Edge service migration method, device, apparatus and storage medium

Abstract

The present application relates to the technical field of data migration, and discloses an edge service migration method, device, equipment and storage medium, the method comprising: determining a next edge server according to a user's moving track prediction result; determining continuous service data to be migrated based on the busy degree of the next edge server; and transmitting the continuous service data to the next edge server.The present application determines the next edge server according to the user's moving track prediction result, and then transmits the continuous service data to be migrated to the next edge server according to the busy degree of the next edge server, thereby avoiding the situation that when the user's geographic position switches from the coverage service of the current edge server to the coverage range of the next edge server, the switching of the edge computing service node will cause the interruption of the user service, ensuring uninterrupted migration of the service and effectively improving the user experience.

Description

Technical Field

[0001] This invention relates to the field of data migration technology, and in particular to an edge service migration method, apparatus, device, and storage medium. Background Technology

[0002] Mobile edge computing technology is a new model for deploying computing resources. By changing the current single, centralized model of data centers, it pushes computing resources closer to users to meet the demands of high traffic, high load, and high availability in 5G environments.

[0003] However, current edge servers have a limited coverage area. When a user's geographical location changes and the service switches from the coverage area of ​​the current edge server to the coverage area of ​​the next edge server, the user's service will be interrupted due to the switching of edge computing service nodes, thus affecting the user experience. Summary of the Invention

[0004] The main objective of this invention is to provide an edge service migration method, apparatus, device, and storage medium, which aims to solve the technical problem that when a user's geographical location switches from the coverage area of ​​the current edge server to the coverage area of ​​the next edge server, the user's service will be interrupted due to the switching of edge computing service nodes, thereby affecting the user experience.

[0005] To achieve the above objectives, the present invention provides an edge service migration method, which includes the following steps:

[0006] The next edge server is determined based on the user's movement trajectory prediction results;

[0007] The continuity service data to be migrated is determined based on the busy level of the next edge server;

[0008] The continuous service data is transmitted to the next edge server.

[0009] Optionally, the step of determining the continuity service data to be migrated based on the busy level of the next edge server includes:

[0010] Determine whether the current busy level of the next edge server has reached a preset busy level;

[0011] If the preset level is reached, then the target service type supported by the next edge server is obtained;

[0012] Determine the degree of matching between the service type of the user's current required continuous service and the target service type, and obtain the pending data to be processed when providing the user with the current continuous service;

[0013] The continuity service data to be migrated is determined based on the matching degree and the data to be processed.

[0014] Optionally, before the step of determining the continuity service data to be migrated based on the matching degree and the data to be processed, the method further includes:

[0015] Based on the movement trajectory prediction results, determine the target duration required for the user to enter the target coverage area of ​​the next edge server;

[0016] Accordingly, the step of determining the continuity service data to be migrated based on the matching degree and the data to be processed includes:

[0017] When the matching degree is higher than the first preset matching degree, the target duration is divided based on a preset ratio to obtain the target time period for advance processing;

[0018] Extract the first target data of the user within the target time period after the user enters the target coverage area from the data to be processed;

[0019] Perform advance processing on the first target data to obtain first advance data;

[0020] Obtain relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the first advanced data and the relevant data.

[0021] Optionally, the step of determining the continuity service data to be migrated based on the matching degree and the data to be processed further includes:

[0022] When the matching degree is lower than the first preset matching degree but higher than the second preset matching degree, extract the second target data within the target duration after the user enters the target coverage area from the data to be processed;

[0023] The second target data is processed in advance to obtain the second advanced data;

[0024] Obtain relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the second advanced data and the relevant data.

[0025] Optionally, the step of determining the continuity service data to be migrated based on the matching degree and the data to be processed further includes:

[0026] When the matching degree is lower than the second preset matching degree, extract all remaining data that needs to be processed after the user enters the target coverage area from the data to be processed;

[0027] The remaining data is processed to obtain the third advanced data;

[0028] Obtain relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the third advanced data and the relevant data.

[0029] Optionally, after determining whether the busy level of the next edge server at the current moment has reached a preset busy level, the method further includes:

[0030] If the preset level is not reached, relevant data associated with the current continuity service is obtained, and continuity service data to be migrated is determined based on the relevant data.

[0031] Optionally, before the step of determining the next edge server based on the user's movement trajectory prediction result, the method further includes:

[0032] Determine the destination location and arrival time from the user's travel data;

[0033] Calculate the travel time required for the user to reach the target location from the current location using several preset transportation methods, and determine the time range based on the travel time.

[0034] Determine whether the time difference between the current time and the arrival time is within the specified duration.

[0035] If the time is within the specified time range, a target transportation mode corresponding to the time difference is selected from the plurality of preset transportation modes, and the user's travel trajectory is predicted based on the movement trajectory corresponding to the target transportation mode to obtain the movement trajectory prediction result.

[0036] If the user is not within the specified time range, the target location and arrival time are input into a preset trajectory prediction model to predict the user's travel trajectory and obtain the movement trajectory prediction result. The preset trajectory prediction model is obtained by training the user's historical travel data.

[0037] Furthermore, to achieve the above objectives, the present invention also proposes an edge service migration apparatus, the apparatus comprising:

[0038] The service determination module is used to determine the next edge server based on the user's movement trajectory prediction results;

[0039] The service data module is used to determine the continuity service data to be migrated based on the busy level of the next edge server;

[0040] The service migration module is used to transfer the continuous service data to the next edge server.

[0041] Furthermore, to achieve the above objectives, the present invention also proposes an edge service migration device, the device comprising: a memory, a processor, and an edge service migration program stored in the memory and executable on the processor, the edge service migration program being configured to implement the steps of the edge service migration method as described above.

[0042] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing an edge service migration program, which, when executed by a processor, implements the steps of the edge service migration method as described above.

[0043] This invention provides an edge service migration method, apparatus, device, and storage medium. The method determines the next edge server based on user movement trajectory prediction; then determines the continuous service data to be migrated based on the busy level of the next edge server; and finally transmits the continuous service data to the next edge server. Compared to existing technologies where edge servers have a certain coverage area, causing service interruptions when a user's geographical location changes from the coverage area of ​​the current edge server to the coverage area of ​​the next edge server due to the switching of edge computing service nodes, this invention ensures uninterrupted service migration, effectively improving the user experience. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the edge service migration device structure in the hardware operating environment involved in the embodiments of the present invention;

[0045] Figure 2 This is a flowchart illustrating the first embodiment of the edge service migration method of the present invention;

[0046] Figure 3 This is a flowchart illustrating the second embodiment of the edge service migration method of the present invention;

[0047] Figure 4 This is a flowchart illustrating the third embodiment of the edge service migration method of the present invention;

[0048] Figure 5 This is a structural block diagram of the first embodiment of the edge service migration device of the present invention.

[0049] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0050] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0051] Reference Figure 1 , Figure 1 This is a schematic diagram of the edge service migration device structure of the hardware operating environment involved in the embodiment of the present invention.

[0052] like Figure 1 As shown, the edge service migration device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk drive. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0053] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on edge service migration devices and may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0054] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and an edge service migration program.

[0055] exist Figure 1In the edge service migration device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the edge service migration device of the present invention can be set in the edge service migration device, and the edge service migration device calls the edge service migration program stored in the memory 1005 through the processor 1001 and executes the edge service migration method provided in the embodiment of the present invention.

[0056] This invention provides an edge service migration method, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the edge service migration method of the present invention.

[0057] In this embodiment, the edge service migration method includes the following steps:

[0058] Step S10: Determine the next edge server based on the user's movement trajectory prediction results.

[0059] It should be noted that the execution subject of the method in this embodiment can be a computing service device with edge service migration, network communication, and program execution functions, such as a mobile phone, tablet computer, or personal computer, or other electronic devices that perform the same or similar functions. The following description uses the aforementioned edge service migration device (hereinafter referred to as the migration device) to illustrate this embodiment and the subsequent embodiments.

[0060] Understandably, the above-mentioned mobile trajectory prediction results can be the result of predicting the user's mobile trajectory. The mobile trajectory prediction results may include the predicted location that the user is about to arrive at, where the predicted location is outside the coverage area of ​​the current edge server.

[0061] It should be noted that the aforementioned next edge server can be an edge server that provides edge computing services to users and covers the aforementioned predicted location. The next edge server is determined based on the aforementioned predicted location when the user is in the current server's coverage area.

[0062] In a specific implementation, the aforementioned migration device can be associated with each edge server and can predict the user's movement trajectory based on the user's travel information and the user's real-time location to predict the predicted location of the user when the user exceeds the coverage service of the current edge server. Then, a movement trajectory prediction result containing the predicted location is generated. Finally, the edge server covering the predicted location is queried from each edge server, and the queried edge server is used as the next edge server. If there are multiple edge servers queried, the server closest to the predicted location is selected first and used as the next edge server.

[0063] It should be understood that the next edge server is determined when the user is on the current edge server. Therefore, when the user arrives at a predicted location that is outside the coverage area of ​​the current edge server, the user can directly use the edge computing services provided by the next edge server. This avoids the problem of interrupting user services caused by the process of switching edge computing service nodes when the user is outside the coverage area of ​​the current edge server.

[0064] Step S20: Determine the continuity service data to be migrated based on the busy level of the next edge server.

[0065] It should be noted that the above-mentioned level of activity can be determined by the utilization rate of computing power and storage of the next edge server. That is, the higher the utilization rate of computing power and storage, the higher the level of activity, and vice versa.

[0066] It is understood that the aforementioned continuity service data may be the data that needs to be processed to provide continuity services to users, as well as the necessary data required to provide continuity services.

[0067] In its implementation, after determining the next edge server, the migration device can query the busy status table of the next edge server in advance to check the busy level of the next edge server during the user's current time period. If the busy level of the current time period is low, it can be determined that after sending the continuity service data to be migrated to the next edge server in advance, the next edge server can process the data quickly. Thus, after the user enters the coverage service of the next edge server, the next edge server can quickly continue to provide services to the user. At this time, it can be determined that the continuity service data to be migrated is the relevant data currently providing continuity services to the user.

[0068] It should be understood that if the current time period is highly busy, it is advisable to promptly send the relevant data for providing continuous service to users to the next edge server. However, the next edge server may not be able to process the data quickly. In this case, the data required for providing continuous service to users when they access the required edge server can be processed in advance on the current edge server. This alleviates the pressure on the next edge server and ensures that it can effectively provide the corresponding service to users. Therefore, the continuous service data to be migrated can be determined as the relevant data for providing continuous service to users currently, plus the processed data obtained by processing the data required for providing continuous service to users when they access the required edge server.

[0069] It should be noted that the aforementioned busy status table can be generated periodically by the edge server to represent its busy status. This busy status table can be synchronized from the cloud computing center to other edge servers or directly to nearby edge servers. The busy status table can include time periods, the corresponding busy level for each time period, the main types of business being processed, and their corresponding processing percentages. The time periods can be divided according to dimensions such as weekdays and holidays, and must at least be divided into regular weekday working hours, regular weekday closing hours, and holidays to ensure that the busy level can be determined for each time period. Business types can include video, map, etc. The busy status table can include multiple main types of business being processed and their corresponding processing percentages. The aforementioned migration device can determine the corresponding time period from the busy status table based on the user's current time period, and query the computing power and storage utilization percentages of each business within that time period to determine the busy level based on the percentages.

[0070] Understandably, the aforementioned data may be necessary data for providing continuity services to the next edge server. For example, if the continuity service is a navigation service, the necessary data required for the map navigation service, such as the URL, starting point, ending point, and user navigation preferences, can be synchronized to the next edge server.

[0071] Step S30: Transmit the continuity service data to the next edge server.

[0072] In practical implementation, when the next edge server is not busy, the aforementioned migration device can transmit the relevant data for providing continuous services to users as continuous service data in advance to the next edge server. Alternatively, when the next edge server is busy, it can transmit the relevant data for providing continuous services to users, as well as the processed data obtained by processing the data required to provide continuous services to users when they enter the required edge server, as continuous service data to be migrated to the next edge server in advance. After transmitting the aforementioned continuous service data to the next edge server in advance, the migration of user services is completed. When a user switches from the current edge server to the next edge server, the next edge server can directly provide continuous services to the user based on the continuous service data to be migrated, ensuring uninterrupted migration of user services.

[0073] This embodiment determines the next edge server based on the user's movement trajectory prediction results; then, it determines the continuous service data to be migrated based on the busy level of the next edge server; finally, it transmits the continuous service data to the next edge server. Compared to existing technologies where edge servers have a certain coverage area, causing service interruptions when the user's geographical location changes from the coverage area of ​​the current edge server to the coverage area of ​​the next edge server due to the switching of edge computing service nodes, this embodiment ensures uninterrupted service migration through the aforementioned edge service migration method, effectively improving the user experience.

[0074] refer to Figure 3 , Figure 3 This is a flowchart illustrating the second embodiment of the edge service migration method of the present invention.

[0075] Based on the first embodiment described above, in this embodiment, step S20 includes:

[0076] Step S201: Determine whether the current busy level of the next edge server has reached the preset busy level.

[0077] It should be noted that the above-mentioned preset busy level can be used to determine whether the busy level is high. That is, if the busy level reaches the preset busy level, the busy level is determined to be high; conversely, if the busy level does not reach the preset busy level, the busy level is determined to be low.

[0078] In a practical implementation, the aforementioned migration device can determine whether the busy level is high by detecting whether the current busy level of the next edge server reaches the preset busy level.

[0079] Step S202: If the preset level is reached, then obtain the target service type that the next edge server supports processing.

[0080] It should be noted that the target business type mentioned above refers to the main processing business supported by the next edge server. This main processing business can be a business type that ranks among the top three or top five in terms of the number of processes processed.

[0081] In practical implementation, when the migration device detects that the busy level of the next edge server reaches the preset level, it can determine that the busy level of the next edge server is high. If the relevant data for providing continuous services to the user is sent to the next edge server in advance, the next edge server will prioritize processing the service of the target service type when the service type of the continuous service required by the user is inconsistent with the target service type. Instead, it will not quickly process the relevant data transmitted by the user in advance, resulting in service interruption. Therefore, the migration device needs to obtain the target service type that the next edge server supports in processing, so as to determine the continuous service data to be migrated based on the degree of matching between the target service type and the service type of the continuous service currently required by the user.

[0082] Furthermore, in this embodiment, after step S202, the method further includes:

[0083] Step S202': If the preset level is not reached, obtain relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the relevant data.

[0084] In specific implementation, when the migration device detects that the busy level of the next edge server has not reached the preset level, it can determine that the busy level of the next edge server is low. It can also determine that after sending the data to the next edge server in advance, the next edge server can process the data more quickly. Therefore, the relevant data for providing continuous services to users can be transmitted to the next edge server in advance as continuous service data to be migrated, so that after the user enters the coverage service of the next edge server, the next edge server can quickly continue to provide services to the user.

[0085] Step S203: Determine the degree of matching between the service type of the current continuous service required by the user and the target service type, and obtain the pending data to be processed when providing the current continuous service to the user.

[0086] In a specific implementation, after obtaining the target service type supported by the next edge server, the migration device can match the service type of the user's current required continuous service with the target service type, determine the degree of matching between the two, and then obtain the pending data to be processed when providing the current continuous service to the user.

[0087] Step S204: Determine the continuity service data to be migrated based on the matching degree and the data to be processed.

[0088] In a specific implementation, the aforementioned migration device can determine the amount of data to be pre-processed in the current edge server from the data to be processed based on the degree of matching, and then pre-process the pre-processed data, and then use the pre-processed data and the relevant data for providing continuous services to users as the continuous service data to be migrated.

[0089] It should be understood that the aforementioned advance processing can perform calculations on the data to be processed in advance and cache intermediate results during the calculation process, so that after the data obtained from the advance processing is transmitted to the next edge server, the next edge server can directly use the calculation results to provide services to users.

[0090] It should be noted that a higher degree of matching indicates that the business mainly handled by the next edge server is consistent with the business requiring continuous service from the user. This means that the next edge server can accurately provide continuous service to the user without needing to process too much data in advance on the current edge server. Therefore, the amount of data processed in advance is lower. Conversely, a higher degree of matching indicates that the business mainly handled by the next edge server is inconsistent with the business requiring continuous service from the user. This means that too much data needs to be processed in advance on the current edge server to ensure that the next edge server can accurately provide continuous service to the user. Therefore, the amount of data processed in advance is higher.

[0091] Furthermore, in this embodiment, before step S204, the following steps are also included:

[0092] The target duration required for the user to enter the target coverage area of ​​the next edge server is determined based on the movement trajectory prediction results.

[0093] It should be noted that the aforementioned target coverage service can be the coverage service of the next edge server.

[0094] It is understood that the target duration can be the time required for the user to travel from the current location to the preset location, that is, the time required for the user to travel from the current location to the target coverage service.

[0095] In a specific implementation, the aforementioned migration device can extract the user's current location and predicted location, as well as the predicted movement trajectory from the current location to the predicted location, from the aforementioned movement trajectory prediction results. Then, the trajectory prediction device can predict the target time required for the user to move from the current location to the predicted location. This target time can be used to determine the amount of data to be processed in advance.

[0096] Accordingly, in this embodiment, step S204 includes:

[0097] Step S2041: When the matching degree is higher than the first preset matching degree, the target duration is divided based on a preset ratio to obtain the target time period for advance processing.

[0098] It should be noted that the matching degree mentioned above can be divided into high, medium, and low, and the degree of advance processing can be determined according to the different matching degrees. The first preset matching degree mentioned above can be the matching degree that determines the matching degree to be high. That is, if the matching degree reaches the first preset matching degree, the matching degree can be determined to be relatively high.

[0099] It is understandable that the above-mentioned preset ratio can be the ratio for dividing the target duration, such as 1 to 2, that is, taking half of the target duration.

[0100] It should be noted that the target time period mentioned above can be the period before the user enters the next edge server.

[0101] In a specific implementation, the aforementioned migration device can determine whether the matching degree is higher than the first preset matching degree. If it is higher than the first preset matching degree, it can be determined that the matching degree is high. Then, the target duration can be divided according to the preset ratio, and the result of the division can be used as the target time period for advance processing.

[0102] Step S2042: Extract the first target data from the data to be processed within the target time period after the user enters the target coverage area.

[0103] In a specific implementation, the aforementioned migration device can extract the data that needs to be processed when the user enters the aforementioned target coverage service and provides the current continuous service within the aforementioned target time period from the aforementioned data to be processed, and use this data as the aforementioned first target data.

[0104] Step S2043: Perform advance processing on the first target data to obtain the first advance data.

[0105] In specific implementation, the aforementioned migration device can perform advance processing on the aforementioned first target data. Since the service type of the user's current required continuous service and the target service type are highly matched, the next edge server can support the processing of the aforementioned data to be processed. The current edge server does not need to perform advance processing on all the data to be processed. At this time, a portion of the data can be processed in the current edge server, that is, the aforementioned first target data can be processed to obtain the first advance data, so as to alleviate the pressure on the next edge server and improve processing efficiency.

[0106] Step S2044: Obtain relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the first advanced data and the relevant data.

[0107] In a specific implementation, the aforementioned migration device can use the relevant time associated with the current continuous service and the aforementioned first advanced data as the continuous service data to be migrated, and transmit the continuous service data to the aforementioned next edge server. This allows the next edge server to use the first advanced data and relevant data to cope with the service pressure during the target time period before the user enters its coverage service when the user enters the next edge server. This ensures that the service is not interrupted when the edge server switches, while also reserving some time for the next edge server to provide services after the target time period.

[0108] Furthermore, in this embodiment, step S204 further includes:

[0109] Step S2041': When the matching degree is lower than the first preset matching degree but higher than the second preset matching degree, extract the second target data within the target duration after the user enters the target coverage area from the data to be processed.

[0110] It should be noted that the second preset matching degree can be the matching degree in the determination of the matching degree. That is, if the matching degree reaches the second preset matching degree and is lower than the first preset matching degree, then the matching degree can be determined to be in the middle.

[0111] In a specific implementation, the aforementioned migration device can determine the matching degree when the matching degree is lower than the lower than the preset matching degree but higher than the second preset matching degree. At this time, the data that needs to be processed when the user enters the target coverage service and provides the current continuous service within the target duration can be extracted from the data to be processed. This data is used as the second target data. It can be seen that the amount of the second target data is greater than the amount of the first target data.

[0112] Step S2042': Perform advance processing on the second target data to obtain second advance data.

[0113] In a specific implementation, the aforementioned migration device can perform advance processing on the aforementioned second target data. Since the matching degree is not high at this time, but the next edge server can still have a certain degree of matching with the business type of the continuous service currently required by the user, most of it can be processed in the current edge server, and the remaining part can be processed by the next edge server. That is, the aforementioned second target data is processed to obtain the second advance data, so as to alleviate the pressure on the next edge server and improve the processing efficiency.

[0114] Step S2043': Obtain relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the second advanced data and the relevant data.

[0115] In a specific implementation, the aforementioned migration device can use the relevant time associated with the current continuous service and the aforementioned second advanced data as the continuous service data to be migrated, and transmit the continuous service data to the aforementioned next edge server. This allows the next edge server to use the second advanced data and relevant data to cope with the service pressure within the target duration before the user enters its coverage service when the user enters the next edge server. This ensures that the service is not interrupted when the edge server switches, while also reserving some time for the next edge server to provide services after the target duration.

[0116] Furthermore, in this embodiment, step S204 further includes:

[0117] Step S2041”: When the matching degree is lower than the second preset matching degree, extract all remaining data that needs to be processed after the user enters the target coverage area from the data to be processed.

[0118] In a specific implementation, when the migration device detects that the matching degree is lower than the second preset matching degree, it can determine that the matching degree is low. At this time, the remaining data that has not yet been processed in the current edge server after the user enters the target coverage service can be extracted from the data to be processed. It can be seen that the data volume of the third target data is greater than the data volume of the second target data.

[0119] Step S2042”: Process the remaining data to obtain the third advanced data.

[0120] In a specific implementation, the aforementioned migration device can perform advance processing on the remaining data. Since the matching degree is low at this time, the next edge server cannot handle the business that the user currently needs for continuous service well. Therefore, the remaining part of the data to be processed after the current edge server has processed, that is, the remaining data that should be processed by the next edge server, can be all processed in advance on the current edge server, so that all the data to be processed is processed by the current edge server. That is, the aforementioned remaining data is processed in advance to obtain the third advance data, so as to ensure that the service is not interrupted.

[0121] Step S2043”: Obtain relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the third advanced data and the relevant data.

[0122] In a specific implementation, the aforementioned migration device can use the relevant time associated with the current continuity service and the aforementioned third advanced data as the continuity service data to be migrated, and transmit the continuity service data to the aforementioned next edge server, so that the next edge server can provide continuous services to users based on the third advanced data, ensuring that the service is not interrupted.

[0123] This embodiment determines whether the current busy level of the next edge server has reached a preset busy level. If it has, it obtains the target service type that the next edge server supports processing. It then determines the matching degree between the service type of the user's current required continuous service and the target service type, and obtains the pending data to be processed when providing the current continuous service to the user. Based on the matching degree and the pending data, it determines the continuous service data to be migrated. This embodiment determines the matching degree between the user's current required continuous service and the target service type, and determines the continuous service data to be migrated based on the matching degree and the pending data. If the matching degree is high, a portion of the pending data can be preprocessed to alleviate the pressure on the next edge server. If the matching degree is low, the remaining data can be preprocessed, ensuring that all pending data is processed by the current edge server, guaranteeing uninterrupted service. This embodiment effectively improves the efficiency of service migration by determining the continuous service data to be migrated based on the matching degree between the service type of the next edge server and the service type of the user's required continuous service.

[0124] refer to Figure 4 , Figure 4 This is a flowchart illustrating the third embodiment of the edge service migration method of the present invention.

[0125] Based on the above embodiments, in this embodiment, before step S10, the method further includes:

[0126] Step S01: Determine the destination location and arrival time of the destination from the user's travel data.

[0127] It should be noted that the aforementioned travel data may be trip information in the user's terminal, such as the time and location in notes or memos, or the time and location involved when the user navigates through a map. This embodiment does not limit this.

[0128] In a specific implementation, the aforementioned migration device can extract the user's target location and arrival time from the user's travel data. Correspondingly, if the user has not traveled, it is determined that the edge server where the user is currently located will not change, and there is no need to extract the target location and arrival time. The target location can be the predicted location.

[0129] Step S02: Calculate several travel times required for the user to travel from the current location to the target location using several preset transportation methods, and determine the time range based on the several travel times.

[0130] It should be noted that the above-mentioned preset transportation modes can be any transportation mode that the user can use, such as walking, car, bus, and walking.

[0131] In its implementation, the aforementioned migration device can sequentially calculate the travel time required for a user to reach their target location from their current location, considering all of the preset modes of transportation. Based on these calculated travel times, a time range can be determined. For example, if cycling takes 25 minutes, taking the bus takes 30 minutes, walking takes 50 minutes, and driving takes 10 minutes, the time range can be determined to be between 10 and 50 minutes.

[0132] Step S03: Determine whether the time difference between the current time and the arrival time is within the time range.

[0133] In a specific implementation, the aforementioned migration device can determine whether the user will use one of the aforementioned preset modes of transportation by judging whether the difference between the current time and the arrival time is within the aforementioned time range.

[0134] Step S04: If within the time range, select the target transportation mode corresponding to the time difference from the preset transportation modes, and predict the user's travel trajectory based on the movement trajectory corresponding to the target transportation mode to obtain the movement trajectory prediction result.

[0135] In its implementation, when the aforementioned migration device detects that the time difference is within the aforementioned time range, it can determine from several preset transportation modes the target transportation mode whose travel time to the target location is closest to the aforementioned time difference. Continuing with the example of the aforementioned time range, if the calculated time difference is 37 minutes, it can be determined that the travel time using a bus (30 minutes) is close to the aforementioned time difference, thus confirming that the user will use the bus. Furthermore, after determining the target transportation mode, the migration device can predict the user's travel trajectory using the user's current location as the starting point, the target location as the destination, the aforementioned time difference as the travel time, and the route corresponding to the target transportation mode as the movement trajectory, thereby obtaining the aforementioned movement trajectory prediction result.

[0136] It should be understood that if there are multiple target modes of transportation whose travel time to reach the target location is closest to the above time difference, that is, the occurrence time of multiple target modes of transportation is consistent with the above time difference and has the lowest deviation from the above time difference compared to other modes of transportation, then the mode of transportation that the user already owns, such as a vehicle, will be given priority. If the user does not own a vehicle, then the mode of transportation closest to the user will be given priority.

[0137] Step S04': If the user is not within the specified time range, the target location and arrival time are input into a preset trajectory prediction model to predict the user's travel trajectory and obtain the movement trajectory prediction result. The preset trajectory prediction model is obtained by training the user's historical travel data.

[0138] It should be noted that the aforementioned historical travel data can be data on a user's past trips. This historical travel data can include time data and the corresponding location data. The time data can include the day of the year, the month, the day of the current month, and the time of day. The location data can include latitude and longitude data. For example, a user can be at location A at 8:30 AM on January 1, 2020. The longitude of location A is 116°25'10.44" and the latitude is 39°53'39.14"; the corresponding time data could be (1, 1, 1, 8, 30), and the corresponding location data would be (116°25'10.44" and 39°53'39.14").

[0139] Understandably, the aforementioned migration device can pre-train an initial trajectory prediction model based on the user's historical travel data to obtain a preset trajectory prediction model for predicting the user's movement trajectory. This initial trajectory prediction model can be a random forest model.

[0140] In a specific implementation, if the migration device detects that the time difference is not within the specified duration range, it can determine that the user has not used the aforementioned preset modes of transportation. In this case, the target location and arrival time can be input into the preset trajectory prediction model, which will then predict the user's travel trajectory based on the target location and arrival time and output the movement prediction result.

[0141] This embodiment determines the target location and arrival time from the user's travel data; calculates several travel times from the user's current location to the target location using several preset transportation methods, and determines a time range based on these travel times; it then determines whether the time difference between the current time and the arrival time is within the time range; if it is within the time range, it selects the target transportation method corresponding to the travel time and time difference from the preset transportation methods, and predicts the user's travel trajectory based on the movement trajectory corresponding to the target transportation method, obtaining a movement trajectory prediction result; if it is not within the time range, it inputs the target location and arrival time into a preset trajectory prediction model to predict the user's travel trajectory, obtaining a movement trajectory prediction result. The preset trajectory prediction model is obtained by training the user's historical travel data. This embodiment effectively improves the accuracy of movement trajectory prediction results by selecting an appropriate strategy to predict the user's travel trajectory based on whether the time difference between the current time and the arrival time is within the time range.

[0142] Furthermore, embodiments of the present invention also propose a storage medium storing an edge service migration program, wherein the edge service migration program, when executed by a processor, implements the steps of the edge service migration method as described above.

[0143] Reference Figure 5 , Figure 5 This is a structural block diagram of the first embodiment of the edge service migration device of the present invention.

[0144] like Figure 5 As shown, the edge service migration device proposed in this embodiment of the invention includes:

[0145] The service determination module 501 is used to determine the next edge server based on the user's movement trajectory prediction results.

[0146] Service data module 502 is used to determine the continuity service data to be migrated based on the busy level of the next edge server.

[0147] Service migration module 503 is used to transfer the continuous service data to the next edge server.

[0148] This embodiment determines the next edge server based on the user's movement trajectory prediction results; then, it determines the continuous service data to be migrated based on the busy level of the next edge server; finally, it transmits the continuous service data to the next edge server. This embodiment determines the next edge server based on the user's movement trajectory prediction results, and then transmits the continuous service data to the next edge server based on its busy level. Compared to existing technologies where edge servers have a certain coverage area, and service interruptions occur when the user's geographical location changes from the coverage area of ​​the current edge server to the coverage area of ​​the next edge server due to the switching of edge computing service nodes, this embodiment ensures uninterrupted service migration through the aforementioned edge service migration device, effectively improving the user experience.

[0149] Based on the first embodiment of the edge service migration device of the present invention described above, a second embodiment of the edge service migration device of the present invention is proposed.

[0150] In this embodiment, the service data module 502 is further configured to determine whether the current busy level of the next edge server has reached a preset busy level; if the preset busy level is reached, the target service type supported by the next edge server is obtained; the matching degree between the service type of the current continuous service required by the user and the target service type is determined, and the pending data to be processed when providing the current continuous service to the user is obtained; the continuous service data to be migrated is determined according to the matching degree and the pending data.

[0151] In one implementation, the service data module 502 is also used to determine the target duration required for the user to enter the target coverage area of ​​the next edge server based on the movement trajectory prediction result.

[0152] In one implementation, the service data module 502 is further configured to: divide the target duration based on a preset ratio to obtain a target time period for advance processing when the matching degree is higher than a first preset matching degree; extract the first target data within the target time period after the user enters the target coverage area from the data to be processed; perform advance processing on the first target data to obtain first advance data; acquire relevant data associated with the current continuous service; and determine the continuous service data to be migrated based on the first advance data and the relevant data.

[0153] In one implementation, the service data module 502 is further configured to: extract second target data within the target duration after the user enters the target coverage area from the data to be processed when the matching degree is lower than a first preset matching degree but higher than a second preset matching degree; perform advance processing on the second target data to obtain second advance data; acquire relevant data associated with the current continuous service; and determine the continuous service data to be migrated based on the second advance data and the relevant data.

[0154] In one implementation, the service data module 502 is further configured to, when the matching degree is lower than the second preset matching degree, extract all remaining data that needs to be processed after the user enters the target coverage area from the data to be processed; process the remaining data to obtain third advanced data; obtain relevant data associated with the current continuity service; and determine the continuity service data to be migrated based on the third advanced data and the relevant data.

[0155] In one implementation, the service data module 502 is further configured to, if the preset level is not reached, acquire relevant data associated with the current continuity service, and determine the continuity service data to be migrated based on the relevant data.

[0156] Based on the above embodiments of the edge service migration device of the present invention, a third embodiment of the edge service migration device of the present invention is proposed.

[0157] In this embodiment, the service determination module 501 is further configured to determine the target location and arrival time of the user's trip from the user's travel data; calculate several travel times required for the user to reach the target location from the current location using several preset transportation modes, and determine a time range based on the several travel times; determine whether the time difference between the current time and the arrival time is within the time range; if it is within the time range, select a target transportation mode from the several preset transportation modes whose travel time corresponds to the time difference, and predict the user's travel trajectory based on the movement trajectory corresponding to the target transportation mode to obtain a movement trajectory prediction result; if it is not within the time range, input the target location and the arrival time into a preset trajectory prediction model to predict the user's travel trajectory to obtain a movement trajectory prediction result, wherein the preset trajectory prediction model is obtained by training the user's historical travel data.

[0158] Other embodiments or specific implementations of the edge service migration device of the present invention can be referred to the above-described method embodiments, and will not be repeated here.

[0159] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0160] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0161] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0162] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for migrating edge services, characterized in that, The edge service migration method includes the following steps: The next edge server is determined based on the user's movement trajectory prediction results; The continuity service data to be migrated is determined based on the busy level of the next edge server; The continuous service data is transmitted to the next edge server; The step of determining the continuity service data to be migrated based on the busy level of the next edge server includes: Determine whether the current busy level of the next edge server has reached a preset busy level; If the preset busy level is reached, then the target service type supported by the next edge server is obtained; Determine the degree of matching between the service type of the user's current required continuous service and the target service type, and obtain the pending data to be processed when providing the user with the current required continuous service; The continuity service data to be migrated is determined based on the matching degree and the data to be processed.

2. The edge service migration method as described in claim 1, characterized in that, Before the step of determining the continuity service data to be migrated based on the matching degree and the data to be processed, the method further includes: Based on the movement trajectory prediction results, determine the target duration required for the user to enter the target coverage area of ​​the next edge server; Accordingly, the step of determining the continuity service data to be migrated based on the matching degree and the data to be processed includes: When the matching degree is higher than the first preset matching degree, the target duration is divided based on a preset ratio to obtain the target time period for advance processing; Extract the first target data of the user within the target time period after the user enters the target coverage area from the data to be processed; Perform advance processing on the first target data to obtain first advance data; Obtain relevant data associated with the currently required continuity service, and determine the continuity service data to be migrated based on the first advanced data and the relevant data.

3. The edge service migration method as described in claim 2, characterized in that, The step of determining the continuous service data to be migrated based on the matching degree and the data to be processed further includes: When the matching degree is lower than the first preset matching degree but higher than the second preset matching degree, extract the second target data within the target duration after the user enters the target coverage area from the data to be processed; The second target data is processed in advance to obtain the second advanced data; Obtain relevant data associated with the currently required continuity service, and determine the continuity service data to be migrated based on the second advanced data and the relevant data.

4. The edge service migration method as described in claim 2, characterized in that, The step of determining the continuous service data to be migrated based on the matching degree and the data to be processed further includes: When the matching degree is lower than the second preset matching degree, extract all remaining data that needs to be processed after the user enters the target coverage area from the data to be processed; The remaining data is processed to obtain the third advanced data; Obtain relevant data associated with the currently required continuity service, and determine the continuity service data to be migrated based on the third advanced data and the relevant data.

5. The edge service migration method as described in claim 1, characterized in that, After the step of determining whether the current busy level of the next edge server has reached the preset busy level, the method further includes: If the preset busy level is not reached, relevant data associated with the currently required continuity service is obtained, and the continuity service data to be migrated is determined based on the relevant data.

6. The edge service migration method as described in any one of claims 1 to 5, characterized in that, Before the step of determining the next edge server based on the user's movement trajectory prediction results, the method further includes: Determine the destination location and arrival time from the user's travel data; Calculate the travel time required for the user to reach the target location from the current location using several preset transportation methods, and determine the time range based on the travel time. Determine whether the time difference between the current time and the arrival time is within the specified duration. If the time is within the specified time range, a target transportation mode corresponding to the time difference is selected from the plurality of preset transportation modes, and the user's travel trajectory is predicted based on the movement trajectory corresponding to the target transportation mode to obtain the movement trajectory prediction result. If the user is not within the specified time range, the target location and arrival time are input into a preset trajectory prediction model to predict the user's travel trajectory and obtain the movement trajectory prediction result. The preset trajectory prediction model is obtained by training the user's historical travel data.

7. An edge service migration device, characterized in that, The device includes: The service determination module is used to determine the next edge server based on the user's movement trajectory prediction results; The service data module is used to determine the continuity service data to be migrated based on the busy level of the next edge server; The service migration module is used to transfer the continuous service data to the next edge server; The service data module is also used for: Determine whether the current busy level of the next edge server has reached a preset busy level; If the preset busy level is reached, then the target service type supported by the next edge server is obtained; Determine the degree of matching between the service type of the user's current required continuous service and the target service type, and obtain the pending data to be processed when providing the user with the current required continuous service; The continuity service data to be migrated is determined based on the matching degree and the data to be processed.

8. An edge service migration device, characterized in that, The device includes: a memory, a processor, and an edge service migration program stored on the memory and executable on the processor, the edge service migration program being configured to implement the steps of the edge service migration method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores an edge service migration program, which, when executed by a processor, implements the steps of the edge service migration method as described in any one of claims 1 to 6.

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