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

Block chain-based edge computing multidimensional trust evaluation method and system Download PDF

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CN116668450A
CN116668450A CN202310290575.0A CN202310290575A CN116668450A CN 116668450 A CN116668450 A CN 116668450A CN 202310290575 A CN202310290575 A CN 202310290575A CN 116668450 A CN116668450 A CN 116668450A
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王艳
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Ningbo University of Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/104—Peer-to-peer [P2P] networks
    • H04L67/1044—Group management mechanisms 
    • H04L67/1053—Group management mechanisms  with pre-configuration of logical or physical connections with a determined number of other peers
    • H04L67/1057—Group management mechanisms  with pre-configuration of logical or physical connections with a determined number of other peers involving pre-assessment of levels of reputation of peers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
    • H04L67/10015—Access to distributed or replicated servers, e.g. using brokers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/104—Peer-to-peer [P2P] networks
    • H04L67/1061—Peer-to-peer [P2P] networks using node-based peer discovery mechanisms
    • H04L67/1068—Discovery involving direct consultation or announcement among potential requesting and potential source peers
    • H04L67/107—Discovery involving direct consultation or announcement among potential requesting and potential source peers with limitation or expansion of the discovery scope
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The application relates to a block chain-based edge computing multidimensional trust evaluation method and a system, comprising the following steps: determining a distributed internet of things edge computing architecture based on a blockchain; based on the determined distributed internet of things edge computing architecture based on the blockchain, a trust evaluation model is established, intra-domain trust evaluation and inter-domain trust fusion and reputation computation are carried out on the nodes providing the service after the service is finished, and the final reputation value of each service providing node is obtained. According to the application, the domain is taken as a whole to carry out multidimensional trust evaluation on the service providing node, a lightweight extensible trust evaluation model suitable for the edge computing environment of the Internet of things is obtained, evaluation feedback information and QoS expression level in the domain are processed and integrated by means of uncertainty theory, the reliability of the service is measured from two indexes of expression and stability, the performance of the service can be accurately described, and meanwhile, the dynamic property and the uncertainty of the service performance can be described. The method and the device can be widely applied to the technical field of the Internet of things.

Description

Block chain-based edge computing multidimensional trust evaluation method and system
Technical Field
The application relates to a block chain-based edge computing multidimensional trust evaluation method and system, and belongs to the technical field of Internet of things.
Background
With the popularization of 5G technology, the number of terminal nodes of the internet of things increases dramatically, and because of the resource limitation of the terminal nodes and the dynamic nature of the network environment, establishing a one-to-one accurate trust evaluation in the edge computing environment of the internet of things is a great challenge. Many researchers have proposed a blockchain-based trust assessment model in an internet of things environment that treats trust as a whole, with trust values corresponding to binary experiences (i.e., positive or negative), which in many cases may produce inaccurate assessment results, and does not take into account the dynamics of the network environment. Some researchers claim that more accurate reasoning can be provided for decisions by treating trust as a combination of multiple trusted attributes. Still other researchers claim that trusted services should meet the requirements of the requesting node, their performance should be stable, that is, their time series objective QoS data and subjective feedback ratings from the requesting node should have good central trends, narrow ranges of variation and low frequency of variation. However, in the conventional internet of things trust evaluation system, it is difficult to cover the above three features.
Currently, 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 interacted with the terminal node, and the burden of the resource-limited terminal node is increased. Whereas centralized trust management models typically rely on third party trust management centers to evaluate and store trust values for end nodes throughout the network, this can result in opacity, delay, congestion, and even a single point of failure of the trust evaluation.
Disclosure of Invention
Aiming at the problems, the application aims to provide a multi-dimensional trust evaluation method and a system for edge calculation based on a blockchain.
In order to achieve the above purpose, the present application adopts the following technical scheme:
in a first aspect, the present application provides a blockchain-based edge computation multidimensional trust assessment method, comprising the steps of:
determining a distributed internet of things edge computing architecture based on a blockchain;
based on the determined distributed internet of things edge computing architecture based on the blockchain, a trust evaluation model is established, intra-domain trust evaluation and inter-domain trust fusion and reputation computation are carried out on the nodes providing the service after the service is finished, and the domain trust value and the final reputation value of each service providing node are obtained.
Further, the blockchain-based distributed internet of things edge computing architecture includes: a domain node layer and an edge server layer;
the domain node layer is internally provided with a plurality of domains divided according to geographic positions, each domain is internally provided with a domain management node and a plurality of domain nodes, and the domain management nodes and the domain nodes are communicated with each other through an overlay network protocol or a bottom network protocol; the domain management node is used for periodically collecting subjective feedback rating information and objective QoS values in the domain, processing the subjective feedback rating information and the objective QoS values to obtain trust data, and sending the trust data to the edge server layer; the domain node is used for providing subjective feedback rating information of the service providing node for the domain management node; the service providing node is an edge server or domain node capable of providing service;
and a plurality of edge servers and blockchains are configured in the edge server layer, and the edge servers are used for providing services for domain nodes and maintaining normal operation of the blockchains.
Further, based on the determined edge computing architecture of the distributed internet of things based on the blockchain, a trust evaluation model is established, intra-domain trust evaluation and inter-domain trust fusion and reputation computation are performed on the nodes providing the service after the service is finished, and a final reputation value of each service providing node is obtained, including:
based on the expressive degree and the stability of the service attributes of the service providing node in each domain, calculating to obtain the trust degree of the service providing node in each domain;
and calculating to obtain the final credit value of the service providing node based on the trust degree of the service providing node in each domain.
Further, the calculating, based on the performance and stability of the service attribute of the service providing node in each domain, the trust of the service providing node in each domain includes:
according to service providing node sp j And the promise expression level of the domain service node and the monitoring expression level of the domain service node are calculated to obtain the service providing node sp j Is a property actual performance level of (1);
integrating the collected actual performance level information of each attribute, and calculating the performance and stability of each service attribute of the service providing node in the whole domain;
and constructing a self-adaptive attribute weight mechanism, and calculating the intra-domain trust degree of the service providing node based on the performance degree and the stability degree of each service attribute of the service providing node in the whole domain.
Further, the integrating the collected actual performance level information of each attribute, and calculating the performance and stability of each service attribute in the whole domain by the service providing node includes:
the probability language elements are adopted to represent the performances of all the attributes of the service providing nodes in the whole domain;
calculating an attribute performance of the service providing node based on the representation of each attribute performance of the service providing node in the entire domain;
based on the information entropy, the attribute stability of the service providing node is calculated.
Further, based on the trust degree of the service providing node in each domain, a final reputation value of the service providing node is calculated, which comprises the following steps:
calculating weight information according to the interaction times of the service provider in each domain;
carrying out inter-domain trust fusion on the trust degree of the service providing node in each domain according to the weight information;
the query block chain obtains the reputation value of the service providing node of the last time window, and calculates to obtain the final reputation value of the service providing node of the h time window.
Further, the h time window service provides the final reputation value of the nodeThe method comprises the following steps:
wherein , and />Representing final reputation values of the h time window and h-1 time window service providing nodes; t (T) h (A(x i )，sp j ) Representing service providing nodes sp j In the h time window, in the domain a (x i ) Is the confidence level of (2); />When the trust between domains is fused, the weight information occupied by the trust value of each domain is represented; sp (sp) j →A(x i )| h Representing sp j And domain A (x i ) The interaction times of the internal node in the h time window; mu (mu) 1 ，1-μ 1 Respectively representing the weight of trust calculated by the current time window and the weight occupied by the reputation value at the last moment.
In a second aspect, the present application provides a blockchain-based edge computing multidimensional trust assessment system comprising:
the architecture determining module is used for determining a distributed internet of things edge computing architecture based on a blockchain;
the trust evaluation module is used for establishing a trust evaluation model based on the determined distributed internet of things edge computing architecture based on the blockchain, carrying out intra-domain trust evaluation and inter-domain trust fusion and reputation calculation on the nodes providing the service after the service is finished, obtaining the final reputation value of each service providing node, and selecting better service providing nodes by the service request node.
In a third aspect, the present application provides a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform any of the methods.
In a fourth aspect, the present application provides 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 to be executed by the one or more processors, the one or more programs comprising instructions for performing any of the methods.
Due to the adoption of the technical scheme, the application has the following advantages:
(1) The application provides a multi-dimensional trust evaluation for the service providing node by taking the domain as a whole, and realizes a lightweight extensible trust evaluation model suitable for the edge computing environment of the Internet of things.
(2) The application integrates the evaluation feedback information and QoS expression level in the domain by means of uncertainty theory (hesitation fuzzy set theory), and measures the credibility of the service from two indexes of the expression level and the stability, thereby not only accurately describing the performance of the service, but also describing the dynamic property and the uncertainty of the service performance.
(3) The application provides a self-adaptive attribute weight mechanism, which correlates the weight of each attribute with the feedback times of the nodes in the domain to the attribute, and more accurately measures the overall performance of the service providing node
(4) The application realizes the rapid verification of the node identity data, the tamper resistance of trust evidence, the cross-domain sharing of trust data and the fusion of inter-domain trust data by means of the blockchain intelligent contract technology.
Therefore, the method and the device can be widely applied to the technical field of the Internet of things.
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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 drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Like parts are designated with like reference numerals throughout the drawings. In the drawings:
FIG. 1 is a block chain based architecture diagram in an embodiment of the application;
FIG. 2 is a diagram of an edge computing trust evaluation framework in an embodiment of the application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present application. It will be apparent that the described embodiments are some, but not all, embodiments of the application. All other embodiments, which are obtained by a person skilled in the art based on the described embodiments of the application, fall within the scope of protection of the application.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
In heterogeneous internet of things edge computing environments, the diversity of service types results in diversity of evaluation attributes, which is a tremendous effort for building trust evaluation models that contain multiple attributes. In some embodiments of the present application, a multi-dimensional trust evaluation method based on blockchain edge computation is provided, an evaluation mode combining centralized and decentralized trust evaluation is adopted, authentication of node identity is realized by means of blockchain technology, and automatic evaluation and sharing of trust data are realized. First, terminal nodes having similar locations are divided into a domain, and the domain is evaluated as a whole for the performance of service providing nodes. Each domain selects a node with stronger resource capability as a domain management node (domain administrator, DA), periodically collects performance data (subjective feedback and QoS actual performance level of a request node) of each attribute of a service providing node in the domain, then converts the performance data into a form of a probability language element (probabilistic linguistic elements, PLEs), the representation mode considers qualitative variables and distribution attributes thereof at the same time, can better reflect the dynamic property and uncertainty of service performance, calculates the performance degree of each attribute of the service providing node in the domain, calculates the stability of each attribute based on an information entropy theory, measures the performance of each attribute from two indexes of the performance degree and the stability degree, and secondly, provides a self-adaptive attribute weight mechanism to determine each attribute weight based on the feedback times of each attribute of the service providing node in the domain and calculates the trust value of the service providing node in each domain. And finally, weighting the trust value of the service providing node in each domain, and inquiring the blockchain to obtain the reputation value of the service providing node at the last moment, and finally obtaining the current reputation value of the service providing node.
In accordance therewith, further embodiments of the present application provide a blockchain-based edge computing multidimensional trust evaluation system, apparatus and storage medium.
Example 1
As shown in fig. 1 and 2, the present embodiment provides a multi-dimensional trust evaluation method based on edge computation of a blockchain, which includes the following steps:
1) A blockchain-based distributed internet of things edge computing architecture is determined.
As shown in fig. 1, in the distributed internet of things edge computing architecture adopted in this embodiment, the architecture is divided into an edge server layer and a domain node layer. Wherein, a plurality of edge servers and block chains maintained by the edge servers are configured in the edge server layer; a plurality of domains divided according to geographic positions are configured in the domain node layer, and each domain is configured with a domain management node (DA) and a plurality of domain nodes; the domain management node and each domain node communicate with each other via an overlay network protocol or an underlay network protocol.
In particular, four components involved in the architecture, namely edge servers, domain nodes, domain management nodes, and blockchains, are described below, respectively.
Domain node: refers to a fixed or mobile node requesting service within a particular geographic location. Due to resource limitations, these domain nodes act as clients of the blockchain, leaving only the Merkle root of the blockchain. After interacting with the service providing node, the domain node provides subjective feedback rating information of the service providing node to the domain management node. The service providing node refers to a node capable of providing service, and comprises an edge server and a domain node with strong resource capacity and capable of providing service, wherein the service providing node can provide service in a domain and can also provide service in a cross-domain.
Domain management node (DA): a fixed node in the domain with powerful computing power and storage power, which acts as a full node of the blockchain, is also a management node of the whole domain, which is responsible for periodically collecting subjective feedback rating information and objective QoS (quality of service ) values in the domain, and then processing these trust data and submitting them to the blockchain for further processing. In addition, it is responsible for intra-domain QoS performance monitoring.
Edge server: refers to fixed servers with powerful computing and storage capabilities, which are typically located near the base station, can serve other requesting nodes, and are responsible for maintaining the normal operation of the blockchain, which acts as a full node of the blockchain, responsible for authentication.
Blockchain: the blockchain has the advantage of high reliability due to the consensus mechanism and the same distributed storage copy, and the application applies the blockchain technology to the distributed internet of things edge computing architecture, thereby obviously enhancing the security of the edge computing network.
The trust data submitted by all domains is stored in one block for a certain period of time, that is, the trust data of the period of time is placed in the block, and the trust data of the next period of time is placed in the next block to form a blockchain. The format of the various transaction data in the blockchain is shown in table 1 below. The ID represents the transaction number, and the transaction type consists of TE (proof of trust), QC (QoS performance), IR (identity registration), LTV (local trust value update). Except for the smart contracts, various transactions are packaged into blocks for storage in the data format shown in Table 1. Once these transactions are packed into blocks, they cannot be tampered with or deleted.
TABLE 1 transaction data format
2) Based on the determined distributed internet of things edge computing architecture based on the blockchain, a trust evaluation model is established, intra-domain trust evaluation and inter-domain trust fusion and reputation calculation are carried out on the nodes providing the service after the service is finished, and a final reputation value of each service providing node is obtained and is used for the service request node to select a better service providing node.
As shown in fig. 2, the trust evaluation model established in the embodiment is divided into two layers, and the first layer is intra-domain trust evaluation, which can be calculated from two indexes of expressivity and stability; the other layer is cross-domain trust fusion and reputation evaluation, namely fusing trust values of service providing nodes in each domain in an h time window, and then querying a blockchain to obtain the reputation value of the service providing node in the last time window to obtain the final reputation value of the h time window.
2.1 Based on the performance and stability of the service attribute of the service providing node in each domain, the trust degree of the service providing node in each domain is calculated.
In order to more accurately measure service trustworthiness, the present application constructs two metrics to evaluate the trustworthiness of a service providing node. The first is the degree of performance, which is used primarily to measure the performance of each attribute, and the second is the degree of stability, which is used primarily to measure the dynamics and uncertainty of each attribute. The specific evaluation process is as follows:
2.1.1 According to service providing node sp j And the promise expression level of the domain management node and the monitoring expression level of the domain management node, and calculating to obtain the sp of the service providing node j Is a property actual performance level of (c).
By providing nodes sp to services j Comparing the attribute monitoring performance level of the service providing node with the promised performance level of the service providing node, and calculating to obtain the actual performance level of the attribute of the service provided by the service providing nodeThe calculation formula is as follows:
wherein ,representing service providing nodes sp in an h time window j Directional domain node A (x i ，y k ) Providing a monitoring performance level of the attribute at the time of service; />Representing service providing nodes sp j Directional domain node A (x i ，y k ) The committed performance level; />Representing service providing nodes sp in an h time window j Directional domain node A (x i ，y k ) The attribute of the service is provided to actually represent the level.
2.1.2 Integrating the actual performance level information of each attribute collected in the step 2.1.1), and calculating the performance degree and stability of each service attribute of the service providing node in the whole domain.
Specifically, the method comprises the following steps:
2.1.2.1 Using probabilistic language elements to represent the performance of the attributes of the service providing node in the whole domain.
In order to accurately aggregate feedback information of each requesting node in a domain, and consider qualitative variables and distribution characteristics thereof, the application adopts Probability Language Elements (PLEs) to represent the performance of providing service attributes by service providing nodes. Probabilistic Language Elements (PLEs) are defined as follows:
definition 1 assume s= { S α |α=1, 2,..τ } is the set of language terms and the probabilistic language variables (probabilistic linguistic elements, PLEs) are wherein sl (p l ) For the linguistic term variable s l And corresponding probability p l #L (p) is the number of language terms in L (p).
Definition 2 supposing s= (S α |α=1, 2,..τ } is a set of language terms, for the probabilistic language variable L (p) = (s l (p (l) )|s l E S, l=1,.#l (p) }, the expected value of L (p) is:
wherein ,fl Is the language term s l Is a subscript of (2).
Thus, each attribute performance of a service providing node in the entire domain can be expressed as:
wherein ,|sl I indicates that the requesting node provides information about sp within the domain j Is rated s l Is a number of (3).
2.1.2.2 Based on the representation of each attribute performance of the service providing node in the entire domain, calculating an attribute performance of the service providing node.
Wherein the service providing node sp j In the h time window in the domain A (x i ) The expression vector of each attribute in the tree is:
wherein ,indicating that the service providing node spj is in the h time windowIn domain A (x i ) The inner q attribute represents. To facilitate subsequent calculations, the property representation in PLE mode is converted to a numerical representation using equation (1), as shown in the following equation
2.1.2.3 Based on the information entropy, calculating the attribute stability of the service providing node.
Information entropy is used as a measurement tool because it is suitable for measuring uncertainty of information expressed in probability, and information expressed in PLE just satisfies these conditions. The information entropy represents a measure of the degree of order of the system, the greater the uncertainty of the variables, the greater the information entropy.
Definition 3. Assuming probabilistic language elements are:the entropy of L (p) is defined as
Wherein z is set to 1.28.
The stability calculation formula is
st(L(p))＝τ*(1-H(L(p))) (7)
Where τ represents an adaptive adjustment factor, which prevents some highly stable but poorly performing service providing nodes from obtaining a high trust value.0.ltoreq.β.ltoreq.1 for controlling the minimum value of τ depending on the size of E (L (p). When β is fixed, E (p) is closer to 1, τ is largerWhich represents sp j In the h time window, in the domain a (x i ) Stability of the q-th attribute in (c).
2.1.3 An adaptive attribute weight mechanism is constructed, and the intra-domain trust level of the service providing node is calculated based on the performance and stability of each service attribute of the service providing node in the whole domain.
Wherein the service providing node sp j In the h time window, in the domain a (x i ) The confidence level of (2) is expressed as:
wherein ,σ1 and (1-σ1 ) Weights representing performance and stability degrees respectively,the weight of the q-th attribute in the h-th time window is represented. The basic idea is that the more times a domain evaluates a certain attribute, the more important the requesting node within the domain will be to represent that attribute.
wherein ,represents A (x) i ) At the h time window pair sp j Number of feedback of the q-th attribute submitted.
2.2 Based on the trust of the service providing node in each domain, the final credit value of the service providing node is calculated.
Specifically, the method comprises the following steps:
2.2.1 Calculating weight information according to the number of interactions of the service provider in each domain;
2.2.2 Inter-domain trust fusion is carried out on the trust degree of the service providing node in each domain according to the weight information;
2.2.3 The query blockchain obtains the reputation value of the service providing node of the last time window, and calculates to obtain the final reputation value of the h time window.
An h time window, a service providing node sp j The reputation calculation expression of (2) is
wherein , and />Representing final reputation values of the h time window and h-1 time window service providing nodes; />When the trust between domains is fused, the weight information occupied by the trust value of each domain is represented; sp (sp) j →A(x i )| h Representing sp j And domain A (x i ) The interaction times of the internal node in the h time window; mu (mu) 1 ，1-μ 1 Respectively representing the weight of trust calculated by the current time window and the weight occupied by the reputation value at the last moment.
Example 2
In contrast to the above embodiment 1, which provides a blockchain-based edge computing multidimensional trust evaluation method, this embodiment provides a blockchain-based edge computing multidimensional trust evaluation system. The system provided in this embodiment may implement the blockchain-based edge computing multidimensional trust evaluation method in embodiment 1, and the system may be implemented in software, hardware, or a combination of software and hardware. For example, the system may include integrated or separate functional modules or functional units to perform the corresponding steps in the methods of embodiment 1. Since the system of this embodiment is substantially similar to the method embodiment, the description of this embodiment is relatively simple, and the relevant points may be found in part in the description of embodiment 1, which is provided by way of illustration only.
The multi-dimensional trust evaluation system based on edge calculation of the blockchain provided by the embodiment comprises:
the architecture determining module is used for determining a distributed internet of things edge computing architecture based on a blockchain;
the trust evaluation module is used for establishing a trust evaluation model based on the determined distributed internet of things edge computing architecture based on the blockchain, carrying out intra-domain trust evaluation and inter-domain trust fusion and reputation calculation on the nodes providing the service after the service is finished, obtaining the domain trust value and the final reputation value of each service providing node, and selecting better service providing nodes by the service request node.
Example 3
The present embodiment provides a processing device corresponding to the blockchain-based edge computing multidimensional trust evaluation method provided in the present embodiment 1, where the processing device may 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 embodiment 1.
The processing device comprises a processor, a memory, a communication interface and a bus, wherein the processor, the memory and the communication interface are connected through the bus so as to complete communication among each other. A computer program executable on the processor is stored in the memory, and when the processor executes the computer program, the blockchain-based edge computing multidimensional trust evaluation method provided in embodiment 1 is executed.
In some embodiments, the memory may be a high-speed random access memory (RAM: random Access Memory), and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
In other embodiments, the processor may be a Central Processing Unit (CPU), a Digital Signal Processor (DSP), or other general purpose processor, which is not limited herein.
Example 4
The blockchain-based edge computing multidimensional trust assessment method of embodiment 1 may be embodied as a computer program product that may include a computer readable storage medium having computer readable program instructions embodied thereon for performing the blockchain-based edge computing multidimensional trust assessment method of embodiment 1.
The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but 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 of the preceding.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present application and not for limiting the same, and although the present application has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the application without departing from the spirit and scope of the application, which is intended to be covered by the claims.

Claims (10)

1. The multi-dimensional trust evaluation method based on the edge calculation of the blockchain is characterized by comprising the following steps of:
determining a distributed internet of things edge computing architecture based on a blockchain;
based on the determined distributed internet of things edge computing architecture based on the blockchain, a trust evaluation model is established, intra-domain trust evaluation and inter-domain trust fusion and reputation computation are carried out on the nodes providing the service after the service is finished, and the domain trust value and the final reputation value of each service providing node are obtained.
2. The blockchain-based edge computing multidimensional trust assessment method of claim 1, wherein 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 internally provided with a plurality of domains divided according to geographic positions, each domain is internally provided with a domain management node and a plurality of domain nodes, and the domain management nodes and the domain nodes are communicated with each other through an overlay network protocol or a bottom network protocol; the domain management node is used for periodically collecting subjective feedback rating information and objective QoS values in the domain, processing the subjective feedback rating information and the objective QoS values to obtain trust data, and sending the trust data to the edge server layer; the domain node is used for providing subjective feedback rating information of the service providing node for the domain management node; the service providing node is an edge server or domain node capable of providing service;
and a plurality of edge servers and blockchains are configured in the edge server layer, and the edge servers are used for providing services for domain nodes and maintaining normal operation of the blockchains.
3. The blockchain-based edge computing multidimensional trust evaluation method of claim 2, wherein the establishing a trust evaluation model based on the determined blockchain-based distributed internet of things edge computing architecture performs intra-domain trust evaluation and inter-domain trust fusion and reputation computation on nodes providing services after the service ends to obtain final reputation values of the service providing nodes comprises:
based on the expressive degree and the stability of the service attributes of the service providing node in each domain, calculating to obtain the trust degree of the service providing node in each domain;
and calculating to obtain the final credit value of the service providing node based on the trust degree of the service providing node in each domain.
4. The method for evaluating multi-dimensional trust of a blockchain-based edge computation of claim 3, wherein the computing the trust 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 comprises:
according to service providing node sp j Promise performance level of (2), monitoring performance of domain management node on (c) domain management node, etcStage, calculate service providing node sp j Is a property actual performance level of (1);
integrating the collected actual performance level information of each attribute, and calculating the performance and stability of each service attribute of the service providing node in the whole domain;
and constructing a self-adaptive attribute weight mechanism, and calculating the intra-domain trust degree of the service providing node based on the performance degree and the stability degree of each service attribute of the service providing node in the whole domain.
5. The blockchain-based edge computing multidimensional trust assessment method of claim 4, wherein the integrating the collected actual performance level information of each attribute and computing the performance and stability of each service attribute of the service providing node in the whole domain comprises:
the probability language elements are adopted to represent the performances of all the attributes of the service providing nodes in the whole domain;
calculating an attribute performance of the service providing node based on the representation of each attribute performance of the service providing node in the entire domain;
based on the information entropy, the attribute stability of the service providing node is calculated.
6. The blockchain-based edge computing multidimensional trust evaluation method of claim 3, wherein the computing a final reputation value of a service providing node based on the degree of trust of the service providing node in each domain comprises:
calculating weight information according to the interaction times of the service provider in each domain;
carrying out inter-domain trust fusion on the trust degree of the service providing node in each domain according to the weight information;
the query block chain obtains the reputation value of the service providing node of the last time window, and calculates to obtain the final reputation value of the service providing node of the h time window.
7. The method as claimed in claim 6A multi-dimensional trust evaluation method based on edge calculation of blockchain is characterized in that the h time window service provides final credit value of nodeThe method comprises the following steps:
wherein , and />Representing final reputation values of the h time window and h-1 time window service providing nodes; t (T) h (A(x i )，sp j ) Representing service providing nodes sp j In the h time window, in the domain a (x i ) Is the confidence level of (2); />When the trust between domains is fused, the weight information occupied by the trust value of each domain is represented; the method comprises the steps of carrying out a first treatment on the surface of the I so j →A(x j )| h Representing sp j And domain A (x i ) The interaction times of the internal node in the h time window; mu (mu) 1 ，1-μ 1 Respectively representing the weight of trust calculated by the current time window and the weight occupied by the reputation value at the last moment.
8. A blockchain-based edge computing multidimensional trust assessment system, comprising:
the architecture determining module is used for determining a distributed internet of things edge computing architecture based on a blockchain;
the trust evaluation module is used for establishing a trust evaluation model based on the determined distributed internet of things edge computing architecture based on the blockchain, and carrying out intra-domain trust evaluation, inter-domain trust fusion and reputation computation on the nodes providing the service after the service is finished to obtain the domain trust value and the final reputation value of each service providing node.
9. A computer readable storage medium storing one or more programs, wherein the one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform any of the methods of claims 1-7.
10. A computing device, comprising: one or more processors, 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, the one or more programs comprising instructions for performing any of the methods of claims 1-7.
CN202310290575.0A 2023-03-23 2023-03-23 Block chain-based edge computing multidimensional trust evaluation method and system Pending CN116668450A (en)

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CN116996521A (en) * 2023-09-28 2023-11-03 江西农业大学 Relay committee cross-chain interaction system and method based on trust evaluation model
CN117155947A (en) * 2023-08-30 2023-12-01 国网山东省电力公司德州供电公司 High-reliability real-time sharing method and system for data resources

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Publication number Priority date Publication date Assignee Title
CN117155947A (en) * 2023-08-30 2023-12-01 国网山东省电力公司德州供电公司 High-reliability real-time sharing method and system for data resources
CN117155947B (en) * 2023-08-30 2024-04-09 国网山东省电力公司德州供电公司 High-reliability real-time sharing method and system for data resources
CN116996521A (en) * 2023-09-28 2023-11-03 江西农业大学 Relay committee cross-chain interaction system and method based on trust evaluation model
CN116996521B (en) * 2023-09-28 2023-12-15 江西农业大学 Relay committee cross-chain interaction system and method based on trust evaluation model

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