Privacy calculation method and device based on load balancing, equipment and storage medium

Abstract

The invention discloses a privacy computing method, device and equipment based on load balancing and a storage medium, which are applied to the technical field of privacy computing, and comprise the following steps: when a request end privacy computing node receives a user privacy computing request, determining a first target service instance from the request end privacy computing node through a load balancer, determining a second target service instance through the load balancer according to the assistance end service instance list; and sending the privacy calculation request to a second target service instance of the privacy calculation node of the assistance end through the first target service instance, so as to carry out privacy interaction calculation through the second target service instance and the first target service instance. The appropriate target service instance is selected from the computing node and the assisting end in a load balancing mode to conduct privacy computing, overload of the computing amount is avoided, due to the fact that each request task of each computing node is processed through a single service instance, the computing tasks on the other service instances cannot be affected when a fault occurs, and the computing efficiency is improved. And the reliability of system privacy calculation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of privacy computing, and in particular, to a privacy method, device, equipment and storage medium based on load balancing. Background Art

[0002] At present, with the development of privacy computing technology and the gradual maturity of relevant laws and regulations systems, a large number of privacy computing platforms have emerged globally. Although there are many landing scenarios for privacy computing platforms and the application value is continuously increasing, the high availability of privacy computing platforms has brought challenges to the large-scale application of privacy computing.

[0003] Currently, when performing privacy computing, a monolithic architecture system / platform is usually adopted, and multiple tasks are run on the same monolith. This not only easily causes computational overload, but also affects the remaining tasks that are running when a task component has a problem. Moreover, the tasks that are running need to be interrupted during the fault recovery period, thus reducing the reliability of the privacy computing system / platform. Summary of the Invention

[0004] The present invention provides a privacy computing method and device based on load balancing to improve the reliability of the privacy computing system.

[0005] According to a first aspect of the present invention, there is provided a privacy computing method based on load balancing, including: a request-side privacy computing node receives a registration request from an assist-side privacy computing node, and generates an assist-side service instance list according to the registration request, wherein the assist-side service instance list includes service instances carried on the assist-side privacy computing node;

[0006] When the request-side privacy computing node receives a user privacy computing request, it determines a first target service instance from itself through a load balancer, and determines a second target service instance according to the assist-side service instance list through the load balancer, wherein multiple service instances are respectively carried on the request-side privacy computing node and the assist-side privacy computing node;

[0007] The privacy computing request is sent to the second target service instance of the assist-side privacy computing node through the first target service instance, so as to perform privacy interaction computing between the second target service instance and the first target service instance.

[0008] According to another aspect of the present invention, there is provided a privacy computing device based on load balancing, including:

[0009] The assisting - end service instance list generation module is used to request the requesting - end privacy - computing node to receive the registration request of the assisting - end privacy - computing node and generate an assisting - end service instance list according to the registration request, where the assisting - end service instance list includes the service instances hosted on the assisting - end privacy - computing node;

[0010] The target service instance determination module is used to, when the requesting - end privacy - computing node receives a user privacy - computing request, determine a first target service instance from itself through a load balancer and determine a second target service instance according to the assisting - end service instance list through the load balancer, where multiple service instances are respectively hosted on the requesting - end privacy - computing node and the assisting - end privacy - computing node;

[0011] The privacy - computing module is used to send the privacy - computing request to the second target service instance of the assisting - end privacy - computing node through the first target service instance, so as to perform privacy - exchange computing between the second target service instance and the first target service instance.

[0012] According to another aspect of the present invention, there is provided an electronic device, which includes:

[0013] At least one processor; and

[0014] A memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor can execute the method according to any embodiment of the present invention.

[0016] According to another aspect of the present invention, there is provided a computer - readable storage medium storing computer instructions for causing a processor to implement the method according to any embodiment of the present invention when executed.

[0017] According to another aspect of the present invention, there is provided a computer program product including a computer program, and when the computer program is executed by a processor, it implements the method according to any embodiment of the present invention.

[0018] The beneficial technical effects of the present invention are as follows. By deploying multiple service instances on each computing node and understanding the service instance situation of other nodes through service registration, when performing privacy computing, the target service instance with appropriate computing resources is selected from itself and the assisting end through load balancing for privacy interaction computing, thereby avoiding the problem of overloaded computing volume. And since each request task of each computing node is processed by a single service instance, even when a failure occurs, it will not affect the computing tasks on the remaining service instances, thus improving the reliability of the system's privacy computing.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 It is a flowchart of a privacy computing method based on load balancing according to Embodiment 1 of the present invention;

[0022] Figure 2 It is a schematic structural diagram of a privacy computing node according to Embodiment 1 of the present invention;

[0023] Figure 3 It is a flowchart of a privacy computing method based on load balancing according to Embodiment 2 of the present invention;

[0024] Figure 4 It is a schematic structural diagram of a privacy computing device based on load balancing according to Embodiment 3 of the present invention;

[0025] Figure 5 It is a schematic structural diagram of an electronic device according to Embodiment 4 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0028] It should be noted that the relevant information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in the present disclosure are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data comply with the relevant laws, regulations and standards of the relevant regions.

[0029] Embodiment 1

[0030] Figure 1 The flow chart of a privacy computing method based on load balancing is provided for Embodiment 1 of the present invention. This embodiment is applicable to the situation of privacy computing. This method can be executed by a privacy computing device based on load balancing, and this device can be implemented in the form of hardware and / or software. As Figure 1 shown, this method includes:

[0031] Step S101, the requesting end privacy computing node receives the registration request of the assisting end privacy computing node, and generates a list of assisting end service instances according to the registration request.

[0032] Optionally, the requesting end privacy computing node receives the registration request of the assisting end privacy computing node, and generates a list of assisting end service instances according to the registration request, including: the requesting end privacy computing node receives the registration request of the assisting end privacy computing node, where the registration request includes parameter information of each service instance on the assisting end privacy computing node; generating a list of assisting end service instances according to the parameter information, where the parameter information includes IP address, port number, running information and service name.

[0033] Optionally, the method further includes: sending a registration request to the assisting end privacy computing node, so that the assisting end privacy computing node generates a list of requesting end service instances according to the registration request, where the list of requesting end service instances includes the service instances carried on the requesting end privacy computing node.

[0034] Among them, as Figure 2 shown in the structural schematic diagram of the privacy computing node, during privacy computing, it is specifically achieved through the ciphertext interaction between the privacy computing node A and the privacy computing node B. Both the privacy computing node A and the privacy computing node B can serve as the requesting-end privacy computing nodes. When the privacy computing node A serves as the requesting-end privacy computing node, the corresponding privacy computing node B serves as the assisting-end privacy computing node; when the privacy computing node B serves as the requesting-end privacy computing node, the corresponding privacy computing node A serves as the assisting-end privacy computing node. In this embodiment, only the privacy computing node A is taken as the requesting-end privacy computing node and the privacy computing node B is taken as the assisting-end privacy computing node for illustration. Each privacy node includes multiple service instances respectively. Each pair of service instances processes a privacy computing task, and in each pair of service instances for processing a privacy computing task, it includes one service instance in the privacy computing node A and one service instance in the privacy computing node B. In this embodiment, it is illustrated by taking that the privacy computing node A includes service instances A1, A2, and A3, and the privacy computing node B includes service instances B1, B2, and B3, without limiting the specific number of service instances included in each privacy computing node. Additionally, a load balancer is integrated in each privacy computing node respectively. The load balancer selects the service instances of the privacy cooperation party according to a preset algorithm. And the load balancer in this embodiment specifically refers to a client load balancer, which can distribute the load, such as work tasks or access requests, at the client side to determine which service instance of the opposite cooperation party will process the request, that is, select the service instance to be accessed through a certain load balancing algorithm before sending the request.

[0035] Specifically, since multiple service instances are respectively included on the privacy computing node A and the privacy computing node B, and the multiple service instances can all independently perform privacy computing tasks. Before the task runs, multiple instances of the privacy computing node will register their own information with the other node. For example, the privacy computing node A will receive the registration request from the privacy computing node B, and the registration request includes the parameter information of each service instance on the assisting-end privacy computing node, such as IP address, port number, running information, and service name, etc. And the running information specifically includes the running status and remaining space of the service instance. Of course, this is only an example in this embodiment, without limiting the specific content of the parameter information. The privacy computing node A will generate a list of assisting-end service instances according to the parameter information in the received registration request. The following Table 1 shows an example of the list of assisting-end service instances corresponding to the privacy computing node B as the assisting end:

[0036] Table 1

[0037] Service Name IP Address Port Number Running Information B1 110.220.40.11 01 Idle, 30G of free space remaining B2 110.220.40.12 02 Running, 10G of free space remaining B3 110.220.40.13 03 Idle, 10G of free space remaining

[0038] Similarly, the privacy computing node A will also send a registration request to the privacy computing node B, so that the privacy computing node B generates a list of requester-side service instances according to the received registration request. The following table 2 shows an example of the list of requester-side service instances corresponding to the privacy computing node A as the requester:

[0039] Table 2

[0040]

[0041]

[0042] Optionally, after generating the list of assistant-side service instances according to the registration request, it further includes: the requester-side privacy computing node periodically sends heartbeat detection requests to each service instance in the list of assistant-side service instances; and updates the list of assistant-side service instances according to the heartbeat detection responses of each service instance in the assistant-side privacy computing node.

[0043] Specifically, in this embodiment, after the privacy computing node A generates the list of assistant-side service instances according to the registration request, it will also periodically send heartbeat detection requests to the service instance B1, service instance B2, and service instance B3 in the list of assistant-side service instances. If there is no response or abnormal response from the service instances in the privacy computing node B, it is determined that the service instance has failed, and the failed service instance is removed from the list of assistant-side service instances to update the list of assistant-side service instances shown in Table 1. For example, when sending heartbeat detection requests to the service instance B1, service instance B2, and service instance B3, only the service instance B1 and service instance B2 feedback the heartbeat detection responses, so it can be determined that the service instance B3 has failed, and the service instance B3 is deleted from Table 1. Of course, only the update method of the list of assistant-side service instances is taken as an example for illustration in this embodiment. The update method of the list of requester-side service instances is roughly the same, and will not be elaborated in this embodiment. By updating the list of assistant-side service instances or the list of requester-side service instances, each privacy computing node can accurately learn the latest true situation of each service instance in the cooperation party.

[0044] Step S102, when the requester-side privacy computing node receives a user privacy computing request, determine the first target service instance from itself through the load balancer, and determine the second target service instance through the load balancer according to the list of assistant-side service instances.

[0045] Optionally, when the requesting - end privacy - computing node receives a user privacy - computing request, it determines the first target service instance from itself through a load balancer, including: when the requesting - end privacy - computing node receives a user privacy - computing request, it collects the running information of each service instance of itself through the load balancer, where the running information includes the running status and the remaining space; the service balancer takes the service instance with an idle running status and the largest remaining space as the first target service instance on the side of the requesting - end privacy - computing node.

[0046] Optionally, the load balancer determines the second target service instance according to the assisting - end service instance list, including: the load balancer obtains the running information of each service instance in the assisting - end service instance list; the load balancer takes the service instance with an idle running status and the largest remaining space as the second target service instance on the side of the assisting - end privacy - computing node according to the running information.

[0047] Specifically, since a load balancer is integrated on each privacy - computing node, the load balancer can be used to achieve the balance of computing tasks. For example, when privacy - computing node A receives a user privacy - computing request, since the running information of each service instance within its own node is known. For example, the running information of service instance A1 is: running status idle, remaining space 28G; the running information of service instance A2 is: running status idle, remaining space 10G; the running information of service instance A3 is: running status running, remaining space 10G. Therefore, the service instance A1 with an idle running status and the largest remaining space can be directly selected as the first target service instance on the side of privacy - computing node A1.

[0048] Among them, before the service instance A1 sends the user's privacy computing request to the privacy computing node B, it needs to select a service instance from the privacy computing nodes B through the load balancer to cooperate to complete the current privacy computing task. The selection is specifically determined according to the previously generated list of assisting-end service instances. Although the load balancer on the privacy computing node A side cannot actively collect data from the service instances on the privacy computing node B side, since the privacy computing node B has actively sent a registration request to the privacy computing node A during the registration phase, the privacy computing node A has generated a list of assisting-end service instances based on the registration request. The list of assisting-end service instances details the running information of each service instance in the privacy computing node B. For example, the running information of the service instance B1 is: running status is idle, remaining space is 30G; the running information of the service instance B2 is: running status is running, remaining space is 10G; the running information of the service instance B3 is: running status is idle, remaining space is 10G. Therefore, the service instance B1 with an idle running status and the largest remaining space can be selected as the second target service instance on the privacy computing node B side. Therefore, in this embodiment, the load balancer can determine the first target service instance A1 with the least load pressure in the requesting-end privacy computing node and the second target service instance B1 with the least load pressure in the assisting-end privacy computing node.

[0049] It should be noted that in this embodiment, when the requesting-end privacy computing node determines its first target service instance and the second target service instance of the assisting-end computing node, it always selects the service instance with an idle running status and the largest remaining space from multiple service instances according to the running information of each instance as the target service instance for the current privacy computing, thus avoiding the problem of overloading the computing volume caused by a large number of computing tasks being concentrated in one service instance.

[0050] It is worth mentioning that in this embodiment, the load balancer can also select the target service instance by using a preset algorithm, such as round-robin, random, or least connection number, etc., and filter out the target service instance that meets the specified requirements. Of course, in this embodiment, only examples are given, and the specific method for the load balancer to select the target service instance is not limited. As long as it can eliminate the processing pressure of each service instance in the privacy computer node, it is within the protection scope of this application.

[0051] Step S103: Send the privacy computing request to the second target service instance of the assisting-end privacy computing node through the first target service instance, so as to perform privacy interaction computing through the second target service instance and the first target service instance.

[0052] Specifically, in this embodiment, the privacy computing node A will send the currently received privacy computing request to the second target service instance B1 of the assisting privacy computing node B through the first target service instance A1. After receiving the request, the selected second target service instance B1 in the privacy computing node B will perform corresponding processing and generate a response to feedback to the first target service instance A1 to inform that it is now ready to start privacy computing. At this time, the first target service instance A1 will start the ciphertext interaction for privacy computing with the second target service instance B1. And even if there are failures in tasks on other service instances, it will not affect the execution of this privacy computing task. For example, when the ciphertext interaction for privacy computing between the first target service instance A1 and the second target service instance B1 is in progress, the service instance A3 on the privacy computing node A and the service instance B2 on the privacy computing node B are executing the privacy computing task X. When the service instance A3 and the service instance B2 are interrupted due to component failures during the privacy computing task X, since each service instance in the privacy computing node runs independently, it will not affect the privacy computing process between the first target service instance A1 and the second target service instance B1, avoiding the situation that a problem in one group affects other running tasks in the privacy computing node, thus ensuring the reliability of the system's privacy computing.

[0053] It should be noted that in this embodiment, during the process of privacy computing between the first target service instance A1 and the second target service instance B1, if the second target service instance B1 fails, for example, crashes or has a network interruption, the privacy computing node will re-execute the service discovery and load balancing process to select another new available second target service instance, such as the service instance B3, to continue the ciphertext interaction with the first target service instance A1 to execute the privacy computing task, thereby achieving the normal execution of the privacy computing task through failover. Of course, in this embodiment, only the privacy computing node A is taken as the requesting privacy computing node, and the privacy computing node B is taken as the assisting privacy computing node for illustration. For the privacy computing process where the privacy computing node B is the requesting privacy computing node and the privacy computing node A is the assisting privacy computing node, it is roughly the same as the above method, and will not be elaborated in this embodiment.

[0054] In the embodiment of the present application, by deploying multiple service instances on each computing node and understanding the service instance situation of the other node through the form of service registration, when performing privacy computing, the target service instance with appropriate computing resources is selected from itself and the assisting end through the load balancing method for privacy interaction computing, thus avoiding the problem of overloaded computing volume. And since each request task of each computing node is processed by a single service instance respectively, even when a failure occurs, it will not affect the computing tasks on the remaining service instances, thereby improving the reliability of the system's privacy computing.

[0055] Example Two

[0056] Figure 3 The figure is a flowchart of a privacy computing method based on load balancing provided in Example Two of the present invention. Based on the above embodiment, after the privacy computing request is sent to the second target service instance assisting the privacy computing node through the first target service instance, the method further includes: receiving a privacy computing result viewing request from the user; performing user identity authentication according to the privacy computing result viewing request, and visually displaying the privacy computing result when the authentication is passed. As Figure 3 shown, the method includes:

[0057] Step S201, the privacy computing node at the request end receives the registration request from the privacy computing node at the assisting end, and generates a list of assisting end service instances according to the registration request.

[0058] Optionally, the privacy computing node at the request end receives the registration request from the privacy computing node at the assisting end, and generates a list of assisting end service instances according to the registration request, including: the privacy computing node at the request end receives the registration request from the privacy computing node at the assisting end, where the registration request includes parameter information of each service instance on the privacy computing node at the assisting end; generating a list of assisting end service instances according to the parameter information, where the parameter information includes IP address, port number, running information, and service name.

[0059] Optionally, the method further includes: sending a registration request to the privacy computing node at the assisting end, so that the privacy computing node at the assisting end generates a list of service instances at the request end according to the registration request, where the list of service instances at the request end includes the service instances carried on the privacy computing node at the request end.

[0060] Optionally, after generating the list of assisting end service instances according to the registration request, the method further includes: the privacy computing node at the request end periodically sends heartbeat detection requests to each service instance in the list of assisting end service instances; updating the list of assisting end service instances according to the heartbeat detection responses of each service instance in the privacy computing node at the assisting end.

[0061] Step S202, when the privacy computing node at the request end receives a user privacy computing request, it determines a first target service instance from itself through the load balancer, and determines a second target service instance through the load balancer according to the list of assisting end service instances.

[0062] Optionally, when the requesting - end privacy - computing node receives a user privacy - computing request, it determines a first target service instance from itself through a load balancer, including: when the requesting - end privacy - computing node receives a user privacy - computing request, the load balancer collects the running information of each service instance of itself, where the running information includes the running status and the remaining space; the service balancer takes the service instance with an idle running status and the largest remaining space as the first target service instance on the side of the requesting - end privacy - computing node.

[0063] Optionally, the load balancer determines a second target service instance according to the assisting - end service instance list, including: the load balancer obtains the running information of each service instance in the assisting - end service instance list; the load balancer takes the service instance with an idle running status and the largest remaining space as the second target service instance on the side of the assisting - end privacy - computing node according to the running information.

[0064] Step S203: Send the privacy - computing request to the second target service instance of the assisting - end privacy - computing node through the first target service instance, so as to perform privacy interaction computing between the second target service instance and the first target service instance.

[0065] Step S204: Receive the user's privacy - computing result viewing request; perform user identity authentication according to the privacy - computing result viewing request, and visualize the privacy - computing result when the authentication is passed.

[0066] Specifically, in this embodiment, after the first target service instance A1 and the second target service instance A2 complete the privacy computing, when receiving the user's privacy - computing result viewing request, to ensure data security, the user login account in the privacy - computing result viewing request will be extracted, and the user will be authenticated according to the user login account. Only when the identity authentication is passed will the privacy - computing result be displayed on the front - end visualization interface.

[0067] Among them, when it is determined through authentication that the user is an unregistered illegal user, an alarm prompt message will be generated. For example, "Illegal user, please pay attention to data security". And when the number of viewing request sent by the same illegal user exceeds a preset threshold, the login account of this user will be directly locked, that is, this user is prohibited from logging in to the system, and the login account of this user will be reported so that the management personnel can pay key attention to this user. If it is determined through the identity verification of the management personnel that this user is a new employee, the login account of this user can be added to the list of legal users to lift the login restriction on this user; if it is determined through the identity verification of the management personnel that this user is not an internal employee of the enterprise, it means that the probability that this user is a virus attack user is very high. Therefore, the login account of this user is directly pulled into the blacklist and this user is permanently prohibited from logging in to the system, thereby further ensuring the security of privacy computing. Of course, only examples are given in this embodiment, and the specific process of user identity authentication is not limited. As long as it can identify whether the user is an illegal user or a legal user and interrupt the access in time, it is within the protection scope of this application, and it is not limited in this embodiment.

[0068] In the embodiment of the present application, multiple service instances are deployed on each computing node, and the service instance situation of the other nodes is understood through the form of service registration. When performing privacy computing, the target service instance with appropriate computing resources is selected from itself and the assisting end through the method of load balancing for privacy interaction computing, thereby avoiding the problem of overloaded computing volume. And since each request task of each computing node is processed by a single service instance respectively, even when a failure occurs, it will not affect the computing tasks on the remaining service instances, thereby improving the reliability of the system's privacy computing.

[0069] Embodiment III

[0070] Figure 4 It is a schematic structural diagram of a privacy computing device based on load balancing provided by Embodiment III of the present invention. As Figure 4 shown, the device includes: an assisting end service instance list generation module 310, a target service instance determination module 320, and a privacy computing module 330.

[0071] Among them, the assisting end service instance list generation module 310 is used for the privacy computing node at the request end to receive the registration request from the privacy computing node at the assisting end, and generate an assisting end service instance list according to the registration request. Among them, the assisting end service instance list includes the service instances carried on the privacy computing node at the assisting end;

[0072] The target service instance determination module 320 is configured to, when the requesting - end privacy - computing node receives a user privacy - computing request, determine a first target service instance from itself through a load balancer and determine a second target service instance according to the assisting - end service instance list through the load balancer, where multiple service instances are respectively carried on the requesting - end privacy - computing node and the assisting - end privacy - computing node;

[0073] The privacy - computing module 330 is configured to send the privacy - computing request to the second target service instance of the assisting - end privacy - computing node through the first target service instance, so as to perform privacy - exchange computing between the second target service instance and the first target service instance.

[0074] Optionally, the assisting - end service instance list generation module is configured to receive a registration request from the assisting - end privacy - computing node by the requesting - end privacy - computing node, where the registration request includes parameter information of each service instance on the assisting - end privacy - computing node;

[0075] Generate an assisting - end service instance list according to the parameter information, where the parameter information includes an IP address, a port number, running information, and a service name.

[0076] Optionally, the device further includes a registration request sending module configured to send a registration request to the assisting - end privacy - computing node, so that the assisting - end privacy - computing node generates a requesting - end service instance list according to the registration request,

[0077] where the requesting - end service instance list includes the service instances carried on the requesting - end privacy - computing node.

[0078] Optionally, the device further includes an assisting - end service instance list update module configured to send heartbeat detection requests to each service instance in the assisting - end service instance list at regular intervals by the requesting - end privacy - computing node;

[0079] Update the assisting - end service instance list according to the heartbeat detection responses of each service instance in the assisting - end privacy - computing node.

[0080] Optionally, the target service instance determination module is configured to collect the running information of each service instance on itself through a load balancer when the requesting - end privacy - computing node receives a user privacy - computing request, where the running information includes a running state and remaining space;

[0081] Use the service instance with an idle running state and the largest remaining space as the first target service instance on the side of the requesting - end privacy - computing node through the service balancer.

[0082] Optionally, the target service instance determination module is further configured to obtain the running information of each service instance in the assisting - end service instance list through the load balancer;

[0083] The load balancer selects the service instance with an idle running status and the largest remaining space as the second target service instance on the side of the assisted end privacy computing node according to the running information.

[0084] Optionally, the device further includes a privacy computing result display module, configured to receive a user's privacy computing result viewing request;

[0085] Authenticate the user's identity according to the privacy computing result viewing request, and visually display the privacy computing result when the authentication is passed.

[0086] The privacy computing device based on load balancing provided by the embodiments of the present invention can execute the privacy computing method based on load balancing provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0087] Embodiment Four

[0088] Figure 5 FIG. shows a schematic structural diagram of an electronic device 10 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0089] As Figure 5 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0090] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0091] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the privacy computing method based on load balancing.

[0092] In some embodiments, the privacy computing method applied to load balancing can be implemented as a computer program, which is tangibly included in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the privacy computing method based on load balancing described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the privacy computing method based on load balancing in any other suitable way (e.g., by means of firmware).

[0093] The various embodiments of the systems and technologies described above in this article can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs, which can be executed and / or interpreted on a programmable system including at least one programmable processor, and the programmable processor can be a special or general programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0094] A computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, a special purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0095] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0096] In order to provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and the input received from the user can be in any form (including acoustic input, voice input, or tactile input).

[0097] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected with each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0098] A computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0099] Example Five

[0100] The embodiment of the present invention also provides a computer program product, including a computer program which, when executed by a processor, implements the privacy computing method based on load balancing provided in any embodiment of the present application.

[0101] In the process of implementing the computer program product, computer program code for performing the operations of the present invention can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user computer, partially on the user computer, executed as an independent software package, partially on the user computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user computer through any type of network - including a local area network (LAN) or a wide area network (WAN) - or can be connected to an external computer (e.g., by connecting through an Internet service provider via the Internet).

[0102] It should be noted that in the embodiments of the present application, some existing industry solutions such as certain software, components, models, etc. may be mentioned. They should be regarded as exemplary, and their purpose is only to illustrate the feasibility in the implementation of the technical solutions of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0103] Note that the above is only a preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will understand that the present invention is not limited to the specific embodiments here, and various obvious changes, re-adjustments, and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments only. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A privacy computing method based on load balancing, characterized in that, Including: The requesting - end privacy - computing node receives a registration request from the assisting - end privacy - computing node and generates a list of assisting - end service instances according to the registration request. Among them, the list of assisting - end service instances includes service instances hosted on the assisting - end privacy - computing node; When the requesting - end privacy - computing node receives a user privacy - computing request, it determines a first target service instance from itself through a load balancer, and determines a second target service instance according to the list of assisting - end service instances through the load balancer. Among them, multiple service instances are respectively hosted on the requesting - end privacy - computing node and the assisting - end privacy - computing node; Send the privacy - computing request to the second target service instance of the assisting - end privacy - computing node through the first target service instance, so as to perform privacy - interactive computing between the second target service instance and the first target service instance.

2. The method according to claim 1, wherein The requesting - end privacy - computing node receives a registration request from the assisting - end privacy - computing node and generates a list of assisting - end service instances, including: The requesting - end privacy - computing node receives the registration request from the assisting - end privacy - computing node, where the registration request includes parameter information of each service instance on the assisting - end privacy - computing node; Generate the list of assisting - end service instances according to the parameter information, where the parameter information includes IP address, port number, running information, and service name.

3. The method according to claim 1, wherein The method further includes: Send a registration request to the assisting - end privacy - computing node, so that the assisting - end privacy - computing node generates a list of requesting - end service instances according to the registration request, where the list of requesting - end service instances includes service instances hosted on the requesting - end privacy - computing node.

4. The method according to claim 1, characterized in that After generating the list of assisting - end service instances according to the registration request, it further includes: The requesting - end privacy - computing node periodically sends heartbeat detection requests to each service instance in the list of assisting - end service instances; Update the list of assisting - end service instances according to the heartbeat detection responses of each service instance in the assisting - end privacy - computing node.

5. The method according to claim 1, wherein The step of when the requesting - end privacy - computing node receives a user privacy - computing request and determines a first target service instance from itself through a load balancer includes: When the requesting - end privacy - computing node receives a user privacy - computing request, it collects the running information of each service instance on itself through the load balancer, where the running information includes running status and remaining space; Use the service instance with an idle running status and the largest remaining space as the first target service instance on the side of the requesting - end privacy - computing node through the service balancer.

6. The method according to claim 5, characterized in that, The step of determining a second target service instance according to the list of assisting - end service instances through the load balancer includes: Obtain the running information of each service instance in the list of assisting - end service instances through the load balancer; Use the service instance with an idle running status and the largest remaining space as the second target service instance on the side of the assisting - end privacy - computing node according to the running information through the load balancer.

7. The method according to any one of claims 1 to 6, characterized in that, After sending the privacy computing request to the second target service instance of the assisting - end privacy computing node through the first target service instance, the following steps are further included: Receiving a privacy computing result viewing request from a user; Performing user identity authentication according to the privacy computing result viewing request, and visualizing the privacy computing result when the authentication is passed.

8. A privacy computing device based on load balancing, characterized in that, Including: An assisting - end service instance list generation module, configured to receive a registration request from an assisting - end privacy computing node by a requesting - end privacy computing node, and generate an assisting - end service instance list according to the registration request, where the assisting - end service instance list includes service instances hosted on the assisting - end privacy computing node; A target service instance determination module, configured to determine a first target service instance from itself by a load balancer when the requesting - end privacy computing node receives a user privacy computing request, and determine a second target service instance according to the assisting - end service instance list by the load balancer, where multiple service instances are respectively hosted on the requesting - end privacy computing node and the assisting - end privacy computing node; A privacy computing module, configured to send the privacy computing request to the second target service instance of the assisting - end privacy computing node through the first target service instance, so as to perform privacy - exchange computing between the second target service instance and the first target service instance.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; where The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the method according to any one of claims 1 - 7.

10. A computer-readable storage medium, characterized in that, The computer - readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to execute the method according to any one of claims 1 - 7 when executed.

11. A computer program product, characterized in that, Including a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 - 7 is implemented.

Images