Digital logistics resource sharing and collaborative scheduling system based on cloud computing platform

Abstract

The invention discloses a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform, which relates to the technical field of logistics transportation, and comprises the following steps: establishing a trust mechanism with a user accessing the cloud computing platform, establishing a long-term trust relationship under the trust mechanism, and performing credit scoring through a preset algorithm model; the logistics resource sharing database is used for dispersedly storing logistics resource data on a plurality of physical or virtual nodes by adopting a distributed storage technology, collecting user information related to node information before the information in any node is called, and verifying the authenticity of the user information; the method is used for cooperatively scheduling related data passing verification in the logistics resource database. According to the method, long-term cooperation and resource sharing among users are promoted by constructing a trust mechanism and a credit scoring system, and efficient integration and rapid access of resources are realized by combining a logistics resource sharing database constructed by a distributed storage technology.

Description

Technical Field

[0001] The present invention relates to the field of logistics and transportation technology, and in particular to a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform. Background Art

[0002] With the rapid development of the logistics industry, the demand for real-time tracking and management of logistics freight is increasing. Digital freight refers to a new freight model that uses digital technology to optimize and improve the freight process in order to improve freight efficiency, reduce freight costs, and improve freight safety and service quality. This freight model enables freight companies and users to understand the freight transportation situation more quickly and accurately.

[0003] In the field of digital logistics, the sharing and coordinated scheduling of logistics resources are of great significance to improving logistics efficiency and reducing costs. However, existing logistics resource sharing platforms often lack an effective trust evaluation mechanism, resulting in information asymmetry between resource providers and demanders, making it impossible to determine whether the information is accurate, and increasing cooperation risks and uncertainties. Summary of the invention

[0004] The purpose of the present invention is to provide a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform to address the deficiencies in the above-mentioned prior art.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform, including establishing a trust mechanism with users accessing the cloud computing platform, establishing a long-term trust relationship under this trust mechanism and performing credit scoring through a preset algorithm model, a logistics resource sharing database, which adopts distributed storage technology to store logistics resource data in a dispersed manner on multiple physical or virtual nodes, and each node is interconnected through a network to form a unified logistics resource sharing network. Before the information in any node is called, the user information related to the node information is collected and its authenticity is verified, and a resource collaborative scheduling engine is used to collaboratively schedule the relevant data that has been verified in the logistics resource database, and at the same time retrieve the credit score to provide a decision-making basis for collaborative scheduling, and then use blockchain technology to record the transaction and flow logs of logistics resources.

[0007] Preferably, the trust mechanism includes a trust evaluation module, which uses a multi-dimensional data fusion method to continuously collect historical transaction data, user evaluations and other information of each logistics resource provider, and updates the credit score in real time through a preset algorithm model.

[0008] Preferably, the trust mechanism also includes a trust threshold setting module, and the trust evaluation module provides reference data for the trust threshold setting module. The trust threshold setting module allows the platform to dynamically adjust the trust threshold and trigger corresponding security or management measures based on the evaluation results.

[0009] Preferably, the logistics resource sharing database includes a logistics resource pool and a resource sharing module. The resource sharing module allows each participant in the logistics supply chain to upload, publish and query information in the logistics resource pool, and realize real-time updating and sharing of information through a distributed sharing network.

[0010] Preferably, the resource sharing module includes an information collection and verification unit and a decision feedback unit. The information collection and verification unit is automatically triggered before any node is called, and collects user information related to the node information through the cloud computing network or external data source, including but not limited to user identity, historical transaction records, credit scores, etc., and then verifies the collected information. Based on the verification result, the decision feedback unit will make a decision on whether to allow the node information to be called, and feedback the verification result and decision result to the user and other participants in the cloud computing platform.

[0011] Preferably, the logistics resource pool adopts a distributed transaction processing protocol to ensure that the logistics resource data stored in all relevant nodes remain consistent at any point in time. When the data on a node is updated, the mechanism is automatically triggered to synchronize the updated information to other nodes.

[0012] Preferably, the resource collaborative scheduling engine supports a multi-source credit score fusion mechanism, and the trust evaluation module uses the mechanism to perform multi-dimensional fusion processing to obtain a comprehensive credit score, which serves as an important reference factor for optimizing scheduling decisions during the collaborative scheduling process.

[0013] Preferably, the resource collaborative scheduling engine has real-time monitoring and anomaly detection functions of blockchain logs. It monitors transaction records and log information in the blockchain network in real time, and uses big data analysis, machine learning and other technical means to detect potential abnormal behaviors or attack incidents. When an abnormal situation is found, the system will automatically trigger an alarm mechanism and take corresponding emergency response measures.

[0014] Preferably, a dynamic access control center is built between the cloud computing platform and the logistics resource sharing database. The dynamic access control center dynamically generates access rights for each logistics resource data based on the accessed user information and a preset user authority database. When a user tries to access the logistics resource data in a node in the logistics resource pool, the module first verifies the user's identity and authority level to ensure that the user can only access relevant data within the scope of his authorization.

[0015] Preferably, the decision feedback unit adopts dynamic authority management so that it is integrated with the authority management system of the cloud computing platform. When verification fails, the call is rejected and the information is recorded, and the user's authority or node status is dynamically adjusted.

[0016] In the above technical solution, by building a trust mechanism and a credit scoring system, long-term cooperation and resource sharing among users are promoted. Combined with the logistics resource sharing database built with distributed storage technology, efficient integration and rapid access to resources are achieved, while ensuring data authenticity and security. The resource collaborative scheduling engine combines credit scoring to intelligently schedule and optimize resource allocation based on the demand and supply of logistics resources. Credit scoring, as an important basis for decision-making, helps the scheduling engine identify trusted users and high-quality resources, thereby improving the accuracy and efficiency of resource scheduling. At the same time, this credit-based scheduling method also encourages users to maintain good behavior records and promotes the virtuous cycle of the system. The application of blockchain technology ensures the transparency and immutability of logistics resource transactions and circulation, reduces users' concerns about the authenticity of information, and overall improves the collaborative operation capabilities and resource utilization efficiency of the logistics industry.

[0017] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

[0018] This application document provides an overview of various implementations or examples of the technology described in the present disclosure, and is not a comprehensive disclosure of the entire scope or all features of the disclosed technology.

[0019] Additional aspects and advantages of the present application will be partially given in the following description, which will become apparent from the following description, or will be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0021] Figure 1 This is an overall schematic diagram of a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform of the present invention:

[0022] Figure 2 It is an overall schematic diagram of a credit mechanism in a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform of the present invention; DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0024] See also Figure 1-2 The embodiment of the present invention provides a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform, including establishing a trust mechanism with users accessing the cloud computing platform, establishing a long-term trust relationship under this trust mechanism and performing credit scoring through a preset algorithm model, a logistics resource sharing database, which adopts distributed storage technology to store logistics resource data in a plurality of physical or virtual nodes, and each node is interconnected through a network to form a unified logistics resource sharing network. Before the information in any node is called, the user information related to the node information is collected and its authenticity is verified, a resource collaborative scheduling engine, which is used to collaboratively schedule the relevant data verified in the logistics resource database, and at the same time retrieve the credit score to provide a decision-making basis for collaborative scheduling, and then use blockchain technology to record the transaction and flow log of logistics resources.

[0025] Specifically, users register an account through the cloud computing platform and submit the necessary identity information and qualification certificates. The system reviews the user information to ensure the authenticity of the user's identity, and then calculates the credit score for the user based on the preset algorithm model, taking into account the user's historical behavior (such as transaction records, service quality evaluation, etc.), industry norms and other factors. Then, based on the user's credit score, a long-term trust relationship is established between users, providing a trust basis for subsequent resource sharing and collaborative scheduling. At the same time, the logistics resource sharing database uses distributed storage technology to store logistics resource data (such as vehicle information, warehouse capacity, transportation routes, etc.) in a dispersed manner on multiple physical or virtual nodes. The nodes are interconnected through the network to form a unified and complete logistics resource sharing network. When any When the information in the node is called, the system automatically collects the user information related to the node information and verifies its authenticity. The data can be called only after the verification is passed. If the verification fails, the relevant data cannot be called. The resource collaborative scheduling engine first performs demand analysis and resource matching, receives logistics resource demand information, such as cargo type, transportation starting point and end point, time requirements, etc. The system queries the logistics resource sharing database according to the demand and matches the logistics resources that meet the demand. Then, based on the resource matching results and the user's credit score, the resource collaborative scheduling engine performs intelligent scheduling and formulates the optimal resource allocation plan. During the scheduling process, the system will consider a variety of factors, such as cost, efficiency, service quality, etc. After the scheduling plan is determined, the system automatically executes the scheduling instructions and monitors the scheduling process in real time. In the event of abnormal situations (such as insufficient resources, route changes, etc.), the system will adjust the scheduling plan in time. The entire transaction and circulation process of logistics resources is recorded using blockchain technology. Each transaction and circulation is encrypted and recorded on the blockchain to form an unalterable and traceable record. This recording method not only improves the security and credibility of the transaction, but also provides strong support for dispute resolution and regulatory audits.

[0026] Compared with the prior art, the embodiments of the present invention promote long-term cooperation and resource sharing among users by building a trust mechanism and a credit scoring system. Combined with the logistics resource sharing database built with distributed storage technology, efficient integration and rapid access to resources are achieved, while ensuring data authenticity and security. The resource collaborative scheduling engine combines credit scoring to intelligently schedule and optimize resource allocation based on the demand and supply of logistics resources. Credit scoring, as an important basis for decision-making, helps the scheduling engine identify trusted users and high-quality resources, thereby improving the accuracy and efficiency of resource scheduling. At the same time, this credit-based scheduling method also encourages users to maintain good behavior records and promotes the virtuous cycle of the system. The application of blockchain technology ensures the transparency and non-tamperability of logistics resource transactions and circulation, reduces users' concerns about the authenticity of information, and overall improves the collaborative operation capabilities and resource utilization efficiency of the logistics industry.

[0027] In a further embodiment of the present invention, the trust mechanism includes a trust evaluation module, which is a core component of the trust mechanism. The trust evaluation module uses a multidimensional data fusion method to continuously collect historical transaction data, user evaluations and other information of each logistics resource provider, and updates the credit score in real time through a preset algorithm model. The trust evaluation module mainly collects past transaction records of logistics resource providers through a logistics resource sharing database, including transaction times, transaction amounts, transaction success rates, default situations, etc., and also collects evaluation information on logistics resource providers from the user side, including evaluations of dimensions such as service attitude, response speed, cargo integrity, and punctuality. There are also data sources from other aspects, such as government regulatory data, industry association ratings, social media public opinion, etc., as auxiliary data sources, to further enrich the dimensions of credit evaluation. The trust evaluation module is updated in real time. The trust evaluation module will update the credit score of the logistics resource provider regularly or in a triggered manner. The triggering method is a new transaction or a user evaluation update. During the update process, the latest data will be re-collected, processed and analyzed, and the credit score will be recalculated to ensure the timeliness and accuracy of the credit evaluation.

[0028] In a further embodiment of the present invention, the trust mechanism also includes a trust threshold setting module, and the trust evaluation module provides reference data for the trust threshold setting module. The trust threshold setting module allows the platform to dynamically adjust the trust threshold and trigger corresponding security or management measures based on the evaluation results. The trust threshold setting module is responsible for setting one or more trust thresholds, which are used to determine whether the credit score of the entity meets specific standards. When the credit score of the entity is lower than a certain threshold, the system will take a series of measures (such as restricting access, warnings, penalties, etc.) to deal with potential risks. The trust evaluation module provides the trust threshold setting module with evaluation results (i.e., credit scores), which is an important basis for setting reasonable thresholds. The trust threshold setting module sets or adjusts the thresholds based on these evaluation results and the actual needs of the system.

[0029] In a further embodiment of the present invention, the logistics resource sharing database includes a logistics resource pool and a resource sharing module. The resource sharing module allows each participant in the logistics supply chain to upload, publish and query information in the logistics resource pool, and realize real-time updating and sharing of information through a distributed sharing network. Specifically, the logistics resource pool is the core area in the database that stores all sharable logistics resources. These resources include but are not limited to transportation tools, storage facilities, human resources, and their skills, experience, availability and other information, technical resources, etc. The resource sharing module is a bridge connecting the various participants in the logistics supply chain with the logistics resource pool, facilitating the uploading and query of information, and through the distributed sharing network, ensuring that the information in the logistics resource pool can be updated in real time and synchronized to the systems of all participants, which helps to reduce information asymmetry.

[0030] In a further embodiment of the present invention, the resource sharing module includes an information collection and verification unit and a decision feedback unit. The information collection and verification unit is automatically triggered before any node is called, and user information related to the node information is collected through the cloud computing network or external data source, including but not limited to user identity, historical transaction records, credit scores, etc., and then the collected information is verified. When any node in the logistics supply chain (such as a carrier, warehouse, cargo owner, etc.) attempts to upload, publish or query logistics resource information, the information collection and verification unit will be automatically triggered. This mechanism is implemented by monitoring network requests or database operation events to ensure that all information interaction behaviors are subject to a strict verification process. Based on the verification results, the decision feedback unit will make a decision on whether to allow the node information to be called, and feedback the verification results and decision results to the user and other participants in the cloud computing platform. To ensure the transparency and traceability of the system, all decision-making processes and feedback results will be recorded in detail in the system log.

[0031] In a further embodiment of the present invention, the logistics resource pool adopts a distributed transaction processing protocol to ensure that the logistics resource data stored in all relevant nodes remain consistent at any point in time. When the data on a certain node is updated, the mechanism is automatically triggered to synchronize the updated information to other nodes, so that users who extract the data can obtain the synchronized updated data in a timely manner, thereby avoiding cooperation problems between upstream and downstream due to data errors.

[0032] In a further embodiment of the present invention, the resource collaborative scheduling engine supports a multi-source credit score fusion mechanism. The trust evaluation module adopts the multi-dimensional fusion processing of the mechanism to obtain a comprehensive credit score. The comprehensive credit score serves as an important reference factor for optimizing scheduling decisions in the collaborative scheduling process. The resource collaborative scheduling engine uses the comprehensive credit score obtained by the trust evaluation module as one of the important reference factors for resource collaborative scheduling, and incorporates it into the optimization model of scheduling decisions. The optimization model will consider multiple objectives (such as minimizing costs, minimizing time, optimizing service quality, etc.), and adjust weights or prioritize them according to the comprehensive credit scores of each participant to formulate the optimal scheduling plan.

[0033] In a further embodiment of the present invention, the resource collaborative scheduling engine has real-time monitoring and anomaly detection functions of blockchain logs. It monitors transaction records and log information in the blockchain network in real time. To facilitate administrators and operators to monitor the real-time status of the blockchain network, the resource collaborative scheduling engine provides an intuitive monitoring interface. The interface displays key indicators such as the operating status, transaction volume, and block generation speed of the blockchain network, and allows users to set customized monitoring items according to their needs. It also uses big data analysis, machine learning and other technical means to detect potential abnormal behaviors or attack events. It uses big data analysis technology combined with machine learning algorithms to conduct in-depth mining and intelligent analysis of blockchain log data. By building a data model, analyzing transaction patterns, block generation rules and other features, it identifies abnormal transactions or blocks that do not conform to normal behavior patterns. When an abnormal situation is found, the system will automatically trigger an alarm mechanism and take corresponding emergency measures.

[0034] In a further embodiment of the present invention, a dynamic access control center is built between the cloud computing platform and the logistics resource sharing database. The dynamic access control center first needs to collect and manage the basic information of all access users, including but not limited to user name, password, identity authentication information (such as biometrics, digital certificates, etc.) and the organization or role to which they belong, etc. This information will serve as the basis for subsequent permission verification. The dynamic access control center dynamically generates access rights for each logistics resource data based on the above information and in combination with a preset user permission database. When a user attempts to access the system, the corresponding permission record will be searched in the preset user permission database based on the user's identity information. At the same time, in combination with dynamic conditions such as the current business scenario and time factors, the access rights for the user are dynamically generated. This mechanism can flexibly respond to requirements such as permission changes and temporary authorization. When a user attempts to access logistics resource data in a node in the logistics resource pool, the module first verifies the user's identity and permission level to ensure that the user can only access relevant data within the scope of his authorization, which helps to reduce potential security risks and data leakage incidents.

[0035] In a further embodiment of the present invention, the decision feedback unit adopts dynamic permission management, so that it is integrated with the permission management system of the cloud computing platform through an API interface or a message queue, etc. This integration method ensures that the decision feedback unit can obtain the user's permission information in real time and perform permission verification when executing scheduling decisions. When the verification fails, the call is rejected and the information is recorded. At the same time, the user's permissions or node status are dynamically adjusted according to preset rules and policies. This adjustment can be temporary, such as temporarily reducing the user's permissions to limit their access scope, or it can be permanent, such as adjusting their roles and permissions in the system according to the results of user behavior analysis. In addition, if a node is detected to have abnormal behavior or security risks, the decision feedback unit can also isolate the node or restrict its access rights to further improve the confidentiality of resources.

[0036] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that, for those skilled in the art, the described embodiments can be modified in various ways without departing from the spirit and scope of the present invention. Therefore, the above description is illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform, characterized in that: include: Establishing a trust mechanism with users accessing the cloud computing platform, establishing a long-term trust relationship under this trust mechanism and performing credit scoring through a preset algorithm model; The logistics resource sharing database adopts distributed storage technology to store logistics resource data in multiple physical or virtual nodes. The nodes are interconnected through the network to form a unified logistics resource sharing network. Before the information in any node is called, the user information related to the node information is collected and its authenticity is verified; The resource collaborative scheduling engine is used to collaboratively schedule relevant data that has been verified in the logistics resource database, and at the same time retrieve the credit score to provide a decision-making basis for collaborative scheduling, and then use blockchain technology to record the transaction and flow logs of logistics resources.

2. According to claim 1, a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform is characterized in that: The trust mechanism includes a trust evaluation module, which uses a multi-dimensional data fusion method to continuously collect historical transaction data, user evaluations and other information from each logistics resource provider, and updates the credit score in real time through a preset algorithm model.

3. According to claim 2, a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform is characterized in that: The trust mechanism also includes a trust threshold setting module. The trust evaluation module provides reference data for the trust threshold setting module. The trust threshold setting module allows the platform to dynamically adjust the trust threshold and trigger corresponding security or management measures based on the evaluation results.

4. According to the digital logistics resource sharing and collaborative scheduling system based on cloud computing platform of claim 1, it is characterized in that: The logistics resource sharing database includes a logistics resource pool and a resource sharing module. The resource sharing module allows each participant in the logistics supply chain to upload, publish and query information in the logistics resource pool, and realize real-time updating and sharing of information through a distributed sharing network.

5. According to claim 4, a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform is characterized in that: The resource sharing module includes an information collection and verification unit and a decision feedback unit. The information collection and verification unit is automatically triggered before any node is called, and collects user information related to the node information through the cloud computing network or external data source, including but not limited to user identity, historical transaction records, credit scores, etc., and then verifies the collected information. Based on the verification results, the decision feedback unit will make a decision on whether to allow the node information to be called, and feedback the verification results and decision results to the user and other participants in the cloud computing platform.

6. According to claim 4, a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform is characterized in that: The logistics resource pool adopts a distributed transaction processing protocol to ensure that the logistics resource data stored in all relevant nodes remain consistent at any point in time. When the data on a node is updated, the mechanism is automatically triggered to synchronize the updated information to other nodes.

7. According to claim 2, a digital logistics resource sharing and collaborative scheduling system based on a cloud computing platform is characterized in that: The resource collaborative scheduling engine supports a multi-source credit score fusion mechanism. The trust evaluation module uses this mechanism to obtain a comprehensive credit score after multi-dimensional fusion processing. The comprehensive credit score serves as an important reference factor for optimizing scheduling decisions during the collaborative scheduling process.

8. According to the digital logistics resource sharing and collaborative scheduling system based on cloud computing platform of claim 1, it is characterized in that: The resource collaborative scheduling engine has real-time monitoring and anomaly detection functions for blockchain logs. It monitors transaction records and log information in the blockchain network in real time, and uses big data analysis, machine learning and other technical means to detect potential abnormal behaviors or attack incidents. When an abnormal situation is detected, the system will automatically trigger an alarm mechanism and take corresponding emergency response measures.

9. According to the digital logistics resource sharing and collaborative scheduling system based on cloud computing platform of claim 1, it is characterized in that: A dynamic access control center is built between the cloud computing platform and the logistics resource sharing database. The dynamic access control center dynamically generates access rights for each logistics resource data based on the user information of the access and the preset user authority database. When a user tries to access the logistics resource data in a node in the logistics resource pool, the module first verifies the user's identity and authority level to ensure that the user can only access relevant data within his or her authorized scope.

10. The digital logistics resource sharing and collaborative scheduling system based on cloud computing platform according to claim 5 is characterized in that: The decision feedback unit adopts dynamic authority management to integrate it with the authority management system of the cloud computing platform. When verification fails, the call is rejected and the information is recorded, and the user's authority or node status is dynamically adjusted.

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