Method and apparatus for service customization scheduling in wide area network

Abstract

The application provides a service customization scheduling method and device in a wide area network. The method is executed by a service provider deployed in a service interconnection layer based on a service customization network hierarchical system in the wide area network. Multiple autonomous domains are divided in the wide area network. A reputation opinion parameter of the autonomous domain is calculated. A malicious autonomous domain with a reputation opinion parameter lower than a set reputation threshold is removed. A target service overall transmission demand index is decomposed into domain internal transmission demand indexes of multiple autonomous domains. Related contract items are published according to the domain internal transmission demand indexes. Each autonomous domain freely selects the contract items and provides network transmission services satisfying the domain internal transmission demand indexes. Customized services of the autonomous domains are realized. Expected end-to-end service quality is obtained. A contract model of the service provider and the autonomous domains is constructed. Individual rationality constraints and incentive compatibility constraints are introduced to solve optimal contracts. The customized services of the autonomous domains are satisfied. The overall social utility maximization is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of customized service scheduling methods, and in particular to a customized service scheduling method and device in a wide area network. Background Art

[0002] Existing Internet applications and traditional routing service models are built on the Internet Protocol and Transmission Control Protocol network architecture. The network strives to deliver inter-application communication data to its destination, but makes no guarantees regarding transmission rate or latency. This greatly simplifies the network, but leads to a gradual deterioration in the network environment and user satisfaction. Most network technologies that enhance Quality of Service (QoS) only operate within the operator's network and have not been adopted or utilized by terminals or applications. This makes it impossible to tailor QoS to the needs of differentiated services across the Internet. To fundamentally overcome the current transmission limitations of QoS, a new network architecture, Service Customized Networking (SCN), is proposed. Applications are expected to impose bandwidth, latency, jitter, and packet loss requirements on the network as needed, and the network must provide QoS guarantees to the extent possible.

[0003] In existing technologies, building a service-customized 5G network through network slicing to achieve service customization scenarios only considers end-to-end scheduling from business needs to network spatiotemporal resources, lacking research on inter-domain collaboration and customization. Autonomous Domains (ADs) exhibit significant heterogeneity in network structure, resource types, topology, and protocol preferences, and there is a lack of further work supporting service diversity and customization within autonomous domains. Furthermore, a service-customized routing mechanism based on deep learning in the Internet Protocol Version 6 network has been proposed to meet service personalization needs, ensure the reliability of customized services during routing, and achieve a rapid win-win situation for users and service providers (SPs). However, building service-customized routing paths requires the use of various network resources and energy. Traditional traffic-based payment models are not conducive to service-centric scheduling models and cannot implement customized services within the autonomous domains for differentiated service quality requirements such as deterministic delay jitter, ultra-high throughput bandwidth, and high reliability, while also ensuring predictable end-to-end service quality. Summary of the Invention

[0004] In view of this, an embodiment of the present invention provides a method and device for customized scheduling of services in a wide area network to eliminate or improve one or more defects existing in the prior art, and solves the problem in the prior art that customized services in autonomous domains cannot be realized and the expected end-to-end service quality cannot be obtained due to the differentiated service quality requirements of network transmission services and the lack of coordination in resource scheduling.

[0005] One aspect of the present invention provides a method for scheduling customized services in a wide area network. The method deploys a service provider in a service interconnection layer of a wide area network based on a service customization network layer system. The wide area network is divided into multiple autonomous domains. The method is performed by the service provider and includes the following steps:

[0006] The probability that each autonomous domain can guarantee the required service quality and the probability that it cannot guarantee the required service quality are obtained as positive interaction factors and negative interaction factors respectively, and the probability of successful data packet transmission is obtained as the uncertain interaction opinion factor;

[0007] Calculating a reputation opinion parameter of each autonomous domain based on the positive interaction factor, the negative interaction factor, and the uncertain interaction opinion factor, and storing the parameter on an open reputation blockchain;

[0008] Marking an autonomous domain whose reputation opinion parameter is lower than a set reputation threshold as a malicious autonomous domain, and removing the malicious autonomous domain from the wide area network;

[0009] Decomposing the overall end-to-end transmission requirement indicator of the target service into intra-domain transmission requirement indicators of multiple autonomous domains, wherein the transmission requirement indicators include transmission delay and jitter of the transmission delay;

[0010] Relevant contract items are selected and published based on the transmission demand indicators within each domain, so that each autonomous domain can freely choose the corresponding contract item and provide network transmission services that meet the transmission demand indicators within the corresponding domain; wherein, the contract item is used to record the rewards provided by the service provider to the autonomous domain that meets the transmission demand indicators within a specific domain.

[0011] In some embodiments, calculating the reputation opinion parameter of each autonomous domain based on the positive interaction factor, the negative interaction factor, and the uncertain interaction opinion factor includes:

[0012] The positive interaction factor, negative interaction factor, and uncertain interaction opinion factor of the autonomous domain are obtained, and the positive opinion parameter, negative opinion parameter, and uncertain opinion parameter of the service provider on the autonomous domain are calculated based on the obtained positive interaction factor, negative interaction factor, and uncertain interaction opinion factor, and the calculation expression satisfies:

[0013]

[0014] Among them, α t represents the positive interaction factor, β t represents the negative interaction factor, represents the uncertain interactive opinion factor, represents the positive opinion parameter, represents the negative opinion parameter, represents the uncertain opinion parameter, a represents the service provider, and b represents the autonomous domain;

[0015] And, the reputation opinion parameter is calculated according to the positive opinion parameter and the uncertain opinion parameter of the autonomous domain, and the calculation expression satisfies:

[0016]

[0017] Among them, Ω a→b represents the reputation opinion parameter, and ν is a factor that quantifies the impact of the uncertain interactive opinion factor on reputation.

[0018] In some embodiments, the overall end-to-end transmission requirement indicator of the target service is decomposed into intra-domain transmission requirement indicators within multiple autonomous domains, including:

[0019] The overall end-to-end transmission delay of the target service is decomposed into intra-domain transmission delays within multiple autonomous domains, and the risk coefficient μ is used to relax the budget of the transmission delay within each autonomous domain after decomposition. The expression is:

[0020]

[0021] Wherein, N0 represents the number of autonomous domains participating in the end-to-end transmission of the target service, d i represents the transmission delay of the i-th autonomous domain, where the transmission delay is obtained based on one or more of processing delay, queuing delay, sending delay, and propagation delay. D represents the end-to-end delay requirement in the wide area network;

[0022] Furthermore, the jitter of the transmission delay of each autonomous domain is controlled to be less than a predetermined jitter requirement.

[0023] In some embodiments, the transmission delay of the autonomous domain is calculated using the queuing delay and the sending delay, and the calculation expression satisfies:

[0024]

[0025] Among them, V represents the average arrival rate of data packets, L represents the number of bits of data packets, and H i represents the maximum bandwidth of the i-th autonomous domain.

[0026] In some embodiments, the method further comprises:

[0027] The end-to-end overall transmission demand index of the target service is decomposed into multiple transmission demand indexes within autonomous domains, and solved by minimizing the objective function. The expression of the objective function is:

[0028]

[0029] f(d)=cT *d;

[0030] Where d represents the solution vector, c represents the weight vector, λ1 and λ2 represent the Lagrange coefficients, and d j represents the transmission delay of the jth autonomous domain, J represents the jitter requirement of the transmission delay of the autonomous domain, and T represents discrete time.

[0031] In some embodiments, the method further comprises:

[0032] Implementing network transmission services based on multiple types of network ticket interfaces within an autonomous domain, where each type of network ticket corresponds to a quality of service capability. The network ticket interface is used to implement capability mapping between the network and the application.

[0033] and, dividing the autonomous domains into multiple types according to the quality of service they can provide;

[0034] Obtaining attributes of each type of network ticket, wherein the attributes of each type of network ticket include basic attributes related to spatiotemporal resources and additional attributes affected by the market, wherein the additional attributes affected by the market include the available number of network tickets of the current type in the autonomous domain, the estimated value corresponding to the available number of network tickets of the current type, and the market supply and demand relationship of the network tickets of the current type;

[0035] Calculate the basic market price of each type of online ticket based on the price determined by the attributes of each type of online ticket and the influencing factors of additional attributes;

[0036] Arranging the types of the autonomous domains in ascending order of their quality of service;

[0037] Based on the type and contribution of each autonomous domain, the compensation required for each autonomous domain when it cannot achieve the required service quality under limited time and space resources is calculated;

[0038] Calculating the profit obtained by the service provider from each type of autonomous domain based on the service delay satisfaction, valuation satisfaction, price satisfaction obtained from each type of autonomous domain and their respective weights;

[0039] Calculate the expected utility of the service provider, the expression is:

[0040]

[0041] Calculate the utility of the nth autonomous domain, the expression is:

[0042]

[0043] The overall social utility is calculated based on the expected utility of the service provider and the utility of each autonomous domain. The expression of the overall social utility is:

[0044]

[0045] in, represents the profit obtained by the service provider from the n-type autonomous domain, ∈ represents the parameter used to adjust the overall satisfaction level, represents the cost price of m-type network ticket, F- represents the compensation function, θ n Indicates the type of autonomous domain, d n represents the contribution of the n-type autonomous domain, p m represents the basic market price of the m-type online ticket, Γ n represents the supplementary reward of the n-type autonomous domain in addition to the basic market price, ρ n represents the probability that the autonomous domain belongs to type n.

[0046] In some embodiments, solving the contract item by maximizing the overall social utility includes:

[0047] Individual rationality constraints and incentive compatibility constraints are introduced. The individual rationality constraint requires each autonomous domain to participate in end-to-end customized transmission only when its utility is equal to or greater than zero. The expression is:

[0048]

[0049] The incentive compatibility constraint requires that each autonomous domain should use a contract specifically tailored for the autonomous domain type, rather than other contracts, as expressed as:

[0050]

[0051] Then, the problem expression for solving the contract project by maximizing the overall social utility is:

[0052]

[0053]

[0054]

[0055] Wherein, N represents the type of the autonomous domain.

[0056] In some embodiments, the method further comprises:

[0057] The iterative method based on the individual rationality constraint and the incentive compatibility constraint is used to maximize the overall social utility, which is expressed as:

[0058]

[0059] Through Uall Right 2 The differential of That is U all It's about d 2 The concave function is solved using convex optimization tools to obtain the optimal solution for the contract project.

[0060] On the other hand, the present invention also provides a customized service scheduling device in a wide area network, which includes a processor and a memory, and is characterized in that computer instructions are stored in the memory, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of the above method.

[0061] On the other hand, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the program implements the steps of the above method when executed by a processor.

[0062] The beneficial effects of the present invention are at least:

[0063] In the service customization scheduling method and device in the wide area network described in the present invention, the method is executed by a service provider deployed in the service interconnection layer of the service customization network layered system in the wide area network, and the wide area network is divided into multiple autonomous domains. By calculating the reputation opinion parameters of each autonomous domain and storing them on an open reputation blockchain, malicious autonomous domains whose reputation opinion parameters are lower than the set reputation threshold are eliminated, and the overall end-to-end transmission demand indicators of the target business are decomposed into intra-domain transmission demand indicators within multiple autonomous domains. Relevant contract projects are selected and published according to the intra-domain transmission demand indicators, so that each autonomous domain can freely select the corresponding contract project and provide network transmission services that meet the corresponding intra-domain transmission demand indicators, thereby realizing customized services of the autonomous domain and obtaining the expected end-to-end service quality.

[0064] Furthermore, the present invention constructs a contract model between the service provider and the autonomous domain and introduces individual rationality constraints and incentive compatibility constraints to solve the optimal contract, thereby maximizing the overall social utility while satisfying the customized services of the autonomous domain.

[0065] Additional advantages, objects, and features of the present invention will be set forth in part in the following description and will become apparent to those skilled in the art upon examination of the following or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained by the structures particularly pointed out in the description and drawings.

[0066] Those skilled in the art will understand that the purposes and advantages that can be achieved by the present invention are not limited to the above specific descriptions, and the above and other purposes that can be achieved by the present invention will be more clearly understood based on the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of this application, and do not constitute a limitation of the present invention. In the drawings:

[0068] Figure 1 The figure is a flow chart of a customized service scheduling method in a wide area network according to an embodiment of the present invention.

[0069] Figure 2 A network layering system is customized for services in a wide area network according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0071] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, the accompanying drawings only show structures and / or processing steps closely related to the solutions according to the present invention, while other details that are not closely related to the present invention are omitted.

[0072] It should be emphasized that the term "include / comprises" when used herein refers to the existence of features, elements, steps or components, but does not exclude the existence or addition of one or more other features, elements, steps or components.

[0073] It should also be noted that, unless otherwise specified, the term "connection" herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0074] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0075] In the existing technology, the service customization scenario achieved by building a service-customized 5G network through network slicing only considers the end-to-end scheduling from business needs to network spatiotemporal resources, lacks research on inter-domain collaboration and customization, and lacks more work to support the service diversity and customization of autonomous domains. In addition, the service customization routing mechanism of the Internet version 6 protocol network deep learning requires the use of various network resources and energy to build a service customization routing path. The traditional traffic-based payment model is not conducive to the service-centric scheduling model; the present invention proposes a service customization scheduling method in a wide area network, which uses a subjective logic reputation calculation model to calculate the reputation opinion parameter, and decomposes the target business transmission demand indicator by domain, and at the same time constructs a contract model between the service provider and the autonomous domain to solve the optimal contract, solving the problem in the existing technology that the differentiated service quality requirements of network transmission services and the uncoordinated resource scheduling cannot realize the customized service of the autonomous domain and obtain the expected end-to-end service quality, while maximizing the overall social utility.

[0076] Figure 1 This is a flow chart of a method for customized service scheduling in a wide area network according to an embodiment of the present invention. Specifically, the present application provides a method for customized service scheduling in a wide area network, wherein a service provider is deployed in a service interconnection layer based on a service customization network layer system in the wide area network, and the wide area network is divided into multiple autonomous domains. The method is executed by the service provider, and the method includes the following steps S101 to S105:

[0077] Step S101: obtaining the probability that each autonomous domain can guarantee the required service quality and the probability that it cannot guarantee the required service quality as the positive interaction factor and the negative interaction factor respectively, and obtaining the probability of successful data packet transmission as the uncertain interaction opinion factor.

[0078] Step S102: Calculate the reputation opinion parameters of each autonomous domain based on the positive interaction factor, the negative interaction factor, and the uncertain interaction opinion factor, and store them on the open reputation blockchain.

[0079] Step S103: mark the autonomous domains whose reputation opinion parameters are lower than the set reputation threshold as malicious autonomous domains, and remove the malicious autonomous domains from the wide area network.

[0080] Step S104: decomposing the overall end-to-end transmission requirement index of the target service into intra-domain transmission requirement indexes of multiple autonomous domains. The transmission requirement index includes transmission delay and transmission delay jitter.

[0081] Step S105: Select relevant contract items based on the transmission demand indicators within each domain and publish them so that each autonomous domain can freely choose the corresponding contract items and provide network transmission services that meet the transmission demand indicators within the corresponding domain; wherein the contract items are used to record the rewards provided by the service provider to the autonomous domain that meets the transmission demand indicators within a specific domain.

[0082] In steps S101, S102, and S103, reputation refers to the credibility and image of an autonomous domain on the Internet, reflecting the operational quality of the network and routers within the autonomous domain, as well as the stability and reliability when interconnected with other autonomous domains. To guarantee end-to-end service quality and ensure the reliability of transmission services, a subjective logic reputation calculation model is constructed to calculate the reputation opinion parameters of each autonomous domain, thereby achieving real-time evaluation of the reliability and trustworthiness of the autonomous domain. The subjective logic reputation calculation model includes positive opinion parameters, negative opinion parameters, and uncertain opinion parameters. The subjective logic model differs from other logic models in that it takes subjectivity and uncertainty into account. The present invention uses the probability of successful data packet transmission as an uncertain interaction opinion factor in reputation calculation. In some embodiments, the reputation opinion parameters of each autonomous domain are calculated based on the positive interaction factor, the negative interaction factor, and the uncertain interaction opinion factor, including the following steps S1011 to S1012:

[0083] Step S1011: Obtain the positive interaction factor, negative interaction factor, and uncertain interaction opinion factor of the autonomous domain, and calculate the service provider's positive opinion parameter, negative opinion parameter, and uncertain opinion parameter for the autonomous domain based on the obtained positive interaction factor, negative interaction factor, and uncertain interaction opinion factor. The calculation expression satisfies:

[0084]

[0085] Among them, α t represents the positive interaction factor, β t represents a negative interaction factor, represents the uncertain interaction opinion factor, Parameters indicating positive opinions, represents the negative opinion parameter, represents the uncertain opinion parameter, a represents the service provider, and b represents the autonomous domain.

[0086] Step S1012: Calculate the reputation opinion parameter based on the positive opinion parameter and the uncertain opinion parameter of the autonomous domain. The calculation expression satisfies:

[0087]

[0088] Among them, Ω a→b represents the reputation opinion parameter, and ν is the factor that quantifies the impact of uncertain interactive opinion factors on reputation.

[0089] The reputation opinion parameters are stored and managed on the open reputation blockchain. The open reputation blockchain shares the transaction data on the blockchain so that service providers can retrieve the latest reputation opinion parameters from the reputation blockchain. Based on the subjective logic model, the service provider updates the reputation opinion parameters on the reputation blockchain according to the latest end-to-end service.

[0090] Furthermore, malicious autonomous domains may engage in intentional or unintentional bad behavior, resulting in unpredictable service quality. The present invention sets a reputation threshold to screen out autonomous domains below the set reputation threshold, mark them as malicious autonomous domains, and eliminate them to ensure predictable end-to-end service quality.

[0091] In step S104, the idea of ​​decomposing the end-to-end overall transmission demand indicator of the target service into intra-domain transmission demand indicators within multiple autonomous domains draws on the differentiated transportation modes of the transportation system and the idea of ​​"network ticket inter-trip transfer", enabling the autonomous domain to achieve the coexistence of multiple packet bearer technologies and meet different service quality transmission requirements.

[0092] Furthermore, the difficulty of implementing different transmission requirements is analyzed. Transmission requirement indicators include bandwidth, packet loss, delay, and jitter. The implementation difficulty is divided into five levels, including uncertainty, weak certainty, general certainty, strong certainty, and super-strong certainty. Since bandwidth and packet loss indicators are business flow-oriented and are statistical results of the success or failure of a batch of packet transmissions, they have high fault tolerance and do not require fine-grained control. However, delay and jitter require high precision in system control and require packet-by-packet scheduling. Therefore, the decomposition of transmission requirement indicators mainly considers the decomposition of delay and jitter. In some embodiments, the overall end-to-end transmission requirement indicator of the target service is decomposed into intra-domain transmission requirement indicators within multiple autonomous domains, including:

[0093] The overall end-to-end transmission delay of the target service is decomposed into intra-domain transmission delays within multiple autonomous domains, and the risk coefficient μ is used to relax the budget of the transmission delay within each autonomous domain after decomposition. The expression is:

[0094]

[0095] Where N0 represents the number of autonomous domains participating in the end-to-end transmission of the target service, d i represents the transmission delay of the i-th autonomous domain. The transmission delay is obtained based on one or more of the processing delay, queuing delay, sending delay, and propagation delay. D represents the end-to-end delay requirement in the wide area network.

[0096] Furthermore, the jitter of the transmission delay of each autonomous domain is controlled to be less than a predetermined jitter requirement. The expression for controlling the jitter of the transmission delay of each autonomous domain to be less than a predetermined jitter requirement satisfies:

[0097] maxd i ―mind j ≤J,1≤i,j≤N0;

[0098] Among them, d j represents the transmission delay of the jth autonomous domain.

[0099] When the network has the ability to process data packets and transmit at high speed, the impact of processing delay and propagation delay on end-to-end delay can be ignored. In some embodiments, the transmission delay of the autonomous domain is calculated using queuing delay and sending delay, and the calculation expression satisfies:

[0100]

[0101] Among them, V represents the average arrival rate of data packets, L represents the number of bits of data packets, and H i represents the highest bandwidth of the i-th autonomous domain.

[0102] Furthermore, in order to solve the transmission demand index decomposition problem, in some embodiments, the method further includes: decomposing the end-to-end overall transmission demand index of the target service into multiple autonomous domain transmission demand indexes, and solving the problem by minimizing the objective function. The objective function is expressed as:

[0103]

[0104] f(d)=c T *d;

[0105] Where d represents the solution vector, c represents the weight vector, λ1 and λ2 represent the Lagrange coefficients, and d j represents the transmission delay of the jth autonomous domain, J represents the jitter requirement of the autonomous domain transmission delay, and T represents discrete time.

[0106] In step S105, the service interconnection layer in the SCN layered system transmits the required service quality transmission requirements downward through the network ticket interface. The network ticket interface can realize the capability mapping between the network and the application. For the application, the network ticket represents the network capability of any combination of bandwidth and latency. For the network, the network ticket means issuing service capabilities with a certain bandwidth and latency level. The service provider is introduced as the market to coordinate the autonomous domains. At the same time, a contract model between the service provider and the autonomous domain is constructed, and individual rational constraints and incentive compatibility constraints are introduced to solve the optimal contract. In the case of information asymmetry, the customized service of the autonomous domain is met while the overall social utility is maximized, thereby ensuring the economic benefits of the service provider. In addition, the service provider will provide rewards to the autonomous domain that meets the transmission demand indicators within a specific domain to encourage trusted and high-quality autonomous domains to participate in the service scheduling process of customized transmission demand.

[0107] In some embodiments, the method further comprises:

[0108] Network transmission services are implemented based on multiple types of network ticket interfaces in autonomous domains. Each type of network ticket corresponds to a quality of service capability. The network ticket interface is used to achieve capability mapping between the network and the application.

[0109] Furthermore, autonomous domains are divided into multiple types according to the quality of services they can provide.

[0110] Obtain the attributes of each type of network ticket, including basic attributes related to space-time resources and additional attributes affected by the market. The additional attributes affected by the market include the available number of network tickets of the current type in the autonomous domain, the estimated value corresponding to the available number of network tickets of the current type, and the market supply and demand relationship of the current type of network tickets.

[0111] The basic market price of each type of online ticket is calculated based on the price determined by the attributes of each type of online ticket and the influencing factors of additional attributes.

[0112] Arrange the types of autonomous domains in ascending order of their quality of service.

[0113] Based on the type and contribution of each autonomous domain, the compensation required for the service of each autonomous domain when it cannot achieve the required service quality under limited space-time resources is calculated.

[0114] The profit obtained by the service provider from each type of autonomous domain is calculated based on the service delay satisfaction, valuation satisfaction, price satisfaction and their respective weights obtained from each type of autonomous domain.

[0115] Calculate the expected utility of the service provider, the expression is:

[0116]

[0117] Calculate the utility of the nth autonomous domain, the expression is:

[0118]

[0119] The overall social utility is calculated based on the expected utility of the service provider and the utility of each autonomous domain. The expression of the overall social utility is:

[0120]

[0121] in, represents the profit that the service provider gets from n types of autonomous domains, ∈ represents the parameter used to adjust the overall satisfaction level, represents the cost price of m-type network ticket, F- represents the compensation function, θ nIndicates the type of autonomous domain, d n represents the contribution of n types of autonomous domains, p m represents the basic market price of m-type online tickets, Γ n represents the supplementary reward of n-type autonomous domain in addition to the basic market price, ρ n represents the probability that the autonomous domain belongs to type n.

[0122] Specifically, the contribution referred to in the present invention refers to the QoS service level provided by the autonomous domain.

[0123] The expression of each type of network ticket attribute is:

[0124]

[0125] Among them, e m Indicates the basic attributes of the mth type of network ticket related to time and space resources, and It is an additional attribute affected by the market. Indicates the number of available network tickets of type m in an autonomous domain of type n. represents the estimated value of the available number of m-type network tickets in n-type autonomous domains, Represents the market supply and demand relationship of type m online tickets.

[0126] The basic market price of each type of online ticket is expressed as:

[0127]

[0128] Among them, k m e m The price is determined by the basic attributes. and The value of is affected by additional attributes and is updated periodically over time t, where N represents the type of autonomous domain.

[0129] Based on the type and contribution of each autonomous domain, when each autonomous domain cannot achieve the required service quality under limited space-time resources, compensation is required for the service. The compensation function expression is:

[0130] F - (λ,d)=de ―λt ;

[0131] Where λ represents the type of autonomous domain and d represents the contribution of the autonomous domain.

[0132] The profit that computing service providers obtain from each type of autonomous domain is expressed as:

[0133]

[0134]

[0135] Among them, w1, w2 and w3 are weight parameters, satisfying w1+w2+w3=1, and They represent the service delay satisfaction, valuation satisfaction, and price satisfaction obtained from n types of autonomous domains, respectively. D represents the overall end-to-end transmission delay requirement of the service. Indicates the minimum value that the service provider can tolerate.

[0136] In some embodiments, solving a contract project by maximizing overall social utility includes:

[0137] Individual rationality constraints and incentive compatibility constraints are introduced. The individual rationality constraint requires that each autonomous domain participates in end-to-end customized transmission only when its utility is equal to or greater than zero. The expression is:

[0138]

[0139] The incentive compatibility constraint requires that each autonomous domain should use a contract specifically tailored for the autonomous domain type, rather than other contracts, as expressed as:

[0140]

[0141] Then, the problem expression of solving the contract project by maximizing the overall social utility is:

[0142]

[0143]

[0144]

[0145] Where N represents the type of autonomous domain.

[0146] In some embodiments, the method further comprises:

[0147] The iterative method based on individual rationality constraints and incentive compatibility constraints is used to maximize the overall social utility, which is expressed as:

[0148]

[0149] Through U all Right 2 The differential of That is U all It's about d 2 The concave function is solved using convex optimization tools to obtain the optimal solution for the contract project.

[0150] Specifically, when the transmission delay requirements and the transmission delay jitter requirements of each autonomous domain are met, the iteration ends.

[0151] On the other hand, the present invention also provides a customized service scheduling device in a wide area network, comprising a processor and a memory, wherein the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of the above method.

[0152] On the other hand, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when executed by a processor.

[0153] The present invention will be described below in conjunction with a specific embodiment:

[0154] Figure 2 This invention describes a hierarchical network system for customized services in a wide area network (WAN) as described in one embodiment of the present invention. To address the differentiated QoS requirements of various emerging Internet services, such as deterministic latency jitter, ultra-high throughput bandwidth, and high reliability, this invention proposes a contract-based service scheduling method for WANs. First, to ensure end-to-end service quality, a reputation-based trusted autonomous domain (AD) screening scheme is proposed. The reputation values ​​of the ADs are calculated using a subjective logic model and recorded via a blockchain. A reputation threshold is established to screen potential malicious ADs, ensuring predictable end-to-end service delivery. Secondly, drawing on the differentiated transportation modes and the concept of "network ticketing and inter-trip transfer" in transportation systems, a cross-domain QoS customization method based on indicator decomposition is proposed. This method allows for the coexistence of multiple packet bearer technologies within the ADs and provides different QoS capabilities, enabling the network to provide differentiated services such as expressways, ordinary roads, ordinary trains, and high-speed trains. Finally, to address information asymmetry, an optimal contract-based service customization scheduling mechanism is proposed. Service providers are introduced as market intermediaries to coordinate the ADs. A contribution-reward contract program is established to incentivize ADs to independently select contract projects based on resource attributes and rewards, maximizing the overall system utility. Through the constraints of individual rationality and incentive compatibility, a scheduling strategy based on the optimal contract is realized, which meets end-to-end customization while ensuring the economic benefits of SP.

[0155] The SCN layered architecture consists of the application layer, service presentation layer, service transport layer, service interconnection layer, packet bearer layer, data link layer, and physical layer. The service interconnection layer, overlaying the packet bearer layer, decouples the different tasks of interconnecting networks within a domain and interconnecting different domains. Acting as the control plane, it coordinates the various Active Directory (ADs), AD1 and AD2, and communicates the required QoS requirements downward through interfaces called network tickets: Network Ticket I, Network Ticket II, and Network Ticket III. The network ticket interface enables capability mapping between the network and applications. For applications, a "ticket" represents a network capability consisting of any combination of bandwidth and latency. For the network, a "ticket" represents the issuance of a service capability with a specific bandwidth and latency level. The design of the independent service interconnection layer and the network ticket interface facilitates the coexistence of multiple inter-domain packet transport technologies and manages the resulting heterogeneity.

[0156] Based on the above-mentioned layered system, the present invention proposes a service customization scheduling framework based on contract theory in a wide area network. The SP deployed in the service interconnection layer acts as the employer, performs autonomous domain control and gateway control, and is responsible for decomposing end-to-end QoS indicators from a business perspective. When the transmission delay of AD1 is d1, the jitter of the transmission delay is j1, and the transmission delay of AD2 is d2, and the jitter of the transmission delay is j2, the overall end-to-end transmission delay of the target service is D = d1 + d2, and the jitter of the transmission delay is J = j1 + j2. Based on the theoretically decomposed QoS indicators, a contract is designed, and the corresponding contribution-reward contract items (Γ1, Γ2, Γ3, ...Γ n ) to build a QoS-oriented service pricing model. ADs deployed at the packet bearer layer act as employees. After reputation calculation and screening, they can freely select contract items and execute independent intra-domain QoS routing planning based on decomposed QoS metrics. This achieves the expected end-to-end service quality while exchanging a small amount of intra-domain information. This customized service scheduling framework operates in a discrete time T = {1, 2, …, t, …, T} and includes three modules: reputation calculation, end-to-end QoS metric decomposition, and contract design. The specific solution is as follows:

[0157] 1. Trusted Autonomous Domain Screening Scheme Based on Reputation Computing: Since an unreliable or malicious AD may engage in intentional or unintentional bad behavior, resulting in unpredictable service quality, in order to evaluate the credibility and reliability of ADs, this paper adopts a subjective logic model and proposes a trusted autonomous domain screening scheme based on reputation computing. Candidate autonomous domains are divided into trusted autonomous domains and malicious autonomous domains based on reputation thresholds. The process includes the following steps S1 to S3:

[0158] Step S1: First, the reputation opinions are stored and managed on an open and accessible reputation blockchain, where the evaluation feedback of the AD is registered as a data block, and the SP can retrieve the latest reputation opinions from the reputation blockchain.

[0159] Step S2: After completing an end-to-end service, the SP updates the reputation opinions of ADs based on the subjective logic model according to the latest interactions.

[0160] Specifically, the subjective logic reputation model consists of positive, negative, and uncertain opinions, represented by x, y, and z respectively. Then the reputation opinion of SP(a) on AD(b) is expressed as: a→b :={x a→b ,y a→b ,z a→b},exist:

[0161]

[0162] Based on the subjective logic model, the reputation calculation problem is expressed as:

[0163] Among them, α t and β t Represent the positive interaction factor and negative interaction factor of time period t, represents the probability of successful data packet transmission, which is also the uncertain interaction opinion in reputation calculation. Assuming that ν is a factor that quantifies the impact of uncertain interaction opinion on reputation, then in time period t, the reputation opinion of SP(a) on AD(b) is described as:

[0164] Step S3: Establish a reputation threshold below which ADs will be identified as potentially malicious.

[0165] 2. A Customizable Cross-Domain QoS Method Based on Indicator Decomposition: Based on the concept of "network ticket inter-transfer," this paper proposes a "QoS indicator decomposition" method that decomposes end-to-end service requirements, such as latency, jitter, and packet loss, by domain. First, the difficulty of implementing different QoS requirements is analyzed and categorized into five levels: i) Uncertainty, which refers to no requirements on any QoS indicators, such as BE services; ii) Weak Determinism, which refers to no requirements on latency or jitter, but requirements on bandwidth or packet loss, such as traditional bandwidth-intensive services; iii) Moderate Determinism, which refers to requirements on latency but not jitter. In this case, the solution space for routing and along-path resource allocation is large; iv) Strong Determinism, which refers to requirements on both latency and jitter. This limits the solution space for along-path resource allocation, but still allows for diversity in path selection; and v) Super Determinism, which requires packets to arrive at their destination at a specific time. In this case, the solution space for routing and resource allocation is strictly limited, requiring extremely high precision in system control. It's worth noting that categories iii-v are more challenging than category ii. This is because bandwidth and packet loss metrics are oriented toward service flows and represent the statistical results of the successful transmission of a batch of packets. These metrics are more fault-tolerant and don't require precise control. Traditional resource reservation technologies, such as the Resource Reservation Protocol (RSVP), can suffice. However, delay and jitter require per-packet scheduling, which places high demands on system control precision. Therefore, the decomposition of QoS metrics primarily considers delay and jitter.

[0166] Assume that there are N autonomous domains participating in end-to-end communication, the end-to-end delay requirement is D (when there is no delay requirement, D is infinite or has a large upper bound), and the jitter requirement is J (when there is no jitter requirement, J is infinite or has a large upper bound). Delay mainly includes processing delay, queuing delay, transmission delay, and propagation delay. Assuming that the network has the ability to process data packets and transmit at high speed, the impact of processing delay and propagation delay on end-to-end delay can be ignored, and queuing delay d queue and transmission delay d trans Expressed as:

[0167]

[0168]

[0169] Where V is the average arrival rate of packets, H is the transmission rate (i.e., bandwidth), and assume that all packets consist of L bits.

[0170] The risk factor μ is introduced to moderately relax the theoretically derived latency budget to reduce its impact on end-to-end QoS. Specifically, access network metrics are incorporated into the protocol stack's Service Level Agreement (SLA) for unified consideration. The idea is to measure transmission metrics between the host protocol stack and the gateway, deducting them from the budget as access segment parameters when decomposing cross-domain metrics. However, given that access network transmission quality may not be controllable, the risk factor introduced in the measurement metrics is appropriately relaxed.

[0171] Assuming that there are N0 autonomous domains participating in the end-to-end QoS transmission of a service, the QoS problem based on indicator decomposition can be expressed as:

[0172]

[0173] maxd i ―mind j ≤J,1≤i,j≤N0;#(7)

[0174] In order to solve this nonlinear constrained optimization problem, it is transformed into a linear programming problem and solved using the interior point method. The goal is to minimize an objective function, which is expressed as:

[0175]

[0176] Where f(d) = c T *d, c is a weight vector, d is the solution vector. λ1,λ2 are Lagrange coefficients. According to formulas (4) and (5), d i Initialized as:

[0177] The maximum bandwidth of autonomous domain i is H i is obtained through prior knowledge. The interior point method is then iterated to calculate the gradient of function (8) and update d, λ1, λ2 (a feasible solution is a numerical solver). The iteration ends when the constraints are met or the change in the objective function is less than a predefined tolerance.

[0178] 3. Customized service scheduling mechanism based on optimal contract: In order to encourage autonomous domains to share resources and improve service quality, the present invention designs a contract incentive model that maximizes utility under conditions of information asymmetry, and solves the optimal contract based on feasible conditions to explore the optimal mapping relationship between network resources and service requirements, thereby realizing customized service scheduling.

[0179] 3.1 Contract model between service providers and autonomous domains: In this model, the SP acts as the employer and ADs act as employees. The main process of the contract mechanism between the service provider and the autonomous domain includes the following steps S10 to S40:

[0180] Step S10: ADs registers resources and other related information with SP.

[0181] Step S20: The SP specifies relevant contract items while considering resource availability, wherein the contract items specify the contributed resources (defined by the decomposed QoS indicators) and the corresponding rewards.

[0182] Step S30: SP publishes these contract items to ADs except the filtered malicious ADs.

[0183] Step S40: ADs are free to select contract items according to their types.

[0184] a. ADs type: The quality of service is defined as the type of ADs, represented by parameter θ, and can be divided into N types, N = {1, 2, ..., n, ..., N}. To further describe the quality of service, the service unavailability function is defined as:

[0185] Q(λ,t)=1―e ―λt ,t∈[0,T];#(10)

[0186] This is the proportion of time when ADs are unable to provide the required resources, following an exponential distribution, where t is the unavailability time and λ is the parameter associated with the exponential distribution. As λ increases, the probability of high quality of service increases.

[0187] b. Network Ticket Attributes: SPs and ADs trade through network tickets (commodities). Different types of network tickets represent different QoS capabilities, represented by M = {1, 2, ..., m, ..., M}. ADs map a specific network ticket to the corresponding spatiotemporal resources to achieve the required quality of service. The attributes of network tickets of type m are represented as:

[0188]

[0189] Among them, e m It is a basic attribute parameter vector related to spatiotemporal resources (bandwidth, queue, time slot, buffer, etc.) and is an additional attribute affected by the market. Specifically, is the number of available network tickets of type m in AD, The estimated value of Represents the market supply and demand relationship of m network tickets.

[0190] c. Pricing Model: To establish a charging model based on service quality, a dynamic pricing model determined by the attributes of the network ticket is proposed. The price of the m network ticket is defined as:

[0191]

[0192] where k m e m The price is determined by the basic attributes. and The value of is affected by additional properties and is updated periodically with t.

[0193] 3.2 Optimal contract solution method: First, sort the types of ADs in ascending order of their service quality, i.e. θ1<…<θ n <…<θ N ,n∈N. Here we use the lambda parameter of the exponential distribution function as the type of ADs, θ n =λ n Although SP does not know the specific type of an AD, SP has information ρ about the probability that AD belongs to type n. n ,and

[0194] To solve the information asymmetry problem, SP will provide specific contracts for ADs with different service qualities, denoted as (Γ n ,d n ), where Γ n is the QoS level provided to n types of AD (i.e. contribution d n ) reward. In addition, Γ n A supplementary reward in addition to the basic market price. ADs are free to accept or reject any type of contract. In this mechanism, ADs with better service quality will receive higher rewards, and vice versa.

[0195] Define a compensation function as F ― (λ,d), which represents the degree to which services need to be compensated when ADs cannot achieve the required QoS under limited spatiotemporal resources.

[0196] F ― (λ,d)=de ―λt ;#(13)

[0197] a. SP’s Utility: The goal of SP is to give less rewards while obtaining the desired QoS. Therefore, the profit obtained by SP from n types of AD is calculated as:

[0198]

[0199] Among them, w1, w2 and w3 are weight parameters, satisfying w1+w2+w3=1, and are the service delay satisfaction, valuation satisfaction, and price satisfaction obtained from n types of AD, respectively, and are denoted as:

[0200]

[0201] In the above formula, D is the overall demand for end-to-end services. is the minimum value that SP can tolerate. Since SP is unwilling to bear negative profit, Define the parameter ∈ to adjust the overall satisfaction level, and the expected utility of SP can be expressed as:

[0202]

[0203] b. Utility of AD: Definition is the cost of network tickets of type m, then the utility of AD of type n is expressed as:

[0204]

[0205] c. Overall social utility: Overall social utility is the sum of the utility of SP and all ADs, so:

[0206]

[0207] From formula (18), we can see that the reward is essentially an internal transfer of SP and ADs, which is offset in the calculation of social utility.

[0208] To deal with information asymmetry, the contracts selected by ADs should satisfy the following constraints and lemmas:

[0209] Definition 1 (Individual Rationality IR): Each AD participates in end-to-end customized transmission only when its utility is equal to or greater than zero, that is:

[0210]

[0211] Definition 2 (Excitation Compatibility IC): ADs should favor specific targets for their respective types θ n Customized Contract n , rather than other contracts Γ l , expressed as:

[0212]

[0213] IR and IC state the basic conditions of the contract mechanism, so the optimal contract problem is expressed as:

[0214]

[0215]

[0216]

[0217] Lemma 1 (Monotonicity): For any feasible contract, if and only if θ i ≥θ j , satisfying Γ i ≥Γ j , d i ≥d j .

[0218] Proof: IC conditions show that For simplicity, the constant term p is eliminated in the following inequality m and Γ i ―F ― (θ i ,d i )p m ≥Γ j ―F ― (θ i ,d j )p m ;#(twenty two)

[0219] Γ j ―F ― (θ j ,d j )p m ≥Γ i ―F ― (θ j ,d i )p m ;#(twenty three)

[0220] By integrating formulas (22) and (23), we obtain:

[0221] F ― (θ j ,d j )―F ― (θ j ,d j )≥F ― (θ i ,d i )―F ― (θ i ,d j );#(twenty four)

[0222]

[0223] Therefore, it can be inferred that if and only if θ i ≥θ j When d i ≥d j .

[0224] Γ i ―Γj ≥(F ― (θ i ,d i )―F ― (θ i ,d j ))p m ;#(26)

[0225] Γ j ―Γ i ≥(F ― (θ j ,d j )―F ― (θ j ,d i ))p m ;#(27)

[0226] Yu F ― (λ,d) is a monotonically increasing function of λ, so it can be proved that if and only if θ i ≥θ j When Γ i ≥Γ j .

[0227] Lemma 2: When a type 1 AD satisfies the IR condition, the IR condition holds in all ADs.

[0228] Proof: Γ i ―F ― (θ i ,d i )p m ≥Γ1―F ― (θ i ,d1)p m ≥Γ1―F ― (θ1,d1)p m .

[0229] Lemma 3: IC constraints can be simplified into local downward incentive constraints (LDICs) and local upward incentive constraints (LUICs), which are given as follows:

[0230] Γ i ―F ― (θ i ,d i )p m ≥Γ i―1 ―F ― (θ i ,d i―1 )p m;#(28)

[0231] Γ i ―F ― (θ i ,d i )p m ≥Γ i+1 ―F ― (θ i ,d i+1 )p m ;#(29)

[0232] Proof: When θ i+1 ≥θ i ≥θ i―1 , there is:

[0233] Γ i+1 ―F ― (θ i ,d i+1 )p m ≥Γ i ―F ― (θ i+1 ,d i )p m ;#(30)

[0234] Γ i ―F ― (θ i ,d i )p m ≥Γ i―1 ―F ― (θ i ,d i―1 )p m ;#(31)

[0235] F ― (θ i ,d i )p m ―F ― (θ i ,d i―1 )p m ≥F ― (θ i+1 ,d i )p m ―F[[ID=U106]] ― (θ i+1 ,d i―1 )p m ;#(32)

[0236] By integrating formulas (30), (31) and (32), we get:

[0237] Γ i+1 ―F ―(θ i+1 ,d i+1 )p m ≥Γ i―1 ―F ― (θ i+1 ,d i―1 )p m ≥…≥Γ1―F ― (θ i+1 ,d1)p m ;#(33)

[0238] In summary, LDISs and Downward Incentive Constraints (DICs) have been proven. Similarly, all LUICs and Upward Incentive Constraints (UICs) can be proven to hold by exploiting monotonicity.

[0239] To derive the optimal contract, we use the iterative method of IR and IC to express the maximization of social utility:

[0240]

[0241] Through U all Right 2 The differential of Description all It's about d 2 The concave function can be solved using convex optimization tools (CVX, Software for Disciplined Convex) to obtain the optimal value.

[0242] In summary, the present invention provides a method and device for customized service scheduling in a wide area network. The method is executed by a service provider deployed in a service interconnection layer based on a service customization network hierarchical system in the wide area network. The wide area network is divided into multiple autonomous domains. The reputation opinion parameters of each autonomous domain are calculated and stored on an open reputation blockchain, and malicious autonomous domains with reputation opinion parameters lower than a set reputation threshold are eliminated. The overall end-to-end transmission demand indicators of the target business are decomposed into intra-domain transmission demand indicators within multiple autonomous domains. Relevant contract projects are selected and published according to the intra-domain transmission demand indicators, so that each autonomous domain can freely select the corresponding contract project and provide network transmission services that meet the corresponding intra-domain transmission demand indicators, thereby realizing customized services for the autonomous domains and obtaining the expected end-to-end service quality.

[0243] Furthermore, the present invention constructs a contract model between service providers and autonomous domains and introduces individual rationality constraints and incentive compatibility constraints to solve the optimal contract, thereby maximizing the overall social utility while satisfying the customized services of the autonomous domains.

[0244] An embodiment of the present invention further provides a computer device, which may include a processor and a memory, wherein the processor and the memory may be connected via a bus or other means.

[0245] The processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0246] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as the program instructions / modules corresponding to the method for shielding buttons on an in-vehicle display device in the embodiments of the present invention. The processor executes the non-transitory software programs, instructions, and modules stored in the memory to perform various processor functions and data processing.

[0247] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include a memory remotely located relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0248] The one or more modules are stored in the memory, and when executed by the processor, perform the method described in this embodiment.

[0249] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the aforementioned edge computing server deployment method. The computer-readable storage medium may be a tangible storage medium, such as a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable storage disk, a CD-ROM, or any other form of storage medium known in the art.

[0250] It should be understood by those skilled in the art that the various exemplary components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software or a combination of the two. Whether it is specifically performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present invention are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier.

[0251] It should be understood that the present invention is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted. In the above embodiments, several specific steps are described and illustrated as examples. However, the method of the present invention is not limited to the specific steps described and illustrated. Those skilled in the art may make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present invention.

[0252] In the present invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or replace features of other embodiments.

[0253] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations to the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A service customization scheduling method in a wide area network, characterized in that: A service provider is deployed in a service interconnection layer of a wide area network based on a service customization network hierarchical system, wherein the wide area network is divided into a plurality of autonomous domains. The method is performed by the service provider and includes the following steps: The probability that each autonomous domain can guarantee the required service quality and the probability that it cannot guarantee the required service quality are obtained as positive interaction factors and negative interaction factors respectively, and the probability of successful data packet transmission is obtained as the uncertain interaction opinion factor; Calculating a reputation opinion parameter of each autonomous domain based on the positive interaction factor, the negative interaction factor, and the uncertain interaction opinion factor, and storing the parameter on an open reputation blockchain; Marking an autonomous domain whose reputation opinion parameter is lower than a set reputation threshold as a malicious autonomous domain, and removing the malicious autonomous domain from the wide area network; Decomposing the overall end-to-end transmission requirement indicator of the target service into intra-domain transmission requirement indicators of multiple autonomous domains, wherein the transmission requirement indicators include transmission delay and jitter of the transmission delay; Relevant contract items are selected and published based on the transmission demand indicators within each domain, so that each autonomous domain can freely choose the corresponding contract item and provide network transmission services that meet the transmission demand indicators within the corresponding domain; wherein the contract item is used to record the rewards provided by the service provider to the autonomous domain that meets the transmission demand indicators within the specific domain; The method further includes: decomposing the end-to-end overall transmission demand indicator of the target service into multiple autonomous domain transmission demand indicators, and solving the problem by minimizing an objective function, wherein the expression of the objective function is: f(d)=c T *d; Where d represents the solution vector, c represents the weight vector, λ1 and λ2 represent the Lagrange coefficients, and d j represents the transmission delay of the jth autonomous domain, J represents the jitter requirement of the transmission delay of the autonomous domain, and T represents discrete time; The method further comprises: Implementing network transmission services based on multiple types of network ticket interfaces within an autonomous domain, where each type of network ticket corresponds to a quality of service capability. The network ticket interface is used to implement capability mapping between the network and the application. and, dividing the autonomous domains into multiple types according to the quality of service they can provide; Obtaining attributes of each type of network ticket, wherein the attributes of each type of network ticket include basic attributes related to spatiotemporal resources and additional attributes affected by the market, wherein the additional attributes affected by the market include the available number of network tickets of the current type in the autonomous domain, the estimated value corresponding to the available number of network tickets of the current type, and the market supply and demand relationship of the network tickets of the current type; Calculate the basic market price of each type of online ticket based on the price determined by the attributes of each type of online ticket and the influencing factors of additional attributes; Arranging the types of the autonomous domains in ascending order of their quality of service; Based on the type and contribution of each autonomous domain, the compensation required for each autonomous domain when it cannot achieve the required service quality under limited time and space resources is calculated; Calculating the profit obtained by the service provider from each type of autonomous domain based on the service delay satisfaction, valuation satisfaction, price satisfaction obtained from each type of autonomous domain and their respective weights; Calculate the expected utility of the service provider, the expression is: Calculate the utility of the nth autonomous domain, the expression is: The overall social utility is calculated based on the expected utility of the service provider and the utility of each autonomous domain. The expression of the overall social utility is: in, represents the profit obtained by the service provider from the n-type autonomous domain, ∈ represents the parameter used to adjust the overall satisfaction level, represents the cost price of type m online ticket, F - represents the compensation function, θ n Indicates the type of autonomous domain, d n represents the contribution of the n-type autonomous domain, p m represents the basic market price of the m-type online ticket, Γ n represents the supplementary reward of the n-type autonomous domain in addition to the basic market price, ρ n represents the probability that the autonomous domain belongs to type n; By maximizing the overall social utility, solving the contract items includes: Individual rationality constraints and incentive compatibility constraints are introduced. The individual rationality constraint requires each autonomous domain to participate in end-to-end customized transmission only when its utility is equal to or greater than zero. The expression is: The incentive compatibility constraint requires that each autonomous domain should use a contract specifically tailored for the autonomous domain type, rather than other contracts, as expressed as: Then, the problem expression for solving the contract project by maximizing the overall social utility is: Wherein, N represents the type of the autonomous domain; The method further comprises: The iterative method based on the individual rationality constraint and the incentive compatibility constraint is used to maximize the overall social utility, which is expressed as: Through U all Right 2 The differential of That is U all It's about d 2 The concave function is solved using convex optimization tools to obtain the optimal solution for the contract project.

2. The service customization scheduling method in a wide area network according to claim 1, characterized in that: Calculating the reputation opinion parameter of each autonomous domain according to the positive interaction factor, the negative interaction factor, and the uncertain interaction opinion factor includes: The positive interaction factor, negative interaction factor, and uncertain interaction opinion factor of the autonomous domain are obtained, and the positive opinion parameter, negative opinion parameter, and uncertain opinion parameter of the service provider on the autonomous domain are calculated based on the obtained positive interaction factor, negative interaction factor, and uncertain interaction opinion factor, and the calculation expression satisfies: Among them, α t represents the positive interaction factor, β t represents the negative interaction factor, represents the uncertain interactive opinion factor, represents the positive opinion parameter, represents the negative opinion parameter, represents the uncertain opinion parameter, a represents the service provider, and b represents the autonomous domain; And, the reputation opinion parameter is calculated according to the positive opinion parameter and the uncertain opinion parameter of the autonomous domain, and the calculation expression satisfies: Among them, Ω a→b represents the reputation opinion parameter, and ν is a factor that quantifies the impact of the uncertain interactive opinion factor on reputation.

3. The service customization scheduling method in a wide area network according to claim 1, characterized in that: Decompose the overall end-to-end transmission demand indicators of the target service into intra-domain transmission demand indicators within multiple autonomous domains, including: The overall end-to-end transmission delay of the target service is decomposed into intra-domain transmission delays within multiple autonomous domains, and the risk coefficient μ is used to relax the budget of the transmission delay within each autonomous domain after decomposition. The expression is: Wherein, N0 represents the number of autonomous domains participating in the end-to-end transmission of the target service, d i represents the transmission delay of the i-th autonomous domain, where the transmission delay is obtained based on one or more of processing delay, queuing delay, sending delay, and propagation delay. D represents the end-to-end delay requirement in the wide area network; Furthermore, the jitter of the transmission delay of each autonomous domain is controlled to be less than a predetermined jitter requirement.

4. The service customization scheduling method in a wide area network according to claim 3, characterized in that: The transmission delay of the autonomous domain is calculated using the queuing delay and the sending delay, and the calculation expression satisfies: Among them, V represents the average arrival rate of data packets, L represents the number of bits of data packets, and H i represents the maximum bandwidth of the i-th autonomous domain.

5. A service customization scheduling device in a wide area network, comprising a processor and a memory, characterized in that: The memory stores computer instructions, and the processor is configured to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of the method according to any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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