Traffic discarding method and related equipment based on parallel routing

Abstract

The embodiment of the present application provides a method for discarding traffic based on parallel routing and related equipment. The method for discarding traffic based on parallel routing includes: obtaining the amount of resources occupied by the first process and the amount of resources occupied by the second process; if the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold, then obtaining multi-dimensional traffic feature information; determining a traffic score based on the multi-dimensional traffic feature information; and determining whether the second process is discarded based on the traffic score. The technical solution of the embodiment of the present application objectively evaluates the second process corresponding to the traffic through traffic scoring, can accurately determine the priority level of each process, and discard unimportant traffic first, ensuring that important data will not be discarded or lost, and solving the problem that the discard strategy of the prior art easily leads to errors or losses of important data.

Description

Technical Field

[0001] The present application relates to the field of computer and communication technology, and in particular to a traffic discarding method based on parallel routing and related equipment. Background Art

[0002] Currently, in the Internet field, local traffic is prone to double during data migration, which can easily cause system jams and affect migration efficiency. To prevent this from happening, some processes are generally abandoned when traffic is too large, but the current abandonment strategy will abandon both important and ordinary data, which can easily lead to errors or loss of important data. Summary of the invention

[0003] The embodiments of the present application provide a traffic discarding method and related equipment based on parallel routing, thereby overcoming the problem that the discarding strategy of the prior art is prone to cause important data errors or losses, at least to a certain extent.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0005] According to one aspect of an embodiment of the present application, a method for discarding traffic based on parallel routing is provided, and the method for discarding traffic based on parallel routing includes:

[0006] Obtaining the amount of resources occupied by the first process and the amount of resources occupied by the second process;

[0007] If the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold, obtaining multi-dimensional traffic feature information;

[0008] Determining a traffic score according to the multi-dimensional traffic feature information;

[0009] According to the traffic score, it is determined whether the second process is abandoned.

[0010] In one embodiment of the present application, determining whether the second process is abandoned according to the traffic score specifically includes:

[0011] If the traffic score is within a predetermined discard score interval, determining that the second process is discarded;

[0012] If the traffic score is outside the predetermined discard score interval, it is determined that the second process is not discarded.

[0013] In one embodiment of the present application, before determining whether the second process is abandoned according to the traffic score, the method further includes:

[0014] Acquire performance indicator data of a route, and determine overflow performance of the route according to the performance indicator data;

[0015] The predetermined discard score interval is determined according to the overflow performance of the route.

[0016] In one embodiment of the present application, determining the traffic score according to the multi-dimensional traffic feature information specifically includes:

[0017] The multi-dimensional traffic feature information is input into a traffic scoring model, and the traffic scoring model outputs a corresponding traffic score.

[0018] In one embodiment of the present application, the multi-dimensional traffic information includes real-time feature information and historical feature information, the traffic scoring model includes a first scoring sub-model and a second scoring sub-model, and the multi-dimensional traffic feature information is input into the traffic scoring model, and the traffic scoring model outputs the corresponding traffic score, specifically including:

[0019] Inputting the real-time feature information into a first scoring sub-model, and the first scoring sub-model outputting a first score;

[0020] Inputting the historical feature information into a second scoring sub-model, and the second scoring sub-model outputting a second score;

[0021] A traffic score is determined according to the first score and the second score.

[0022] In one embodiment of the present application, determining the traffic score according to the first score and the second score specifically includes:

[0023] If the first score is greater than a first score threshold, and the second score is greater than a second score threshold, determining that the traffic score is any value within a predetermined discard score interval;

[0024] If the second score is less than the first score threshold, and the second score is less than the second score threshold, the traffic score is determined to be any value outside the predetermined discard score interval.

[0025] In one embodiment of the present application, the multi-dimensional traffic information includes real-time feature information and historical feature information, and determining the traffic score according to the multi-dimensional traffic feature information specifically includes:

[0026] Extracting keywords from traffic based on the real-time feature information;

[0027] A traffic score is determined according to the historical feature information and the keywords in the traffic.

[0028] According to one aspect of an embodiment of the present application, a traffic discarding device based on parallel routing is provided, and the traffic discarding device based on parallel routing includes:

[0029] An occupied resource acquisition module, used to acquire the amount of resources occupied by the first process and the amount of resources occupied by the second process;

[0030] A characteristic information acquisition module, configured to acquire multi-dimensional traffic characteristic information if the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold;

[0031] A traffic score determination module, used to determine a traffic score according to the multi-dimensional traffic feature information;

[0032] The process abandonment decision module is used to determine whether the second process is abandoned according to the traffic score.

[0033] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the traffic discarding method based on parallel routing as described in the above embodiment is implemented.

[0034] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the traffic discarding method based on parallel routing as described in the above embodiments.

[0035] In the technical solutions provided in some embodiments of the present application, the traffic is scored according to the importance of the traffic based on multi-dimensional traffic feature information to obtain a traffic score, and whether the second process corresponding to the traffic should be abandoned is determined based on the traffic score. If the traffic score shows that the second process corresponding to the traffic is of low importance, the corresponding second process is abandoned first. If the traffic score shows that the second process corresponding to the traffic is of high importance, the abandonment of the corresponding second process is delayed. By objectively evaluating the second process corresponding to the traffic through the traffic score, the priority of each process can be accurately determined, and unimportant traffic can be abandoned first, ensuring that important data will not be abandoned or lost, and solving the problem that the abandonment strategy of the prior art easily leads to errors or losses of important data.

[0036] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0038] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied is shown.

[0039] Figure 2 The flowchart of a traffic discarding method based on parallel routing according to an embodiment of the present application is schematically shown.

[0040] Figure 3 is based on Figure 2 A specific implementation flow chart of step 300 in the traffic discarding method based on parallel routing shown in the corresponding embodiment.

[0041] Figure 4 is based on Figure 3 A specific implementation flow chart of step S330 in the traffic discarding method based on parallel routing shown in the corresponding embodiment.

[0042] Figure 5 is based on Figure 2 A specific implementation flow chart of step S400 in the traffic discarding method based on parallel routing shown in the corresponding embodiment.

[0043] Figure 6 is based on Figure 2 Another specific implementation flow chart of the traffic discarding method based on parallel routing shown in the corresponding embodiment.

[0044] Figure 7 A block diagram of a traffic discarding device based on parallel routing according to an embodiment of the present application is schematically shown.

[0045] Figure 8 The structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0046] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0047] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0048] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0049] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0050] Figure 1 A schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied is shown.

[0051] like Figure 1 As shown, the system architecture may include terminal devices (such as Figure 1 The embodiment of the present invention is a schematic diagram of a mobile phone 101, a tablet computer 102, a portable computer 103, a desktop computer, etc., a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the terminal device and the server 105. The network 104 may include various connection types, such as a wired communication link, a wireless communication link, etc.

[0052] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 105 may be a server cluster composed of multiple servers.

[0053] The user can use the terminal device to interact with the server 105 through the network 104 to receive or send messages, etc. The server 105 can be a server that provides various services. For example, the user uses the terminal device 103 (or the terminal device 101 or 102) to upload the amount of resources occupied by the first process and the amount of resources occupied by the second process to the server 105, and the server 105 can obtain the amount of resources occupied by the first process and the amount of resources occupied by the second process; if the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than the predetermined resource threshold, then obtain multi-dimensional traffic feature information; determine the traffic score based on the multi-dimensional traffic feature information; and determine whether the second process is abandoned based on the traffic score.

[0054] It should be noted that the traffic discarding method based on parallel routing provided in the embodiment of the present application is generally executed by the server 105, and accordingly, the traffic discarding device based on parallel routing is generally set in the server 105. However, in other embodiments of the present application, the terminal device may also have similar functions to the server, so as to execute the traffic discarding solution based on parallel routing provided in the embodiment of the present application.

[0055] The implementation details of the technical solution of the embodiment of the present application are described in detail below:

[0056] Figure 2 A flow chart of a method for discarding traffic based on parallel routing according to an embodiment of the present application is shown. The method for discarding traffic based on parallel routing can be executed by a server, which can be Figure 1 Refer to the server shown in . Figure 2 As shown, the traffic discarding method based on parallel routing at least includes:

[0057] Step S100, obtaining the amount of resources occupied by the first process and the amount of resources occupied by the second process.

[0058] Step S200: If the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold, multi-dimensional traffic feature information is obtained.

[0059] Step S300: determining a traffic score based on the multi-dimensional traffic feature information.

[0060] Step S400, determining whether the second process is abandoned according to the traffic score.

[0061] In an embodiment of the present application, when the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold, the abandonment strategy is triggered, at which time the multi-dimensional traffic feature information is first obtained, and then the traffic score is determined based on the multi-dimensional traffic feature information, and finally, it is determined whether the corresponding second process should be abandoned based on the traffic score. The embodiment of the present application objectively evaluates the second process corresponding to the traffic through the traffic score, and can accurately determine the priority of each process, and abandon unimportant traffic first, ensuring that important data will not be abandoned or lost, and solving the problem that the abandonment strategy of the prior art easily leads to errors or losses of important data.

[0062] In step S100, the amount of resources occupied by the first process and the amount of resources occupied by the second process may be obtained by the server itself or through a terminal device. The amount of resources occupied by the first process may include threads occupied by the first process, memory occupied by the first process, bandwidth occupied by the first process, etc. Similarly, the amount of resources occupied by the second process may also include threads occupied by the second process, memory occupied by the second process, bandwidth occupied by the second process, etc.

[0063] In the subsequent embodiments of the present application, threads are used as examples for description.

[0064] In step S200, if the sum of the resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold, it proves that the sum of the resources occupied by the first process and the amount of resources occupied by the second process is close to the critical value of the maximum resources that the system can provide. At this time, it is necessary to control the traffic to avoid a surge in traffic that causes system freezes and affects the efficiency of migration.

[0065] Taking the number of threads as an example, when the sum of the number of threads occupied by the first process and the number of threads occupied by the second process is greater than the predetermined thread threshold, it proves that the total number of threads required by the first process and the second process is close to the total number of threads in the system thread pool. If this is not managed, a large number of processes will not be allocated thread resources, resulting in system freezes and even interruption of some processes, affecting the overall efficiency of migration.

[0066] The above-mentioned predetermined resource threshold may be the maximum amount of resources that the system can provide, a critical value close to the maximum amount of resources that the system can provide, or a threshold with a margin determined according to the application environment.

[0067] Taking the resource amount as the number of threads as an example, the above-mentioned predetermined resource threshold can be the total number of threads in the system thread pool, such as 32 threads, or it can be a critical value close to the total number of threads in the system thread pool, such as 30 threads, or it can be a threshold with a margin determined according to the application environment, such as 24 threads.

[0068] When discarding is required, first obtain the multi-dimensional traffic feature information of the corresponding traffic, score the traffic according to the multi-dimensional traffic feature information, determine the importance of the corresponding traffic, and select the discard process according to the importance.

[0069] In step S300, there are many ways to determine the traffic score, such as determining the importance of the traffic one by one according to multiple dimensions in the multi-dimensional traffic feature information, and then integrating the importance of the traffic determined in each dimension to determine the final traffic importance, that is, the traffic score. Alternatively, the traffic score can be determined by judging based on the multi-dimensional traffic feature information, for example, by relying on a scoring model.

[0070] In some embodiments, Figure 2 As shown, determining the traffic score can rely on a traffic scoring model, and the specific operation is to input the multi-dimensional traffic feature information into the traffic scoring model, and the traffic scoring model outputs the corresponding traffic score.

[0071] Specifically, in some embodiments, the specific implementation of step S300 can be found in Figure 3 . Figure 3 is based on Figure 2 Detailed description of step S300 in the traffic discarding method based on parallel routing shown in the corresponding embodiment, in the traffic discarding method based on parallel routing, the multi-dimensional traffic information includes real-time feature information and historical feature information, the traffic scoring model includes a first scoring sub-model and a second scoring sub-model, and step S300 may include the following steps:

[0072] Step S310: input the real-time feature information into a first scoring sub-model, and the first scoring sub-model outputs a first score.

[0073] Step S320: input the historical feature information into a second scoring sub-model, and the second scoring sub-model outputs a second score.

[0074] Step S330: Determine a traffic score according to the first score and the second score.

[0075] In an embodiment of the present application, multi-dimensional traffic information includes real-time feature information and historical feature information, and the traffic scoring model includes a first scoring sub-model and a second scoring sub-model. Scoring is performed from different dimensions through multiple scoring sub-models, and then the scores from different dimensions are comprehensively sorted to obtain the final traffic score, which can more accurately reflect the importance of traffic.

[0076] In step S310, the first score is determined according to the real-time feature information, the real-time feature information includes real-time user feature information and real-time non-user feature information, the real-time user feature information includes, and the real-time non-user information includes. The first score can reflect the importance of the real-time traffic itself.

[0077] Specifically, the training method of the first scoring sub-model specifically includes: obtaining a set of real-time feature information samples, wherein each real-time feature information sample is pre-calibrated with a corresponding first score; inputting the data of each of the real-time feature information samples into the first scoring sub-model respectively to obtain a first score output by the process strategy; if the first score obtained after the data of the real-time feature information sample is input into the first scoring sub-model is inconsistent with the first score calibrated in advance for the real-time feature information sample, adjusting the coefficient of the process strategy until they are consistent; when the data of all the real-time feature information samples are input into the first scoring sub-model, the first score obtained is consistent with the first score calibrated in advance for the real-time feature information sample, and the training ends.

[0078] In step S320, the second score is determined based on the historical feature information, which includes historical decision information and historical access information. The second score can reflect the previous importance ranking of the traffic and can be used as a reference for current judgment.

[0079] Specifically, the training method of the second scoring sub-model specifically includes: obtaining a set of historical feature information samples, wherein each historical feature information sample is pre-calibrated with a corresponding second score; inputting the data of each of the historical feature information samples into the second scoring sub-model respectively to obtain the second score output by the process strategy; if the second score obtained after the data of the historical feature information sample is input into the second scoring sub-model is inconsistent with the second score calibrated in advance for the historical feature information sample, adjusting the coefficient of the process strategy until they are consistent; when the data of all the historical feature information samples are input into the second scoring sub-model, the second score obtained is consistent with the second score calibrated in advance for the historical feature information sample, and the training ends.

[0080] In step S330, there are many ways to determine the traffic score, such as summing, averaging, weighted sum and weighted average of the first score and the second score, and then using the result as the traffic score. The first score and the second score can also be compared with a score threshold to assign a score. The first score and the second score can also be input into a total score sub-model, and the total score sub-model outputs the corresponding traffic score.

[0081] Specifically, in some embodiments, the specific implementation of step S330 can be found in Figure 4 . Figure 4 is based on Figure 3 The detailed description of step S330 in the traffic discarding method based on parallel routing shown in the corresponding embodiment, in the traffic discarding method based on parallel routing, step S330 may include the following steps:

[0082] Step S331: If the first score is greater than a first score threshold, and the second score is greater than a second score threshold, then the traffic score is determined to be any value within a predetermined discard score interval.

[0083] Step S332: If the second score is less than the first score threshold and the second score is less than the second score threshold, determine that the traffic score is any value outside the predetermined discard score interval.

[0084] In this embodiment, the first score and the second score are compared with the score threshold to assign scores. Specifically, if the first score is greater than the first score threshold, and the second score is greater than the second score threshold, it is proved that the importance of the traffic is low from two dimensions, and the corresponding second process should be abandoned. At this time, the traffic score is determined to be any value within the predetermined abandonment score interval. If the second score is less than the first score threshold, and the second score is less than the second score threshold, it is proved that the importance of the traffic is high from two dimensions, and the corresponding second process should not be abandoned. At this time, the traffic score is determined to be any value outside the predetermined abandonment score interval.

[0085] When the first score is greater than the first score threshold and the second score is less than the second score threshold, or the first score is less than the first score threshold and the second score is greater than the second score threshold, it is necessary to further determine the actual score situation.

[0086] One way is to sum, average, weighted sum, weighted average, etc. the first score and the second score, and then use the obtained result as the traffic score.

[0087] Another way is to input the first score and the second score into the total score sub-model, and the total score sub-model outputs the corresponding traffic score.

[0088] Specifically, the training method of the total scoring sub-model includes: obtaining a set of scoring samples, wherein each scoring sample includes a first score and a second score, and the corresponding traffic score is calibrated in advance; inputting the data of each of the scoring samples into the total scoring sub-model respectively to obtain the traffic score output by the process strategy; if the traffic score obtained after the data of the scoring sample is input into the total scoring sub-model is inconsistent with the traffic score calibrated in advance for the scoring sample, adjusting the coefficient of the process strategy until they are consistent; when the data of all the scoring samples are input into the total scoring sub-model, the traffic score obtained is consistent with the traffic score calibrated in advance for the scoring sample, and the training is completed.

[0089] Specifically, in other embodiments, the specific implementation of step S300 can refer to the following embodiments. Figure 2 The detailed description of step S300 in the traffic discarding method based on parallel routing shown in the corresponding embodiment, in the traffic discarding method based on parallel routing, the multi-dimensional traffic information includes real-time feature information and historical feature information, and step S300 may include the following steps:

[0090] Keywords in the traffic are extracted according to the real-time feature information.

[0091] A traffic score is determined according to the historical feature information and the keywords in the traffic.

[0092] In this embodiment, the traffic score can also be determined by first extracting traffic keywords through keywords, then comprehensively judging the importance of the traffic keywords based on historical feature information, and then scoring the traffic to obtain the traffic score.

[0093] In step S400, determining whether the second process is abandoned may be based on whether the traffic score falls within a corresponding score interval.

[0094] Specifically, in some embodiments, the specific implementation of step S400 can be found in Figure 5 . Figure 5 is based on Figure 2 The detailed description of step S400 in the traffic discarding method based on parallel routing shown in the corresponding embodiment, in the traffic discarding method based on parallel routing, the multi-dimensional traffic information includes real-time feature information and historical feature information, and step S400 may include the following steps:

[0095] Step S410: If the traffic score is within a predetermined discard score interval, it is determined that the second process is discarded.

[0096] Step S420: If the traffic score is outside the predetermined discard score interval, determine that the second process is not discarded.

[0097] In this embodiment, if the traffic score is within the predetermined discard score interval, it proves that the importance level of the corresponding traffic is low and can be discarded first. At this time, it is determined that the corresponding second process is discarded. If the traffic score is outside the predetermined discard score interval, it proves that the importance level of the corresponding traffic is high and should be discarded later. At this time, it is determined that the second process is not discarded.

[0098] In some real-time examples, there may be multiple or only one predetermined abandonment score interval. In this embodiment, the predetermined abandonment score interval may be an interval greater than the predetermined abandonment score.

[0099] In some embodiments of this application, please refer to Figure 6 Before step S400, the method further includes:

[0100] Step S500, obtaining performance indicator data of a route, and determining overflow performance of the route according to the performance indicator data;

[0101] Step S600: determining the predetermined discarding score interval according to the overflow performance of the route.

[0102] In this embodiment, the predetermined abandonment score interval can also be determined dynamically, which is related to the routing performance. In this embodiment, the performance indicator data of the routing is first obtained, which includes the query rate per second (QPS), the transaction processing volume per second (TPS), the time consumption of the processing task, the remaining resource amount, etc., and then the corresponding overflow performance is determined according to the performance indicator data of the routing. The overflow performance refers to the performance of the traffic overflow. According to the severity of the overflow performance, the number of abandoned processes is determined. Specifically, the overflow performance is determined by calculating the query rate per second (QPS), the transaction processing volume per second (TPS), the time consumption of the processing task, the overflow resource amount, etc. In general, the greater the QPS, TPS, the time consumption of the processing task, and the overflow resource amount, the greater the overflow performance, that is, the remaining performance is negatively correlated with the QPS, TPS, the time consumption of the processing task, and the overflow resource.

[0103] When the traffic overflow is too serious, more processes need to be discarded, and the scheduled discard interval should be set wider; when the traffic overflow is not too serious, fewer processes need to be discarded, and the scheduled discard interval should be set narrower.

[0104] The following describes an apparatus embodiment of the present application, which can be used to execute the traffic discarding method based on parallel routing in the above-mentioned embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the above-mentioned embodiment of the traffic discarding method based on parallel routing in the present application.

[0105] Figure 7 A block diagram of a traffic discarding device based on parallel routing according to an embodiment of the present application is shown.

[0106] Reference Figure 7 As shown, according to an embodiment of the present application, a traffic discarding device 900 based on parallel routing includes:

[0107] The occupied resource acquisition module 910 is used to acquire the amount of resources occupied by the first process and the amount of resources occupied by the second process;

[0108] The characteristic information acquisition module 920 is used to acquire multi-dimensional traffic characteristic information if the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold;

[0109] A traffic score determination module 930, configured to determine a traffic score according to the multi-dimensional traffic feature information;

[0110] The process abandonment decision module 940 is used to determine whether the second process is abandoned according to the traffic score.

[0111] The implementation process of the functions and effects of each module in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned traffic discarding method based on parallel routing, and will not be repeated here.

[0112] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0113] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0114] Figure 8A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0115] It should be noted that Figure 8 The computer system of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0116] like Figure 8 As shown, the computer system includes a central processing unit (CPU) 1801, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1802 or the program loaded from the storage part 1808 to the random access memory (RAM) 1803, such as executing the method described in the above embodiment. In RAM 1803, various programs and data required for system operation are also stored. CPU 1801, ROM 1802 and RAM 1803 are connected to each other through bus 1804. Input / output (I / O) interface 1805 is also connected to bus 1804.

[0117] The following components are connected to the I / O interface 1805: an input section 1806 including a keyboard, a mouse, etc.; an output section 1807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1808 including a hard disk, etc.; and a communication section 1809 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 1809 performs communication processing via a network such as the Internet. A drive 1810 is also connected to the I / O interface 1805 as needed. A removable medium 1811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1810 as needed so that a computer program read therefrom is installed into the storage section 1808 as needed.

[0118] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 1809, and / or installed from a removable medium 1811. When the computer program is executed by a central processing unit (CPU) 1801, various functions defined in the system of the present application are executed.

[0119] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0120] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0121] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0122] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0123] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0124] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0125] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0126] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A traffic discarding method based on parallel routing, characterized in that: include: Obtaining the amount of resources occupied by the first process and the amount of resources occupied by the second process; If the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold, then obtaining multi-dimensional traffic characteristic information of the corresponding traffic, the multi-dimensional traffic characteristic information including real-time characteristic information and historical characteristic information; Determining a traffic score according to the multi-dimensional traffic feature information, wherein the traffic score indicates the importance of the traffic; Acquire performance indicator data of a route, and determine overflow performance of the route according to the performance indicator data; Determining a predetermined discard score interval according to the overflow performance of the route, wherein the more serious the overflow of the route is, the wider the corresponding predetermined discard score interval is; If the traffic score is within the predetermined discard score interval, determining that the second process corresponding to the traffic is discarded; If the traffic score is outside the predetermined discard score interval, it is determined that the second process corresponding to the traffic is not discarded.

2. The method for discarding traffic based on parallel routing as claimed in claim 1, characterized in that: Determining the traffic score according to the multi-dimensional traffic feature information specifically includes: The multi-dimensional traffic feature information is input into a traffic scoring model, and the traffic scoring model outputs a corresponding traffic score.

3. The method for discarding traffic based on parallel routing as claimed in claim 2, characterized in that: The traffic scoring model includes a first scoring sub-model and a second scoring sub-model. The multi-dimensional traffic feature information is input into the traffic scoring model, and the traffic scoring model outputs a corresponding traffic score, specifically including: Inputting the real-time feature information into a first scoring sub-model, and the first scoring sub-model outputting a first score; Inputting the historical feature information into a second scoring sub-model, and the second scoring sub-model outputting a second score; A traffic score is determined according to the first score and the second score.

4. The method for discarding traffic based on parallel routing as claimed in claim 3, characterized in that: The determining the traffic score according to the first score and the second score specifically includes: If the first score is greater than a first score threshold, and the second score is greater than a second score threshold, determining that the traffic score is any value within a predetermined discard score interval; If the second score is less than the first score threshold, and the second score is less than the second score threshold, the traffic score is determined to be any value outside the predetermined discard score interval.

5. The method for discarding traffic based on parallel routing as claimed in claim 1, characterized in that: Determining the traffic score according to the multi-dimensional traffic feature information specifically includes: Extracting keywords from traffic based on the real-time feature information; A traffic score is determined according to the historical feature information and the keywords in the traffic.

6. A traffic discarding device based on parallel routing, characterized in that: include: An occupied resource acquisition module, used to acquire the amount of resources occupied by the first process and the amount of resources occupied by the second process; A characteristic information acquisition module, configured to acquire multi-dimensional flow characteristic information of the corresponding flow if the sum of the amount of resources occupied by the first process and the amount of resources occupied by the second process is greater than a predetermined resource threshold, wherein the multi-dimensional flow characteristic information includes real-time characteristic information and historical characteristic information; A traffic score determination module, configured to determine a traffic score according to the multi-dimensional traffic feature information, wherein the traffic score indicates the importance of the traffic; The process abandonment decision module is used to obtain performance indicator data of the route, determine the overflow performance of the route according to the performance indicator data; determine a predetermined abandonment score interval according to the overflow performance of the route, wherein the more serious the overflow of the route is, the wider the corresponding predetermined abandonment score interval is; if the traffic score is within the predetermined abandonment score interval, determine that the second process corresponding to the traffic is abandoned; if the traffic score is outside the predetermined abandonment score interval, determine that the second process corresponding to the traffic is not abandoned.

7. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the traffic discarding method based on parallel routing as claimed in any one of claims 1 to 5 is implemented.

8. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, enables the one or more processors to implement the traffic discarding method based on parallel routing as described in any one of claims 1 to 5.

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