by means of uncertainty theory, measures the credibility of service from two indexes of performance degree and stability, which can accurately describe the performance of service, and also can depict the dynamics and uncertainty of service performance.The application can be widely applied in the technical field of Internet of Things.

Description

TECHNICAL FIELD

[0001] The application relates to a blockchain-based edge computing multi-dimensional trust evaluation method and system, and belongs to the technical field of Internet of Things. BACKGROUND

[0002] With the popularization of 5G technology, the number of Internet of Things terminal nodes increases sharply, and due to the resource constraints of terminal nodes and the dynamic nature of network environment, it is a great challenge to establish one-to-one accurate trust evaluation in the Internet of Things edge computing environment. Many researchers have proposed a blockchain-based trust evaluation model in the Internet of Things environment, which regards trust as a whole, and the trust value corresponds to a binary experience (i.e. positive or negative), which may produce inaccurate evaluation results in many cases, and does not consider the dynamic nature of the network environment. Some researchers claim that more accurate reasoning can be provided for decision-making by considering trust as a combination of multiple trust attributes. Some researchers claim that a trusted service should meet the requirements of the requesting node, and its performance should be stable, that is, its time series objective QoS data and subjective feedback rating from the requesting node should have good central tendency, narrow variation range and low variation frequency. However, it is difficult to cover the above three features in the traditional Internet of Things trust evaluation system.

[0003] At present, existing trust evaluation models can be divided into centralized models and decentralized models. In the decentralized trust evaluation mechanism, the terminal node evaluates the trust value of the node it interacts with, which increases the burden of resource-constrained terminal nodes. The centralized trust management model usually relies on a third-party trust management center to evaluate and store the trust values of the end nodes in the entire network, which may cause the trust evaluation to be opaque, delayed, congested and even single-point failure. SUMMARY

[0004] In view of the above problems, the purpose of the present application is to provide a blockchain-based edge computing multi-dimensional trust evaluation method and system, which constructs a multi-dimensional trust evaluation model suitable for dynamic Internet of Things edge computing environment with blockchain as the interaction mode under the conditions of accurate trust demand and resource constraints, which is of great significance for risk prevention, service selection, recommendation and decision-making.

[0005] To achieve the above purpose, the present application adopts the following technical scheme:

[0006] In a first aspect, the present application provides a blockchain-based edge computing multi-dimensional trust evaluation method, comprising the following steps:

[0007] determining a distributed Internet of Things edge computing architecture based on blockchain;

[0008] Based on a defined blockchain-based distributed IoT edge computing architecture, a trust assessment model is established to perform intra-domain trust assessment and inter-domain trust fusion and reputation calculation on the service-providing nodes after the service ends, so as to obtain the domain trust value and final reputation value of each service-providing node.

[0009] Furthermore, the blockchain-based distributed IoT edge computing architecture includes: a domain node layer and an edge server layer;

[0010] The domain node layer is configured with multiple domains divided according to geographical location. Each domain has a domain management node and several domain nodes. The domain management node and the domain nodes communicate with each other through overlay network protocols or underlying network protocols. The domain management node is used to periodically collect subjective feedback rating information and objective QoS values ​​within the domain, and after processing these data, it obtains trusted data and sends it to the edge server layer. The domain nodes are used to provide subjective feedback rating information of service-providing nodes to the domain management node. The service-providing nodes are edge servers or domain nodes capable of providing services.

[0011] The edge server layer is configured with several edge servers and a blockchain. The edge servers are used to provide services to domain nodes and maintain the normal operation of the blockchain.

[0012] Furthermore, based on the established blockchain-based distributed IoT edge computing architecture, a trust assessment model is established to perform intra-domain trust assessment and inter-domain trust fusion and reputation calculation on the nodes that provided services after the service ends, obtaining the final reputation value of each service-providing node, including:

[0013] Based on the performance and stability of the service attributes of the service provider nodes in each domain, the trust level of the service provider nodes in each domain is calculated.

[0014] The final reputation value of the service provider node is calculated based on its trust level in each domain.

[0015] Furthermore, the calculation of the trust level of the service provider node in each domain based on the performance and stability of its service attributes includes:

[0016] According to the service provider node sp j The service provider node's performance level is calculated based on its commitment performance level and the monitoring performance level of the domain service nodes. j The actual performance level of the attribute;

[0017] The collected information on the actual performance levels of each attribute is integrated, and the performance and stability of each service attribute of the service provider node in the entire domain are calculated.

[0018] An adaptive attribute weight mechanism is constructed, and the trust degree of the service providing node in the domain is calculated based on the performance degree and stability of each service attribute of the service providing node in the entire domain.

[0019] Further, the collected attribute actual performance level information is integrated, and the performance degree and stability of each service attribute of the service providing node in the entire domain are calculated, including:

[0020] The performance of each attribute of the service providing node in the entire domain is represented by using a probability language element;

[0021] Based on the representation of the performance of each attribute of the service providing node in the entire domain, the attribute performance degree of the service providing node is calculated;

[0022] Based on information entropy, the attribute stability of the service providing node is calculated.

[0023] Further, the final reputation value of the service providing node is calculated based on the trust degree of the service providing node in each domain, including:

[0024] According to the number of interactions of the service provider in each domain, weight information is calculated;

[0025] According to the weight information, the trust degrees of the service providing node in each domain are fused between domains;

[0026] The reputation value of the service providing node in the last time window is obtained by querying the blockchain, and the final reputation value of the service providing node in the hth time window is calculated.

[0027] Further, the final reputation value of the service providing node in the hth time window is :

[0028]

[0029]

[0030] wherein, and represent the final reputation values of the service providing node in the hth time window and the h-1th time window; T h (A(x i ),sp j ) represents the trust degree of the service providing node sp j in the hth time window in the domain A(x i ); represents the weight information of each domain trust value when the inter-domain trust is fused; |sp j →A(x i )| h represents sp jThe number of interactions of the node in the domain A (x i ) in the hth time window; μ1,1-μ1 respectively represent the weight of the trust calculated in the current time window and the weight of the reputation value at the last time.

[0031] In a second aspect, the present application provides a multi-dimensional trust evaluation system for edge computing based on a blockchain, comprising:

[0032] An architecture determination module for determining a blockchain-based distributed Internet of Things edge computing architecture;

[0033] A trust evaluation module for establishing a trust evaluation model based on the determined blockchain-based distributed Internet of Things edge computing architecture, performing intra-domain trust evaluation and inter-domain trust fusion and reputation calculation on the nodes providing services after the services are completed, and obtaining the final reputation value of each service providing node for the service request node to select a better service providing node.

[0034] In a third aspect, the present application 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 perform any of the methods.

[0035] In a fourth aspect, the present application provides a computing device comprising one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for performing any of the methods.

[0036] The present application has the following advantages due to the above technical solutions:

[0037] (1) The present application proposes to evaluate the trust of service providing nodes in multiple dimensions as a whole in a domain, realizing a lightweight, scalable and trusted evaluation model suitable for the Internet of Things edge computing environment.

[0038] (2) The present application processes and integrates the evaluation feedback information and QoS performance levels in the domain by means of uncertainty theory (hesitant fuzzy set theory), measures the trustworthiness of the service from two indicators of performance and stability, which can not only accurately describe the performance of the service, but also depict the dynamics and uncertainty of the service performance.

[0039] (3) The present application proposes an adaptive attribute weight mechanism, which associates the weight of each attribute with the number of feedbacks of the nodes in the domain to more accurately measure the overall performance of the service providing node

[0040] (4) The application realizes rapid verification of node identity data, tamper-proofing of trust evidence, cross-domain sharing of trust data and fusion of domain-inter-domain trust data by means of the blockchain smart contract technology.

[0041] Therefore, the application can be widely applied to the field of Internet of Things technology. BRIEF DESCRIPTION OF DRAWINGS

[0042] 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 embodiments. The accompanying drawings are included to provide a description of preferred embodiments, and are not meant to limit the present application. Throughout the drawings, the same reference designates the same elements. In the drawings:

[0043] Figure 1 is a blockchain-based architecture diagram in the embodiments of the application;

[0044] Figure 2 is an edge computing trust evaluation framework diagram in the embodiments of the application. DETAILED DESCRIPTION

[0045] In order to make the objects, technical solutions and advantages of the embodiments of the application clearer, the technical solutions of the embodiments of the application will be described clearly and completely below with reference to the drawings of the embodiments of the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments of the application. Based on the described embodiments of the application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the application.

[0046] It should be noted that the terms used herein are only intended to describe specific embodiments, and are not intended to limit the exemplary embodiments according to the present application. As used herein, the singular form is intended to include the plural form unless the context clearly indicates otherwise, and furthermore, it should be understood that when the terms "comprise" and / or "include" are used in the specification, there is a presence of a feature, step, operation, device, component and / or combinations thereof.

[0047] In a heterogeneous Internet of Things 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 containing multiple attributes. In some embodiments of the present application, a blockchain-based edge computing multi-dimensional trust evaluation method is provided, which adopts a combination of centralized and decentralized trust evaluation, and realizes the authentication of node identity, automatic evaluation and sharing of trust data with the help of blockchain technology. First, terminal nodes with similar positions are divided into a domain, and the performance of the service providing node is evaluated as a whole. Each domain selects a node with strong resource capability as a domain administrator (DA), which periodically collects the performance data of each attribute of the service providing node in the domain (subjective feedback of the requesting node and QoS actual performance level), and then converts it into the form of probabilistic linguistic elements (PLEs). This representation method takes into account both qualitative variables and their distribution attributes, and can better reflect the dynamics and uncertainty of service performance. Then the performance degree of each attribute of the service providing node in the domain is calculated, and the stability of each attribute is calculated based on information entropy theory. The performance of each attribute is measured by the two indicators of performance degree and stability. Secondly, an adaptive attribute weight mechanism is proposed, which determines the weight of each attribute based on the number of feedbacks of each attribute of the service providing node in the domain, and calculates the trust value of the service providing node in each domain. Finally, the trust values of the service providing node in each domain are weighted, and the reputation value of the service providing node at the last time is queried from the blockchain to obtain the current reputation value of the service providing node.

[0048] Correspondingly, some other embodiments of the present application provide a blockchain-based edge computing multi-dimensional trust evaluation system, device and storage medium.

[0049] Embodiment 1

[0050] As shown in Figure 1 , Figure 2 The present embodiment provides a blockchain-based edge computing multi-dimensional trust evaluation method, which includes the following steps:

[0051] 1) Determine the blockchain-based distributed Internet of Things edge computing architecture.

[0052] As shown in Figure 1As shown, in the distributed Internet of Things edge computing architecture adopted by the embodiment, it is divided into an edge server layer and a domain node layer. The edge server layer is configured with a plurality of edge servers and a blockchain maintained by the edge servers. The domain node layer is configured with a plurality of domains divided according to geographical positions, each of which is configured with a domain management node (DA) and a plurality of domain nodes. The domain management nodes and the domain nodes communicate with each other through an overlay network protocol or an underlying network protocol.

[0053] Specifically, the four components involved in the architecture, i.e., the edge server, the domain node, the domain management node, and the blockchain, are introduced below.

[0054] Domain node: refers to a fixed or mobile node requesting service in a specific geographical location. Due to resource limitations, these domain nodes act as clients of the blockchain, only retaining the Merkle root of the blockchain. After interacting with the service providing node, the domain node provides the domain management node with subjective feedback rating information of the service providing node. The service providing node refers to a node that can provide services, including edge servers and domain nodes with strong resource capabilities that can provide services, which can provide services within the domain or across domains.

[0055] Domain management node (DA): refers to a fixed node in the domain with strong computing and storage capabilities, which 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 (quality of service) values within the domain, then processing these trust data and submitting them to the blockchain for further processing. In addition, it is also responsible for QoS performance monitoring within the domain.

[0056] Edge server: refers to a fixed server with strong computing and storage capabilities. These edge servers are usually located near base stations and can provide services to other requesting nodes, and are responsible for maintaining the normal operation of the blockchain, which acts as a full node of the blockchain and is responsible for verification.

[0057] Blockchain: the blockchain has the advantage of high reliability due to its consensus mechanism and identical distributed storage copies. The present application applies blockchain technology to the distributed Internet of Things edge computing architecture, thereby significantly enhancing the security of the edge computing network.

[0058] The trust data submitted by all domains within a certain period of time is saved in a block, that is, 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 to form a block chain. The format of various transaction data in the block chain is shown in Table 1. ID represents the transaction number, and the transaction type is composed of TE (trust evidence), QC (QoS performance), IR (identity registration), and LTV (local trust value update). In addition to the smart contract, various transactions are packaged into blocks for storage through the data format shown in Table 1. Once these transactions are packaged into blocks, they cannot be tampered with or deleted.

[0059] Table 1: Transaction data format

[0060]

[0061] 2) Based on the determined blockchain-based distributed Internet of Things edge computing architecture, a trust evaluation model is established to perform intra-domain trust evaluation and cross-domain trust fusion and reputation calculation on the nodes providing services after the service ends, so as to obtain the final reputation value of each service providing node, which is used for the service request node to select a better service providing node.

[0062] 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 indexes of performance degree and stability degree. The other layer is cross-domain trust fusion and reputation evaluation, that is, the trust values of the service providing node in each domain are fused in the hth time window, and then the reputation value of the service providing node in the last time window is queried from the block chain to obtain the final reputation value in the hth time window.

[0063] 2.1) Based on the performance degree and stability degree of the service providing node in each domain, the trust degree of the service providing node in each domain is calculated.

[0064] In order to more accurately measure the service trustworthiness, the application constructs two indexes to evaluate the trust degree of the service providing node. The first one is performance degree, mainly used to measure the performance of each attribute, and the second one is stability degree, mainly used to measure the dynamicity and uncertainty of each attribute. The specific evaluation process is as follows:

[0065] 2.1.1) According to the commitment performance level of the service providing node sp j and the monitoring performance level of the domain management node, the actual performance level of the attribute of the service providing node sp j is calculated.

[0066] The actual performance level of the attribute of the service providing node sp jThe attribute monitoring performance level of the service providing node is compared with the commitment performance level of the service providing node, and the attribute actual performance level of the service providing node in providing the service is calculated, and the calculation formula is:

[0067]

[0068] wherein, represents the attribute actual performance level of the service providing node sp j in providing the service to the domain node A(x i , y k ) in the hth time window. represents the performance level promised by the service providing node sp j to the domain node A(x i , y k ). represents the attribute actual performance level of the service providing node sp j in providing the service to the domain node A(x i , y k ) in the hth time window.

[0069] 2.1.2) The attribute actual performance level information collected in step 2.1.1) is integrated, and the performance degree and stability degree of each service attribute of the service providing node in the entire domain are calculated.

[0070] Specifically, the following steps are included:

[0071] 2.1.2.1) The performance of each attribute of the service providing node in the entire domain is represented by using a probability language element.

[0072] In order to accurately aggregate the feedback information of each request node in the domain, while considering the qualitative variables and their distribution characteristics, the present application uses a probability language element (PLE) to represent the performance of the service providing node in providing the service attribute. The probability language element (PLE) is defined as follows:

[0073] Definition 1. Assuming that S={s α |α=1,2,...,τ} is a language term set, a probability language variable (PLE) is wherein s l (p l ) is a language term variable s l and a corresponding probability p l , and #L(p) is the number of language terms in L(p).

[0074] Definition 2. Assuming that S=(s α{ s | s E S, l = 1,..#L(p)}, the expected value of L(p) is: l (p (l) )|s l ∈ S, l = 1,..#L(p)}, the expected value of L(p) is:

[0075]

[0076] where f l is the index of the linguistic term s l .

[0077] Therefore, the performance of each attribute of the service providing node in the whole domain can be represented as:

[0078]

[0079]

[0080] where |s l | represents the number of the request nodes in the domain providing the feedback rating s j for a certain attribute of sp l .

[0081] 2.1.2.2) Based on the representation of the performance of each attribute of the service providing node in the whole domain, the attribute performance degree of the service providing node is calculated.

[0082] where the performance vector of each attribute of the service providing node sp j in the domain A(x i ) in the hth time window is:

[0083]

[0084] where represents the performance of the qth attribute of the service providing node spj in the domain A(x i ) in the hth time window. In order to facilitate subsequent calculation, the attribute performance expressed in PLE is converted into numerical representation using formula (1) as shown in the following formula

[0085]

[0086] 2.1.2.3) Based on information entropy, the attribute stability degree of the service providing node is calculated.

[0087] 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 exactly meets these conditions. Information entropy represents the measure of the degree of order of the system, and the greater the uncertainty of the variable, the greater the information entropy.

[0088] Definition 3. Assume the probability language element is: The information entropy of L(p) is defined as

[0089]

[0090] where z is set to 1.28.

[0091] The stability calculation formula is

[0092] st(L(p)) = τ * (1 - H(L(p))) (7)

[0093]

[0094] where τ represents an adaptive adjustment factor, which depends on the size of E(L(p)). It can prevent some service providing nodes with high stability but poor performance from obtaining a high trust value. 0≤β≤1 is used to control the minimum value of τ. When β is fixed, the closer E(L(p) is to 1, the larger the value of τ. When calculating the local trust value, the weight of stability can be increased by adjusting β when the proportion of malicious services is high or the network environment is unstable. Δ>0 represents a constant used to adjust the descending rate of the function curve. Therefore, we can get which represents sp j The stability of the qth attribute in domain A(x i ) in the hth time window.

[0095] 2.1.3) An adaptive attribute weight mechanism is constructed, and the domain trust of the service providing node is calculated based on the performance degree and stability of the service providing node in each service attribute in the entire domain.

[0096] where the domain trust of the service providing node sp j The trust of A(x i ) in the hth time window is represented as:

[0097]

[0098] where σ1 and (1-σ1) represent the weights of the performance degree and the stability degree, respectively, represents the weight of the qth attribute in the hth time window. The basic idea is that the more times the domain evaluates a certain attribute, the more the request node in the domain values the attribute.

[0099]

[0100] where represents the number of feedbacks of the qth attribute submitted by sp i to A(x j ) in the hth time window.

[0101] 2.2) Based on the trust degree of the service providing node in each domain, the final reputation value of the service providing node is calculated.

[0102] Specifically, the following steps are included:

[0103] 2.2.1) According to the number of interactions of the service provider in each domain, the weight information is calculated;

[0104] 2.2.2) According to the weight information, the trust degree of the service providing node in each domain is fused between domains;

[0105] 2.2.3) Query the blockchain to obtain the reputation value of the service providing node in the last time window, and calculate the final reputation value in the hth time window.

[0106] In the hth time window, the service providing node sp j The reputation calculation expression is

[0107]

[0108]

[0109] wherein, and represent the final reputation value of the service providing node in the hth time window and the h-1th time window; represents the weight information of the trust value of each domain when the trust between domains is fused; |sp j → A(x i )| h represents the number of interactions of sp j with the nodes in the domain A(x i ) in the hth time window; μ1,1-μ1 respectively represent the weight of the trust calculated in the current time window and the weight of the reputation value at the last time.

[0110] Embodiment 2

[0111] The above embodiment 1 provides a multi-dimensional trust evaluation method for edge computing based on blockchain. Correspondingly, the present embodiment provides a multi-dimensional trust evaluation system for edge computing based on blockchain. The system provided by the present embodiment can implement the multi-dimensional trust evaluation method for edge computing based on blockchain of embodiment 1. The system can be realized by software, hardware or a combination of software and hardware. For example, the system can include integrated or separate functional modules or functional units to perform the corresponding steps in the methods of embodiment 1. Since the system of the present embodiment is basically similar to the method embodiment, the description process of the present embodiment is relatively simple, and the related parts can be referred to the part of the description of embodiment 1. The system provided by the present embodiment is only illustrative.

[0112] The blockchain-based edge computing multi-dimensional trust evaluation system provided by the embodiment comprises:

[0113] An architecture determination module is configured to determine a blockchain-based distributed Internet of Things edge computing architecture.

[0114] A trust evaluation module is configured to establish a trust evaluation model based on the determined blockchain-based distributed Internet of Things edge computing architecture, perform intra-domain trust evaluation and inter-domain trust fusion and reputation calculation on the nodes providing services after the services are ended, and obtain the domain trust values and final reputation values of the service providing nodes, which are used for the service request nodes to select better service providing nodes.

[0115] Embodiment 3

[0116] The embodiment provides a processing device corresponding to the blockchain-based edge computing multi-dimensional trust evaluation method provided in the embodiment 1, and the processing device can be a processing device for a client, such as a mobile phone, a notebook computer, a tablet computer, a desktop computer, etc., to execute the method of the embodiment 1.

[0117] The processing device comprises a processor, a memory, a communication interface and a bus, the processor, the memory and the communication interface are connected through the bus to complete the communication between each other. The memory stores a computer program that can run on the processor, and the processor executes the blockchain-based edge computing multi-dimensional trust evaluation method provided in the embodiment 1 when the computer program is run.

[0118] In some embodiments, the memory can be a high-speed random access memory (RAM) and can also include a non-volatile memory, such as at least one disk memory.

[0119] In other embodiments, the processor can be a central processing unit (CPU), a digital signal processor (DSP) or various types of general-purpose processors, which are not limited here.

[0120] Embodiment 4

[0121] The blockchain-based edge computing multi-dimensional trust evaluation method of the embodiment 1 can be specifically implemented as a computer program product, and the computer program product can include a computer readable storage medium, which is loaded with computer readable program instructions for executing the blockchain-based edge computing multi-dimensional trust evaluation method described in the embodiment 1.

[0122] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0123] It should be noted that the above-mentioned embodiments are only used to illustrate but not to limit the technical solutions of the present application. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and any modification or equivalent replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A method for multi-dimensional trust evaluation of edge computing based on blockchain, characterized in that The method comprises the following steps: determining a blockchain-based distributed Internet of Things edge computing architecture, comprising: The blockchain-based distributed Internet of Things edge computing architecture comprises a domain node layer and an edge server layer; The domain node layer is configured with a plurality of domains divided according to geographical positions, each domain is configured with a domain management node and a plurality of domain nodes, and the domain management node and each domain node communicate with each other through an overlay network protocol or an underlying network protocol; the domain management node is used for periodically collecting subjective feedback rating information and objective QoS values in the domain, and sending trust data obtained by processing the data to the edge server layer; the domain node is used for providing subjective feedback rating information of a service providing node to the domain management node; the service providing node is an edge server or a domain node capable of providing services; The edge server layer is configured with a plurality of edge servers and a blockchain, and the edge server is used for providing services to the domain node and maintaining normal operation of the blockchain; based on the determined blockchain-based distributed Internet of Things edge computing architecture, a trust evaluation model is established to perform domain trust evaluation, domain trust fusion and reputation calculation on the nodes providing services after the services, and obtain domain trust values and final reputation values of each service providing node, comprising: Based on the performance degree and stability degree of the service providing node in each domain, the trust degree of the service providing node in each domain is calculated. Based on the trust degree of the service providing node in each domain, the final reputation value of the service providing node is calculated. 2.The blockchain-based edge computing multi-dimensional trust evaluation method of claim 1, wherein, The trust degree of the service providing node in each domain is calculated based on the performance degree and stability degree of the service providing node in each domain, comprising: According to the commitment performance level of the service providing node and the monitoring performance level of the domain management node, the attribute actual performance level of the service providing node is calculated. The collected attribute actual performance level information is integrated, and the performance degree and stability degree of each service attribute of the service providing node in the entire domain are calculated; An adaptive attribute weight mechanism is constructed, and the domain trust degree of the service providing node is calculated based on the performance degree and stability degree of each service attribute of the service providing node in the entire domain. 3.The blockchain-based edge computing multi-dimensional trust evaluation method of claim 2, wherein, The collected attribute actual performance level information is integrated, and the performance degree and stability degree of each service attribute of the service providing node in the entire domain are calculated, comprising: The performance of each attribute of the service providing node in the entire domain is represented by using a probability language element; Based on the representation of the performance of each attribute of the service providing node in the entire domain, the attribute performance degree of the service providing node is calculated; Based on information entropy, the attribute stability degree of the service providing node is calculated. 4.The blockchain-based edge computing multi-dimensional trust evaluation method of claim 1, wherein, The final reputation value of the service providing node is calculated based on the trust degree of the service providing node in each domain, comprising: According to the number of interactions of the service provider in each domain, weight information is calculated; According to the weight information, the trust degree of the service providing node in each domain is fused in the domain; The reputation value of the service providing node in the last time window is obtained by querying the blockchain, and the final reputation value of the service providing node in the hth time window is calculated. 5.The blockchain-based edge computing multi-dimensional trust evaluation method of claim 4, wherein, the final reputation value of the h-th time window service providing node is: wherein, and represents the final reputation value of the service providing node in the hth time window and the (h-1)th time window; represents the service providing node in the hth time window, the trust degree of the domain ; represents the weight information of the trust value of each domain when the inter-domain trust is fused; represents the interaction times of the nodes in the domain in the hth time window; respectively represent the weight of the trust calculated in the current time window and the weight of the reputation value at the last time. 6.A blockchain-based edge computing multi-dimensional trust evaluation system, characterized in that, comprising: an architecture determination module, configured to determine a blockchain-based distributed Internet of Things edge computing architecture, comprising: The blockchain-based distributed Internet of Things edge computing architecture comprises a domain node layer and an edge server layer. The domain node layer is configured with a plurality of domains divided according to geographical positions, each domain is configured with a domain management node and a plurality of domain nodes, the domain management node and each domain node communicate with each other through an overlay network protocol or an underlying network protocol; the domain management node is used for collecting subjective feedback rating information and objective QoS values in the domain regularly, and sending trust data obtained by processing these data to the edge server layer; the domain node is used for providing subjective feedback rating information of a service providing node to the domain management node; the service providing node is an edge server or a domain node capable of providing services; The edge server layer is configured with a plurality of edge servers and a blockchain, the edge server is used for providing services to the domain node and maintaining normal operation of the blockchain; A trust evaluation module is used for establishing a trust evaluation model based on the determined blockchain-based distributed Internet of Things edge computing architecture, performing domain trust evaluation, domain trust fusion and reputation calculation on the nodes providing services after the services, obtaining domain trust values and final reputation values of each service providing node, comprising: Based on the performance degree and stability degree of the service providing node in each domain, the trust degree of the service providing node in each domain is calculated. Based on the trust degree of the service providing node in each domain, the final reputation value of the service providing node is calculated.

7. A computer-readable storage medium storing one or more programs, the one or more programs comprising instructions that when executed by a computer cause the computer to perform a method of any of claims 1-6. The one or more programs include instructions that when executed by a computing device cause the computing device to perform any of the methods of claims 1-5.

8. A computing device, comprising: Comprise: One or more processors, memories and one or more programs, wherein one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprise instructions for executing any of the methods of claims 1-5.

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