Enterprise cost optimization method and system based on big data

Abstract

The invention provides an enterprise cost optimization method and system based on big data, belongs to the technical field of big data, and is used for realizing flexible and efficient cost optimization through a container packaging mode. The method comprises the following steps: the electronic equipment obtains a flow of a service, the flow of the service comprises N flow nodes, and N is an integer greater than 1; aiming at a target process node in the N process nodes, the electronic equipment configures at least one container for the target process node, each container in the at least one container is packaged with a cost optimization strategy provided for the target process node, and the target process node is any one of the N process nodes; and the electronic equipment determines an optimal cost optimization result of the service through the containers configured to the N process nodes respectively.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to a method and system for optimizing enterprise costs based on big data. Background Art

[0002] With the increasingly fierce market competition and the complex and ever-changing business operating environment, how to effectively manage and control operating costs has become an important issue for enterprises. Cost optimization, as a scientific cost management method, can effectively calculate and optimize the operating costs of enterprises by configuring cost optimization strategies, thereby improving the competitiveness of enterprises.

[0003] Cost optimization strategy is an algorithm formula for calculating and optimizing operating costs generated based on the operation of the enterprise. These strategies can automatically perform cost accounting, monitor cost changes in real time, and promptly discover and solve cost problems, thereby achieving effective control and optimization of operating costs. For enterprises, having an effective cost optimization strategy can not only improve the accuracy and efficiency of cost management, but also help improve the operating benefits and market competitiveness of enterprises. The implementation of cost optimization strategy is as follows: Data collection: Collect the operating data of the enterprise, including but not limited to sales data, production data, human resources data, etc. Data analysis: Use data analysis technology to conduct in-depth analysis of the collected data to find out the key factors of cost changes. Strategy formulation: According to the results of data analysis, formulate a cost optimization strategy suitable for the enterprise. Strategy implementation: Apply the formulated strategy to the operation of the enterprise, monitor cost changes in real time, and adjust the strategy in time. Strategy optimization: According to the effect of strategy implementation, continuously optimize the strategy to improve the efficiency and effectiveness of cost management.

[0004] However, in future scenarios, enterprises may need to be more flexible in cost optimization, and how to meet this demand is a current research issue. Summary of the invention

[0005] The embodiment of the present application provides an enterprise cost optimization method based on big data, which is used to achieve flexible and efficient cost optimization through container encapsulation.

[0006] In order to achieve the above objectives, this application adopts the following technical solutions:

[0007] In the first aspect, an embodiment of the present application provides an enterprise cost optimization method based on big data, which is applied to an electronic device, the method comprising: the electronic device obtains a business process, the business process includes N process nodes, N is an integer greater than 1; for a target process node among the N process nodes, the electronic device configures at least one container for the target process node, each of the at least one container is encapsulated with a cost optimization strategy provided for the target process node, and the target process node is any one of the N process nodes; the electronic device determines the optimal cost optimization result of the business through the containers configured for each of the N process nodes.

[0008] Optionally, the electronic device configures at least one container for the target process node, including: the electronic device determines at least one container suitable for the node type from a container library based on the node type of the target process node; and the electronic device configures the at least one container suitable for the node type to the target process node.

[0009] Optionally, the node type of the target process node can represent the cost generation rule of the target process node, and at least one container is applicable to the node type, which means that the cost optimization strategies encapsulated in at least one container are applicable to optimizing the cost of the target process node, and the cost of the target process node is determined based on the cost generation rule of the target process node.

[0010] Optionally, the electronic device determines the optimal cost optimization result of the business through the containers configured for each of the N process nodes, including: the electronic device combines the containers configured for each of the N process nodes to obtain multiple container combinations; the electronic device determines the cost optimization result of the business under each container combination in the multiple container combinations to obtain multiple cost optimization results; the electronic device determines the optimal cost optimization result of the business from the multiple cost optimization results.

[0011] Optionally, for the i-th process node among N process nodes, i is an integer ranging from 1 to N-1, and the i-th process node is configured with M i The cost optimization strategy encapsulated in Mi containers has different cost optimization methods for the i-th process. For the i+1th process node among N process nodes, the i+1th process node is configured with M i+1 Container, M i+1 The cost optimization strategy for packaging containers is different for the cost optimization method of the i+1th process; the electronic device combines the containers configured for each of the N process nodes to obtain a variety of container combinations, including: the electronic device combines the M configured for the i-th process node i The container and the i+1th process node are configured with M i+1container combinations, when i traverses from 1 to N-1, K container combinations are obtained, K is an integer greater than 1, and each of the K container combinations includes a container configured for each of the N process nodes.

[0012] Optionally, for a target container combination in the K container combinations, the target container combination is any one of the K container combinations; the electronic device determines a cost optimization result of the service under each container combination in the multiple container combinations, and obtains multiple cost optimization results, including: the electronic device inputs the available resources of the i-th process node into a container i configured for the i-th process node in the target container combination, and obtains the cost of the i-th process node output by the container i; the container i is M i a container in the target container combination; if i=1, the available resources of the i-th process node are the resources pre-configured by the business for the 1st process node; the electronic device determines the available resources of the i+1th process node according to the cost of the i-th process node; the electronic device inputs the available resources of the i+1th process node into a container i+1 configured for the i+1th process node in the target container combination, and obtains the cost of the i+1th process node output by the container i+1; the container i+1 is M i+1 a container among containers; when i traverses 1 to N-1, the electronic device obtains the cost of each of the N process nodes, and sums up the costs of each of the N process nodes to obtain a cost of the business for the target container combination, and for K container combinations, the electronic device obtains a total of K costs of the business; the electronic device determines the optimal cost optimization result of the business from multiple cost optimization results, including: the electronic device determines the lowest cost from the K costs of the business, and the lowest cost is the optimal cost optimization result of the business.

[0013] Optionally, the cost of the i-th process node is the ciphertext information i encrypted and output by container i, and the electronic device is configured to first decrypt the ciphertext information i to obtain plaintext; the cost of the i+1-th process node is the ciphertext information i+1 encrypted and output by container i+1, and the electronic device is configured to first decrypt the ciphertext information i+1 to obtain plaintext.

[0014] Optionally, the plaintext information of the cost of the i-th process node is P bits, P is an integer greater than 3, and the container i is configured to: use a preset key to encrypt the PmodR1-th bit to the PmodR2-th bit of the P bits to obtain a first segment of ciphertext information, wherein there are Q bits remaining after the PmodR2-th bit of the P bits, Q is an integer greater than 1, and the container i is further configured to: use a preset key to encrypt the QmodR3-th bit to the QmodR4-th bit of the Q bits to obtain a second segment of ciphertext information; the container i is further configured to: encrypt the 1-th bit to the PmodR1-1-th bit of the P bits The first section of ciphertext information, the 1st bit to the QmodR3-1th bit of the Q bits, the second section of ciphertext information, and the QmodR4+1th bit to the Qth bit of the Q bits are sequentially spliced ​​to obtain the ciphertext information of the cost of the i-th process node; wherein mod represents a modulus operation, R1 is the sum of the count value of the counter of container i and the random natural number s1 randomly generated by container i, R2 is the sum of the count value and the random natural number s2 randomly generated by container i, R3 is the sum of the count value and the random natural number s3 randomly generated by container i, and R4 is the sum of the count value and the random natural number s4 randomly generated by container i.

[0015] Optionally, container i is also configured to synchronously provide random natural numbers s1, s2, s3 and s4 to the electronic device while providing ciphertext information of the cost of the i-th process node to the electronic device, and the count value of the counter of container i+1 is synchronized with the count value of the counter of container i.

[0016] In the second aspect, an embodiment of the present application provides a cost optimization strategy for containerized applications and an implementation system thereof, a big data-based enterprise cost optimization method and system applied to electronic devices, and the system is configured as follows: the system obtains a business process, and the business process includes N process nodes, where N is an integer greater than 1; for the i-th process node among the N process nodes, i is an integer traversing from 1 to N, the system configures at least one container for the i-th process node, and each container in the at least one container is encapsulated with a cost optimization strategy provided for the i-th process node; the system determines the optimal cost optimization strategy for the business based on the containers configured for each of the N process nodes.

[0017] Optionally, the system configures at least one container for the target process node, including: the system determines at least one container suitable for the node type from a container library based on the node type of the target process node; the system configures the at least one container suitable for the node type to the target process node.

[0018] Optionally, the node type of the target process node can represent the cost generation rule of the target process node, and at least one container is applicable to the node type, which means that the cost optimization strategies encapsulated in at least one container are applicable to optimizing the cost of the target process node, and the cost of the target process node is determined based on the cost generation rule of the target process node.

[0019] Optionally, the system determines the optimal cost optimization result of the business through the containers configured for each of the N process nodes, including: the system combines the containers configured for each of the N process nodes to obtain multiple container combinations; the system determines the cost optimization result of the business under each container combination in the multiple container combinations to obtain multiple cost optimization results; the system determines the optimal cost optimization result of the business from the multiple cost optimization results.

[0020] Optionally, for the i-th process node among N process nodes, i is an integer ranging from 1 to N-1, and the i-th process node is configured with M i The cost optimization strategy encapsulated in Mi containers has different cost optimization methods for the i-th process. For the i+1th process node among N process nodes, the i+1th process node is configured with M i+1 Container, M i+1 The cost optimization strategy encapsulated in the i+1th process has different cost optimization methods for the i+1th process; the system combines the containers configured for each of the N process nodes to obtain multiple container combinations, including: the system combines the M configured for the i-th process node i The container and the i+1th process node are configured with M i+1 container combinations, when i traverses from 1 to N-1, K container combinations are obtained, K is an integer greater than 1, and each of the K container combinations includes a container configured for each of the N process nodes.

[0021] Optionally, for a target container combination in the K container combinations, the target container combination is any one of the K container combinations; the system determines a cost optimization result of the business under each of the multiple container combinations, and obtains multiple cost optimization results, including: the system inputs the available resources of the i-th process node into a container i configured for the i-th process node in the target container combination, and obtains the cost of the i-th process node output by the container i; container i is M i a container in the target container combination; if i=1, the available resources of the i-th process node are the resources pre-configured by the business for the 1st process node; the system determines the available resources of the i+1th process node based on the cost of the i-th process node; the system inputs the available resources of the i+1th process node into a container i+1 configured for the i+1th process node in the target container combination, and obtains the cost of the i+1th process node output by container i+1; container i+1 is Mi+1 a container among containers; when i traverses 1 to N-1, the system obtains the cost of each of the N process nodes, and sums up the costs of each of the N process nodes to obtain a cost of the business for the target container combination. For K container combinations, the system obtains K costs of the business in total; the system determines the optimal cost optimization result of the business from multiple cost optimization results, including: the system determines the lowest cost from the K costs of the business, and the lowest cost is the optimal cost optimization result of the business.

[0022] Optionally, the cost of the i-th process node is the ciphertext information i encrypted and output by container i, and the system is configured to first decrypt the ciphertext information i to obtain plaintext; the cost of the i+1-th process node is the ciphertext information i+1 encrypted and output by container i+1, and the system is configured to first decrypt the ciphertext information i+1 to obtain plaintext.

[0023] Optionally, the plaintext information of the cost of the i-th process node is P bits, P is an integer greater than 3, and the container i is configured to: use a preset key to encrypt the PmodR1-th bit to the PmodR2-th bit of the P bits to obtain a first segment of ciphertext information, wherein there are Q bits remaining after the PmodR2-th bit of the P bits, Q is an integer greater than 1, and the container i is further configured to: use a preset key to encrypt the QmodR3-th bit to the QmodR4-th bit of the Q bits to obtain a second segment of ciphertext information; the container i is further configured to: encrypt the 1-th bit to the PmodR1-1-th bit of the P bits The first section of ciphertext information, the 1st bit to the QmodR3-1th bit of the Q bits, the second section of ciphertext information, and the QmodR4+1th bit to the Qth bit of the Q bits are sequentially spliced ​​to obtain the ciphertext information of the cost of the i-th process node; wherein mod represents a modulus operation, R1 is the sum of the count value of the counter of container i and the random natural number s1 randomly generated by container i, R2 is the sum of the count value and the random natural number s2 randomly generated by container i, R3 is the sum of the count value and the random natural number s3 randomly generated by container i, and R4 is the sum of the count value and the random natural number s4 randomly generated by container i.

[0024] Optionally, container i is also configured to synchronously provide random natural number s1, random natural number s2, random natural number s3 and random natural number s4 to the system while providing the system with ciphertext information of the cost of the i-th process node, and the count value of the counter of container i+1 is synchronized with the count value of the counter of container i.

[0025] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having program code stored thereon. When the program code is executed by the computer, the method described in the first aspect is executed.

[0026] In summary, the above method and system have the following technical effects:

[0027] When obtaining the process of a business, the electronic device can configure at least one container for each process node of the process to provide at least one cost optimization strategy. In this way, the electronic device can determine the cost optimization results of the business under different cost optimization strategies based on the different cost optimization strategies provided by the container configured for each process node, thereby ultimately being able to determine the optimal cost optimization result of the business and achieve flexible and efficient cost optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A flowchart of a method for optimizing enterprise costs based on big data provided in an embodiment of the present application;

[0029] Figure 2 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] In the embodiment of the present invention, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association relationship between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each information agreed in advance (for example, specified by the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0031] In addition, the specific indication method may also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can refer to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, different indication methods may be used for different information. In the specific implementation process, the desired indication method can be selected according to specific needs. The embodiment of the present invention does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present invention should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0032] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiment of the present invention. Among them, the sending period and / or sending time of these sub-information can be pre-defined, for example, pre-defined according to a protocol, or can be configured by the sending end device by sending configuration information to the receiving end device.

[0033] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present invention do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or an electronic device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or an electronic device. The type of memory can be any form of storage medium, which is not limited by the embodiments of the present invention.

[0034] The "protocol" involved in the embodiments of the present invention may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol in a reliable access method system for future Internet of Things devices, and the embodiments of the present invention do not specifically limit this.

[0035] In the embodiments of the present invention, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will perform corresponding processing under certain objective circumstances, but do not limit the time, nor do they require the device to perform judgment actions when implementing, nor do they mean the existence of other limitations.

[0036] In the description of the embodiments of the present invention, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the embodiments of the present invention is only a kind of association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In addition, in the description of the embodiments of the present invention, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solution of the embodiments of the present invention, in the embodiments of the present invention, the words "first" and "second" are used to distinguish the same items or similar items with basically the same functions and effects. Those skilled in the art will appreciate that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference. At the same time, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0037] The architecture and business scenarios described in the embodiments of the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. A person of ordinary skill in the art can appreciate that with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

[0038] First, the concept of the container involved in this application is introduced:

[0039] Container technology in cloud computing is a lightweight, portable virtualization technology that allows applications and their dependencies to be packaged into a container that can run independently. This technology enables applications to run in the same way in any environment, enabling rapid deployment and seamless migration.

[0040] The essence of the container:

[0041] Process: A container is essentially a process that divides resources, files, devices, states, and configurations into an independent space through technologies such as namespaces and control groups. Image: A container image is similar to an installation package that contains everything an application needs to run, including code, runtime environment, system libraries, and configuration files.

[0042] Features of the container:

[0043] Lightweight: Containers share the host machine's kernel and do not need to run a complete operating system for each container, so they start and stop faster and use fewer resources. Portability: Containers can run across platforms without worrying about differences in operating systems or environments, which allows applications to be quickly migrated between different environments. Efficiency: Because they share the host machine kernel, containerized applications run directly on the host operating system without an additional virtualization layer, so they have lower performance overhead.

[0044] Key technologies:

[0045] Docker: Docker is a representative tool of containerization technology, which provides an open platform for developing, shipping and running applications. Docker defines the container building process through Dockerfile and uses Docker Engine to create and manage containers. Kubernetes: Kubernetes (K8s for short) is an open source container orchestration platform that is used to automate the deployment, expansion and management of containerized applications. Kubernetes realizes the automated management of container clusters by defining a set of objects such as Pod (container group), Service (service), and Deployment (deployment).

[0046] Application Scenario

[0047] Microservice architecture: In a microservice architecture, each service is an independent container. By using Docker and Kubernetes, developers can easily achieve rapid deployment and dynamic expansion of services. Continuous Integration / Continuous Deployment (CI / CD): Containerization technology provides great convenience for the CI / CD process. Through Docker images, developers can ensure that exactly the same application version is used in development, testing, and production environments. Container cloud platform: Many companies have begun to build their own container cloud platforms to better manage and utilize container resources. These platforms usually include functions such as container management, monitoring, log collection, and network configuration.

[0048] In short, container technology plays an important role in cloud computing. Through its lightweight, portable and efficient characteristics, it greatly simplifies the deployment, management and expansion process of applications, becoming one of the cornerstones of modern cloud-native application development.

[0049] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0050] See also Figure 1 , the embodiment of the present application provides a method for enterprise cost optimization based on big data. The method is executed by an electronic device, and the process of the method includes:

[0051] S101, process of electronic device acquiring services.

[0052] The business process includes N process nodes, where N is an integer greater than 1. Business can be information at the enterprise level, such as a certain business of a certain enterprise, such as the business of selling a certain product, or the establishment of a certain mechanism within the enterprise, without any specific restrictions. N process nodes means that the completion of the business requires the cooperation of N departments / institutions of the enterprise, and the link completed by each department / institution is a process node of the business, such as product design → product manufacturing → product testing → product operation → product sales → product after-sales, etc.

[0053] The process of the electronic device acquiring the service may be acquired in a preconfigured manner, or may be acquired dynamically, such as from other devices, such as from an enterprise database, without specific limitation. The process of the electronic device acquiring the service may be information of the process of acquiring the service, and the information may include the node type of each process node, and specifically may be information of the department / institution corresponding to the process node, such as the name or logo.

[0054] S102, for a target process node among the N process nodes, the electronic device configures at least one container for the target process node.

[0055] Among them, in at least one container configured for the target process node, each container is encapsulated with a cost optimization strategy provided for the target process node, and the target process node is any one of the N process nodes.

[0056] The electronic device can determine at least one container suitable for the node type from the container library according to the node type of the target process node. The node type of the target process node can represent the cost generation rule of the target process node. The cost of the target process node is determined based on the cost generation rule of the target process node, that is, when the department / institution corresponding to the target process node completes the node link corresponding to the business, what kind of rules will be used to generate the corresponding cost. For example, taking product manufacturing as an example, the rules generated by product manufacturing include manually controlling equipment to produce materials, so the cost of product manufacturing includes: material cost, labor cost, equipment loss cost, etc. At least one container is applicable to the node type means that the cost optimization strategies encapsulated in at least one container are applicable to optimizing the cost of the target process node. Taking product manufacturing as an example, the algorithm or formula of the cost optimization strategy configured for the container corresponding to product manufacturing is used to optimize the cost of product manufacturing by optimizing the material cost at a certain production efficiency (determined by the cost of labor and equipment). For example, the cost of a single person, the cost of purchasing a single device, the cost of operating loss of a single device, and the cost of optimized materials can be pre-configured. In this way, by inputting the number of personnel, the number of equipment, and the number of materials into the algorithm or formula of the cost optimization strategy, combined with the above pre-configured parameters, the cost of optimized product production can be obtained. The number of personnel, the number of equipment, and the number of materials can be available resources for product production, and the specifics can also be referred to the following introduction.

[0057] The electronic device configures at least one container suitable for the node type to the target process node, that is, establishes a corresponding relationship between the identifier of the at least one container and the information of the target process node.

[0058] S103, the electronic device determines the optimal cost optimization result of the business through the containers configured in each of the N process nodes.

[0059] The electronic device combines the containers configured for the N process nodes respectively to obtain a plurality of container combinations.

[0060] For example, for the i-th process node among N process nodes, i is an integer ranging from 1 to N-1, and the i-th process node is configured with M i The cost optimization strategy encapsulated in Mi containers has different cost optimization methods for the i-th process (or different focuses). Taking product production as an example, the cost optimization strategy for one container corresponding to product production in the above example is to optimize material costs, and the cost optimization strategy for another container corresponding to product production is to optimize equipment costs. For example, the cost of a single person, the cost of purchasing a single device after optimization, the cost of operating losses of a single device, and the cost of materials can be pre-configured. Similarly, for the i+1th process node among N process nodes, the i+1th process node is configured with Mi+1 Container, M i+1 The cost optimization strategy for encapsulating the i+1th process has different cost optimization methods for the i+1th process.

[0061] On this basis, the electronic device can configure the M i The container and the i+1th process node are configured with M i+1 The combination of containers gives M i* M i+1 There are K combinations of containers. When i traverses from 1 to N-1, K combinations of containers are obtained. K is an integer greater than 1. Each of the K combinations of containers includes a container configured for each of the N process nodes. For example, N=3, the containers corresponding to the first process node are container C11, container C12, and container C12, the containers corresponding to the second process node are container C21 and container C22, and the container corresponding to the third process node is container C3. K=6, which are container C11→container C21→container C3, container C12→container C21→container C3, container C13→container C21→container C3, container C11→container C22→container C3, container C12→container C22→container C3, and container C13→container C22→container C3.

[0062] The electronic device determines the cost optimization result of the business under each container combination in multiple container combinations, and obtains multiple cost optimization results.

[0063] For example, for a target container combination among K container combinations, the target container combination is any container combination among the K container combinations; the electronic device can input the available resources of the i-th process node into a container i configured for the i-th process node in the target container combination, and obtain the cost of the i-th process node output by container i. For example, by inputting the number of personnel, the number of equipment, and the number of materials into the algorithm or formula of the cost optimization strategy, combined with the above pre-configured parameters, the cost of optimized product production can be obtained. Container i is M i A container in a container, or a container corresponding to the i-th process node in the target container combination; if i=1, the available resources of the i-th process node are the resources pre-configured by the business for the first process node. The resources vary according to the business. Taking product design as an example, the available resources for product design can be the number of personnel, the number of design software, the number of simulation software, etc.

[0064] The electronic device determines the available resources of the i+1th process node according to the cost of the i-th process node. The cost of the i-th process node corresponds to the available resources of the i+1th process node. If the cost of the i-th process node is larger, the available resources of the i+1th process node will be relatively smaller, otherwise, the cost will be uncontrollable. On the contrary, if the cost of the i-th process node is smaller, the available resources of the i+1th process node will be relatively larger, that is, a dynamic cost balance is achieved. If the cost of a process node is relatively large, the available resources of the next process node will be relatively smaller to control the cost of the next process node. For example, when the cost of the i-th process node is relatively small, the number of personnel in the available resources of the i+1th process node corresponding to the i-th process node can be 20 people. When the cost of the i-th process node is relatively large, the number of personnel in the available resources of the i+1th process node corresponding to the i-th process node can be 18 people. However, no matter how the cost of the i-th process node changes, the various available resources of the i+1-th process node are reasonable, that is, they are dynamically fine-tuned while satisfying the completion of the business. The corresponding relationship between the cost of the i-th process node and the available resources of the i+1-th process node can be the correspondence between the cost range of the i-th process node and the available resources of the i+1-th process node.

[0065] The electronic device inputs the available resources of the i+1th process node into a container i+1 configured for the i+1th process node in the target container combination, and obtains the cost of the i+1th process node output by container i+1. Container i+1 is M i+1 A container in a container is similar to the above, and will not be described in detail.

[0066] When i traverses from 1 to N-1, the electronic device obtains the cost of each of the N process nodes, and sums up the costs of each of the N process nodes to obtain a cost of the business for the target container combination. For K container combinations, the electronic device obtains a total of K costs of the business, such as K=6, i.e., 6 costs.

[0067] The electronic device can determine the optimal cost optimization result of the service from multiple cost optimization results. For example, the electronic device can determine the lowest cost from K kinds of costs of the service, and the lowest cost is the optimal cost optimization result of the service.

[0068] Optionally, the cost of the i-th process node is the ciphertext information i encrypted and output by container i, and the electronic device is configured to first decrypt the ciphertext information i to obtain plaintext; the cost of the i+1-th process node is the ciphertext information i+1 encrypted and output by container i+1, and the electronic device is configured to first decrypt the ciphertext information i+1 to obtain plaintext, that is, the cost is the user's privacy information, and the communication between the electronic device and the container needs to be encrypted to avoid leakage of privacy information.

[0069] Specifically, the plaintext information of the cost of the i-th process node is P bits, P is an integer greater than 3, and the container i is configured to: use a preset key to encrypt the PmodR1-th bit to the PmodR2-th bit of the P bits to obtain a first segment of ciphertext information, wherein, after the PmodR2-th bit of the P bits, there are Q bits remaining, Q is an integer greater than 1, and the container i is further configured to: use a preset key to encrypt the QmodR3-th bit to the QmodR4-th bit of the Q bits to obtain a second segment of ciphertext information; the container i is further configured to: sequentially concatenate the 1st to PmodR1-1-th bits of the P bits, the first segment of ciphertext information, the 1st to QmodR3-1-th bits of the Q bits, the second segment of ciphertext information, and the QmodR4+1-th bit to the Q-th bit of the Q bits to obtain the ciphertext information of the cost of the i-th process node;

[0070] Among them, mod represents the modulus operation, R1 is the sum of the count value of the counter of container i and the random natural number s1 randomly generated by container i, R2 is the sum of the count value and the random natural number s2 randomly generated by container i, R3 is the sum of the count value and the random natural number s3 randomly generated by container i, and R4 is the sum of the count value and the random natural number s4 randomly generated by container i.

[0071] Among them, when container i generates random natural numbers s1-s2, it needs to consider whether the sum of random natural numbers s1-s2 and the count value is greater than P. If it is greater, it will be regenerated. If it is less, it will be used, that is, the above logic will be executed. Similarly, when container i generates random natural numbers s3-s4, it needs to consider whether the sum of random natural numbers s3-s4 and the count value is greater than Q. If it is greater, it will be regenerated. If it is less, it will be used, that is, the above logic will be executed. R1 is the count value of the counter of container i, and the value is 0-7. The count value is increased by 1 after each encryption. If encryption is performed once when the count value is 7, it will flip to 0.

[0072] Optionally, container i is further configured to synchronously provide random natural numbers s1, s2, s3 and s4 to the electronic device while providing the electronic device with the ciphertext information of the cost of the i-th process node, and the count value of the counter of the electronic device is synchronized with the count value of the counter of container i, that is, the electronic device adds 1 to the count value after each decryption, and if a decryption is performed when the count value is 7, it is flipped to 0. For example, the count values ​​of the counters of container i and the electronic device are initially 0, container i uses the count value initially 0 to perform the above-mentioned first encryption, and then the count value is updated to 1, and accordingly, the electronic device uses the count value initially 0 to perform the above-mentioned first decryption, and then the count value is updated to 1, and so on.

[0073] It can be understood that the advantage of the above encryption and decryption method is that it can ensure security through random natural numbers and calculated values. Even if the random natural numbers are stolen during the transmission process, the information cannot be decrypted because the calculated values ​​of the electronic device or container i cannot be stolen. In addition, the random natural numbers also ensure that the encryption position of the information sent each time is different, further improving security.

[0074] When the electronic device receives the ciphertext information of the cost of the i-th process node, it will perform decryption, which is the reverse process of the above encryption. Since the information used for decryption is synchronized between the electronic device and container i, the decryption can be successful.

[0075] In addition, the encryption and decryption of the communication between the electronic device and the container i+1 is similar, which can be understood by reference and will not be repeated here.

[0076] In summary, in the case of obtaining a business process, the electronic device can configure at least one container for each process node of the process to provide at least one cost optimization strategy. In this way, the electronic device can determine the cost optimization results of the business under different cost optimization strategies based on the different cost optimization strategies provided by the container configured for each process node, thereby ultimately being able to determine the optimal cost optimization result of the business and achieve flexible and efficient cost optimization.

[0077] Combination of the above Figure 1 The method provided by the embodiment of the present application is described in detail. The following introduces the cost optimization strategy of the containerized application for executing the method provided by the embodiment of the present application and its implementation system, the system is applied to an electronic device, and the system is configured as follows: the system obtains the process of the business, the process of the business includes N process nodes, N is an integer greater than 1; for the i-th process node among the N process nodes, i is an integer traversing from 1 to N, the system configures at least one container for the i-th process node, and each container in at least one container is encapsulated with a cost optimization strategy provided for the i-th process node; the system determines the optimal cost optimization strategy for the business according to the containers configured for each of the N process nodes.

[0078] Optionally, the system configures at least one container for the target process node, including: the system determines at least one container suitable for the node type from a container library based on the node type of the target process node; the system configures the at least one container suitable for the node type to the target process node.

[0079] Optionally, the node type of the target process node can represent the cost generation rule of the target process node, and at least one container is applicable to the node type, which means that the cost optimization strategies encapsulated in at least one container are applicable to optimizing the cost of the target process node, and the cost of the target process node is determined based on the cost generation rule of the target process node.

[0080] Optionally, the system determines the optimal cost optimization result of the business through the containers configured for each of the N process nodes, including: the system combines the containers configured for each of the N process nodes to obtain multiple container combinations; the system determines the cost optimization result of the business under each container combination in the multiple container combinations to obtain multiple cost optimization results; the system determines the optimal cost optimization result of the business from the multiple cost optimization results.

[0081] Optionally, for the i-th process node among N process nodes, i is an integer ranging from 1 to N-1, and the i-th process node is configured with M i The cost optimization strategy encapsulated in Mi containers has different cost optimization methods for the i-th process. For the i+1th process node among N process nodes, the i+1th process node is configured with M i+1 Container, M i+1 The cost optimization strategy encapsulated in the i+1th process has different cost optimization methods for the i+1th process; the system combines the containers configured for each of the N process nodes to obtain multiple container combinations, including: the system combines the M configured for the i-th process node i The container and the i+1th process node are configured with M i+1 container combinations, when i traverses from 1 to N-1, K container combinations are obtained, K is an integer greater than 1, and each of the K container combinations includes a container configured for each of the N process nodes.

[0082] Optionally, for a target container combination in the K container combinations, the target container combination is any one of the K container combinations; the system determines a cost optimization result of the business under each of the multiple container combinations, and obtains multiple cost optimization results, including: the system inputs the available resources of the i-th process node into a container i configured for the i-th process node in the target container combination, and obtains the cost of the i-th process node output by the container i; container i is M ia container in the target container combination; if i=1, the available resources of the i-th process node are the resources pre-configured by the business for the 1st process node; the system determines the available resources of the i+1th process node based on the cost of the i-th process node; the system inputs the available resources of the i+1th process node into a container i+1 configured for the i+1th process node in the target container combination, and obtains the cost of the i+1th process node output by container i+1; container i+1 is M i+1 a container among containers; when i traverses 1 to N-1, the system obtains the cost of each of the N process nodes, and sums up the costs of each of the N process nodes to obtain a cost of the business for the target container combination. For K container combinations, the system obtains K costs of the business in total; the system determines the optimal cost optimization result of the business from multiple cost optimization results, including: the system determines the lowest cost from the K costs of the business, and the lowest cost is the optimal cost optimization result of the business.

[0083] Optionally, the cost of the i-th process node is the ciphertext information i encrypted and output by container i, and the system is configured to first decrypt the ciphertext information i to obtain plaintext; the cost of the i+1-th process node is the ciphertext information i+1 encrypted and output by container i+1, and the system is configured to first decrypt the ciphertext information i+1 to obtain plaintext.

[0084] Optionally, the plaintext information of the cost of the i-th process node is P bits, P is an integer greater than 3, and the container i is configured to: use a preset key to encrypt the PmodR1-th bit to the PmodR2-th bit of the P bits to obtain a first segment of ciphertext information, wherein there are Q bits remaining after the PmodR2-th bit of the P bits, Q is an integer greater than 1, and the container i is further configured to: use a preset key to encrypt the QmodR3-th bit to the QmodR4-th bit of the Q bits to obtain a second segment of ciphertext information; the container i is further configured to: encrypt the 1-th bit to the PmodR1-1-th bit of the P bits The first section of ciphertext information, the 1st bit to the QmodR3-1th bit of the Q bits, the second section of ciphertext information, and the QmodR4+1th bit to the Qth bit of the Q bits are sequentially spliced ​​to obtain the ciphertext information of the cost of the i-th process node; wherein mod represents a modulus operation, R1 is the sum of the count value of the counter of container i and the random natural number s1 randomly generated by container i, R2 is the sum of the count value and the random natural number s2 randomly generated by container i, R3 is the sum of the count value and the random natural number s3 randomly generated by container i, and R4 is the sum of the count value and the random natural number s4 randomly generated by container i.

[0085] Optionally, container i is also configured to synchronously provide random natural number s1, random natural number s2, random natural number s3 and random natural number s4 to the system while providing the system with ciphertext information of the cost of the i-th process node, and the count value of the counter of container i+1 is synchronized with the count value of the counter of container i.

[0086] Combine the following Figure 2 The components of the electronic device 500 are described in detail:

[0087] The processor 501 is the control center of the electronic device 500, and may be a processor or a general term for multiple processing elements. For example, the processor 501 is one or more central processing units (CPUs), or may be application specific integrated circuits (ASICs), or may be configured to implement one or more integrated circuits of the embodiments of the present application, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (FPGAs).

[0088] Optionally, the processor 501 can execute various functions of the electronic device 500 by running or executing the software program stored in the memory 502 and calling the data stored in the memory 502, as described above. Figure 1 Functionality in the method shown.

[0089] In a specific implementation, as an embodiment, the processor 501 may include one or more CPUs, such as Figure 2 CPU0 and CPU1 are shown in FIG.

[0090] In a specific implementation, as an embodiment, the electronic device 500 may also include multiple processors. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0091] Among them, the memory 502 is used to store the software program for executing the solution of the present application, and the execution is controlled by the processor 501. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0092] Optionally, the memory 502 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 502 may be integrated with the processor 501, or may exist independently, and the interface circuit ( Figure 2 (not shown) is coupled to the processor 501, which is not specifically limited in the embodiment of the present application.

[0093] The transceiver 503 is used for communication with other systems. For example, if the multi-beam based positioning system is a terminal, the transceiver 503 can be used for communication with a network device or with another terminal.

[0094] Optionally, the transceiver 503 may include a receiver and a transmitter ( Figure 2 The receiver is used to implement a receiving function, and the transmitter is used to implement a sending function.

[0095] Optionally, the transceiver 503 may be integrated with the processor 501, or may exist independently and communicate with the electronic device 500 through an interface circuit ( Figure 2 (not shown) is coupled to the processor 501, which is not specifically limited in the embodiment of the present application.

[0096] It should be noted that Figure 2 The structure of the electronic device 500 shown in the figure does not constitute a limitation on the system. The actual electronic device 500 may include more or fewer components than those shown in the figure, or combine certain components, or arrange the components differently.

[0097] In addition, the technical effects based on the electronic device 500 can refer to the technical effects of the method in the above method embodiment, which will not be repeated here.

[0098] It should be understood that the processor in the embodiment of the present application may be a central processing unit (CPU), and 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, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0099] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0100] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable system. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0101] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0102] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0103] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0104] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are 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 this application.

[0105] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0106] In the several embodiments provided in the present application, it should be understood that the disclosed systems, systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some feature fields can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the system or unit can be electrical, mechanical or other forms.

[0107] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0109] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0110] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for enterprise cost optimization based on big data, characterized in that: Applied to electronic equipment, the method comprises: The electronic device acquires a service process, wherein the service process includes N process nodes, where N is an integer greater than 1; For a target process node among the N process nodes, the electronic device configures at least one container for the target process node, each of the at least one container is encapsulated with a cost optimization strategy provided for the target process node, and the target process node is any one of the N process nodes; The electronic device determines the optimal cost optimization result of the business through the containers configured for each of the N process nodes.

2. The method according to claim 1, characterized in that The electronic device configures at least one container for the target process node, including: The electronic device determines, according to the node type of the target process node, at least one container applicable to the node type from a container library; The electronic device configures at least one container suitable for the node type to the target process node.

3. The method according to claim 2, characterized in that The node type of the target process node can represent the cost generation rule of the target process node, and the at least one container is applicable to the node type, which means that the cost optimization strategies encapsulated in each of the at least one container are applicable to optimizing the cost of the target process node, and the cost of the target process node is determined based on the cost generation rule of the target process node.

4. The method according to claim 1, characterized in that: The electronic device determines the optimal cost optimization result of the business through the containers configured in each of the N process nodes, including: The electronic device combines the containers configured for the N process nodes to obtain multiple container combinations; The electronic device determines a cost optimization result of the service under each container combination in the multiple container combinations to obtain multiple cost optimization results; The electronic device determines the optimal cost optimization result for the service from the multiple cost optimization results.

5. The method according to claim 4, characterized in that For the i-th process node among the N process nodes, i is an integer ranging from 1 to N-1, and the i-th process node is configured with M i containers, the cost optimization strategies encapsulated in the Mi containers have different cost optimization methods for the i-th process, and for the i+1-th process node among the N process nodes, the i+1-th process node is configured with M i+1 containers, the M i+1 The cost optimization strategy for packaging the containers has different cost optimization methods for the i+1th process; The electronic device combines the containers configured for the N process nodes to obtain multiple container combinations, including: The electronic device configures the M i The M containers and the i+1th process node are configured i+1 container combinations, when i traverses from 1 to N-1, K container combinations are obtained, K is an integer greater than 1, and each of the K container combinations includes a container configured for each of the N process nodes.

6. The method according to claim 5, characterized in that For a target container combination in the K container combinations, the target container combination is any one of the K container combinations; the electronic device determines a cost optimization result of the service under each container combination in the multiple container combinations, and obtains multiple cost optimization results, including: The electronic device inputs the available resources of the i-th process node into a container i configured for the i-th process node in the target container combination, and obtains the cost of the i-th process node output by the container i; the container i is M i a container among containers; if i=1, the available resources of the i-th process node are the resources pre-configured by the business for the first process node; The electronic device determines the available resources of the (i+1)th process node according to the cost of the (i)th process node; The electronic device inputs the available resources of the i+1th process node into a container i+1 configured for the i+1th process node in the target container combination, and obtains the cost of the i+1th process node output by the container i+1; the container i+1 is M i+1 A container in a container; When i traverses from 1 to N-1, the electronic device obtains the cost of each of the N process nodes, and sums the costs of each of the N process nodes to obtain a cost of the service for the target container combination. For the K container combinations, the electronic device obtains a total of K costs of the service. The electronic device determines the optimal cost optimization result of the service from the multiple cost optimization results, including: The electronic device determines the lowest cost from the K costs of the service, and the lowest cost is the optimal cost optimization result of the service.

7. The method according to claim 6, characterized in that The cost of the i-th process node is the ciphertext information i encrypted and output by the container i, and the electronic device is configured to first decrypt the ciphertext information i to obtain plaintext; The cost of the i+1th process node is the ciphertext information i+1 encrypted and output by the container i+1, and the electronic device is configured to first decrypt the ciphertext information i+1 to obtain plaintext.

8. The method according to claim 7, characterized in that The plaintext information of the cost of the i-th process node is P bits, where P is an integer greater than 3. The container i is configured to: use a preset key to encrypt the PmodR1th bit to the PmodR2th bit of the P bits to obtain a first segment of ciphertext information, wherein Q bits remain after the PmodR2th bit of the P bits, and Q is an integer greater than 1. The container i is also configured to: use the preset key to encrypt the QmodR3th bit to the QmodR4th bit of the Q bits to obtain a second segment of ciphertext information; the container i is also configured to: sequentially concatenate the 1st to the PmodR1-1th bits of the P bits, the first segment of ciphertext information, the 1st to the QmodR3-1th bits of the Q bits, the second segment of ciphertext information, and the QmodR4+1th bit to the Qth bit of the Q bits to obtain the ciphertext information of the cost of the i-th process node; Among them, mod represents a modulus operation, R1 is the sum of the count value of the counter of the container i and the random natural number s1 randomly generated by the container i, R2 is the sum of the count value and the random natural number s2 randomly generated by the container i, R3 is the sum of the count value and the random natural number s3 randomly generated by the container i, and R4 is the sum of the count value and the random natural number s4 randomly generated by the container i.

9. The method according to claim 8, characterized in that The container i is also configured to synchronously provide the random natural number s1, the random natural number s2, the random natural number s3 and the random natural number s4 to the electronic device while providing the ciphertext information of the cost of the i-th process node to the electronic device, and the count value of the counter of the container i+1 is synchronized with the count value of the counter of the container i.

10. A cost optimization strategy for containerized applications and its implementation system, characterized in that: The system is applied to electronic equipment, and the system is configured as follows: The system acquires a business process, where the business process includes N process nodes, where N is an integer greater than 1; For an i-th process node among the N process nodes, i is an integer ranging from 1 to N, the system configures at least one container for the i-th process node, and each container in the at least one container is encapsulated with a cost optimization strategy provided for the i-th process node; The system determines an optimal cost optimization strategy for the business according to the containers configured for each of the N process nodes.

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