Data processing method and device, networking architecture and computer readable storage medium

Abstract

The embodiment of the invention provides a data processing method and device, a networking architecture and a computer readable storage medium. The method comprises the following steps: receiving uplink data; the uplink data comprises type identification information; classifying the uplink data according to the type identification information; and under the condition that the uplink data is classified into the sensed object data, the sensed object data is shunted to a preset local shunting device so as to perform data processing on the sensed object data through the local shunting device, and the sensed object data after data processing is sent to a second local server. According to the embodiment of the invention, the physical link is greatly shortened, the time delay is reduced, and the data transmission efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a data processing method, device, networking architecture and computer-readable storage medium. Background Art

[0002] At present, the technology of synaesthesia integration is still in the initial research stage. The high-precision perception algorithm has high requirements on computing power, and the real-time perception requires high speed and low latency for both the processing and feedback of the perception results. This places extremely high demands on the network architecture of synaesthesia integration.

[0003] The synaesthesia fusion network architecture mainly relies on traditional wireless communication systems, such as Figure 1 As shown, it takes up the computing power of the base station hardware and needs to be transmitted to the public network through the core network. It also requires a lot of routing forwarding. Summary of the invention

[0004] The present disclosure provides a data processing method, device, networking architecture and computer-readable storage medium.

[0005] In a first aspect, an embodiment of the present disclosure provides a data processing method, which is applied to a base station. The method includes:

[0006] Receiving uplink data; the uplink data including type identification information;

[0007] Classifying the uplink data according to the type identification information;

[0008] In the case where the uplink data is classified as perceived object data, the perceived object data is diverted to a preset local diversion device, so that the perceived object data is processed by the local diversion device, and the processed perceived object data is sent to a second local server.

[0009] In a second aspect, an embodiment of the present disclosure provides a data processing method, which is applied to a local distribution device, and the method includes:

[0010] Receiving the sensed object data diverted from the base station;

[0011] Performing data processing on the sensed object data;

[0012] The processed data of the sensed object is sent to the second local server.

[0013] In a third aspect, an embodiment of the present disclosure provides a data processing device, applied to a base station, comprising: a first memory and a first processor; the first memory stores a first computer program that can be executed by the first processor, and when the first computer program is executed by the first processor, the data processing method described in the first aspect is implemented.

[0014] In a fourth aspect, an embodiment of the present disclosure provides a data processing device, applied to a local diversion device, comprising: a second memory and a second processor; the second memory stores a second computer program that can be executed by the second processor, and when the second computer program is executed by the second processor, it implements the data processing method described in the second aspect.

[0015] In a fifth aspect, an embodiment of the present disclosure provides a networking architecture, including: a local offload device and at least one base station; the local offload device includes the data processing device according to the fourth aspect, and the base station includes the data processing device according to the third aspect;

[0016] One or more of the at least one base station communicates with the sensed object;

[0017] The data processing device in the local distribution device is connected to the data processing device in each base station and is connected to the second local server.

[0018] In a sixth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the data processing method described in the first aspect or the second aspect when executed by a processor.

[0019] The disclosed embodiment saves the computing power of the base station by diverting the perceived object data and having the local diversion device process the perceived object data. The local diversion device transmits the processed perceived object data to the second local server without passing through the public network, thereby improving user privacy security. Moreover, since the data is transmitted through the local diversion device, there is no large amount of routing forwarding in the middle, which greatly shortens the physical link, reduces the delay, and improves the data transmission efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In the accompanying drawings of the embodiments of the present disclosure:

[0021] Figure 1 It is a schematic diagram of the structure of a traditional wireless communication system;

[0022] Figure 2 A schematic diagram of a novel network architecture provided for an embodiment of the present disclosure;

[0023] Figure 3 A flow chart of a data processing method applied to a base station provided in an embodiment of the present disclosure;

[0024] Figure 4 A flow chart of a data processing method applied to a local distribution device provided by an embodiment of the present disclosure;

[0025] Figure 5 A schematic diagram of a data processing method provided by an embodiment of the present disclosure;

[0026] Figure 6 A flowchart of an exemplary camera data processing method provided in an embodiment of the present disclosure;

[0027] Figure 7 A block diagram of a first data processing device applied to a base station provided in an embodiment of the present disclosure;

[0028] Figure 8 A block diagram of the composition of a second data processing device applied to a local traffic distribution device provided by an embodiment of the present disclosure;

[0029] Fig. 9 A block diagram of a second data processing device applied to a base station provided in an embodiment of the present disclosure;

[0030] Fig.10 A block diagram of the composition of a second data processing device applied to a local distribution device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, the communication perception data processing method and computer-readable storage medium provided by the embodiments of the present disclosure are described in detail below in conjunction with the accompanying drawings.

[0032] The present disclosure will be described more fully below with reference to the accompanying drawings, but the embodiments shown may be embodied in different forms, and the present disclosure should not be construed as being limited to the embodiments set forth below. On the contrary, the purpose of providing these embodiments is to make the present disclosure thorough and complete, and will enable those skilled in the art to fully understand the scope of the present disclosure.

[0033] The accompanying drawings of the embodiments of the present disclosure are used to provide a further understanding of the embodiments of the present disclosure, and constitute a part of the specification, and are used together with the detailed embodiments to explain the present disclosure, and do not constitute a limitation of the present disclosure. By describing the detailed embodiments with reference to the accompanying drawings, the above and other features and advantages will become more apparent to those skilled in the art.

[0034] The present disclosure may be described with reference to plan views and / or cross-sectional views by means of ideal schematic views of the present disclosure. Therefore, the exemplary illustrations may be modified according to manufacturing techniques and / or tolerances.

[0035] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0036] The terms used in the present disclosure are only used to describe specific embodiments and are not intended to limit the present disclosure. The term "and / or" as used in the present disclosure includes any and all combinations of one or more related enumerated items. The singular forms "one" and "the" as used in the present disclosure are also intended to include plural forms, unless the context clearly indicates otherwise. The terms "including", "made of..." as used in the present disclosure specify the presence of the features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof.

[0037] Unless otherwise defined, all terms (including technical and scientific terms) used in this disclosure have the same meaning as commonly understood by those of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and this disclosure, and will not be interpreted as having an idealized or overly formal meaning unless explicitly defined in this disclosure.

[0038] The present disclosure is not limited to the embodiments shown in the drawings, but includes modifications of the configurations formed based on the manufacturing process. Therefore, the regions illustrated in the drawings have schematic properties, and the shapes of the regions shown in the drawings illustrate the specific shapes of the regions of the elements, but are not intended to be limiting.

[0039] With the development of 5G communication technology and the increase in various business usage scenarios, wireless mobile communication systems are not limited to traditional communication application scenarios. Combining wireless communication with related vertical industries has also become a new research and application direction for wireless communication equipment vendors and operators. For example, combining communication systems with perception systems, based on the integration of resources and equipment, broadens wireless communication application scenarios and creates new industry value for the wireless communication industry.

[0040] The integration of communication and perception systems is called "communication and perception integration", abbreviated as "synaesthesia integration" or "synaesthesia". "Communication and perception integration" is written as Integrated Sensing And Communication, abbreviated as ISAC, and is collectively referred to as synaesthesia integration below.

[0041] The integration of interawareness has broadened the application scenarios of traditional communications and provided many values. First, both communication and perception require the use of radio spectrum resources, and wireless spectrum is a very scarce and valuable resource. If wireless signals can be used to transmit information and perceive information, spectrum resources can be saved and spectrum utilization can be improved.

[0042] Secondly, communication and perception require similar hardware devices (such as transceiver antennas, amplifiers, filters, etc.), which are also very expensive and complex. If the original equipment can support both communication and perception with minimal changes, it is equivalent to saving hardware costs.

[0043] Thirdly, both communication and perception have similar information processing processes (such as signal encoding, modulation, demodulation, decoding, etc.), which are very complex. If the radar perception function can be integrated into a wireless communication base station, and a set of equipment can simultaneously realize the functions of communication and perception, and achieve communication-assisted perception and perception-assisted communication environment, it will be of great value to communication and perception application scenarios. The application scenarios that are gradually being promoted, such as low-altitude security warning, Internet of Vehicles road supervision, medical health monitoring, etc., also confirm this point.

[0044] In summary, the integrated fusion of interawareness can bring many benefits to the operation and maintenance costs and application scope of communication base stations and wireless sensing systems, broaden the application scenarios of wireless communications, and become a key technology for research in the 5G-Advanced (5G-Evolution) stage, as well as one of the core visions of 6G.

[0045] At present, the technology of synaesthesia integration is still in the initial research stage. The high-precision perception algorithm has high requirements on computing power, and the real-time perception requires high speed and low latency for both the processing and feedback of the perception results. This places extremely high demands on the network architecture of synaesthesia integration.

[0046] The current synaesthesia integrated fusion network architecture mainly relies on the following Figure 1 The traditional wireless communication system 100 shown in the figure includes a first base station 101, a first core network 102, a first packet data network 103 and a first local server 104, wherein the first base station 101 is connected to the first core network 102, the first core network 102 is connected to the first packet data network 103, and the first packet data network 103 is connected to the first local server 104; the first base station 101 communicates with the first sensed object 105 and the first terminal 106 to obtain uplink data, and transmits the uplink data to the first local server 104 through the first core network 102 and the first packet data network 103 in sequence. The data of the first sensed object 105 needs to occupy the hardware computing power of the first base station 101. In addition, because it needs to be transmitted to the public network through the first core network 102, and a large number of routing and forwarding processes, it brings problems of large delay and poor user privacy security.

[0047] Local traffic diversion technology has emerged. With local traffic diversion, data no longer passes through the core network to reach the public network, but is transmitted to the local data center and related application servers through the local gateway, greatly improving the privacy and security of users. In addition, local traffic diversion is an important means to reduce latency and relieve the pressure on the core network of the communication system, which can effectively solve the above-mentioned problems of large latency and insufficient computing power.

[0048] Therefore, in response to the above problems, the disclosed embodiment proposes a new networking architecture of synaesthesia integration based on local shunt technology. Only one hardware single-board device is added to the traditional synaesthesia integrated base station to optimize the traditional networking architecture, solve the problems of large latency, computing power impact, and poor privacy security of perceived users in the current synaesthesia network, and propose a communication perception data processing method based on the new networking architecture. The method saves the computing power of the base station by shunting the perceived object data, and the perceived object data is processed by the local shunt device, and the processed perceived object data is transmitted to the local server by the local shunt device without passing through the public network, thereby improving the privacy security of users, and the transmission is carried out through the local shunt device without a large amount of routing forwarding in the middle, which greatly shortens the physical link, reduces the latency, and improves the data transmission efficiency.

[0049] like Figure 2 As shown, it is a schematic diagram of a new type of networking architecture 200 provided in an embodiment of the present disclosure.

[0050] The networking architecture 200 provided by the embodiment of the present disclosure includes: a local traffic distribution device 201 and at least one second base station 202 (which may be referred to as a base station or a synaesthesia base station for short);

[0051] The local traffic distribution device 201 includes a data processing device 2011 (which may be referred to as the first data processing device 2011) applied to the local traffic distribution device. The first data processing device 2011 is used to implement the data processing method applied to the local traffic distribution device according to the embodiment of the present disclosure.

[0052] Each second base station 202 of the at least one second base station 202 includes a data processing device 2021 applied to the base station (which may be referred to as the second data processing device 2021 for short); the second data processing device 2021 is used to implement the data processing method applied to the base station in the embodiment of the present disclosure;

[0053] One or more second base stations 202 of the at least one second base station 202 communicate with a second sensed object 203 (hereinafter referred to as a sensed object); and one or more second base stations 202 communicate with a second terminal 208 (hereinafter referred to as a terminal); the second sensed object 203 may include but is not limited to the first sensed object 105 described above; the second terminal 208 may include but is not limited to the first terminal 106 described above;

[0054] The first data processing device 2011 in the local distribution device 201 is connected to the second data processing device 2021 in each second base station 202, and is connected to the second local server 204; wherein the local distribution device 201 can be connected to the second local server 204 through an optical fiber; the second local server 204 can be a private network server;

[0055] The novel networking architecture 200 may further include: a second core network 205 (may be referred to as the core network) and a second packet data network 206 (may be referred to as the packet data network);

[0056] Each second base station 202 is respectively connected to a corresponding second core network 205;

[0057] The second core network 205 is connected to the corresponding second packet data network 206;

[0058] The second packet data network 206 is connected to the third local server 207; wherein the third local server 207 and the first local server 104 are both public network servers, and the two may be the same or different.

[0059] The second core network 205 may include but is not limited to the above-mentioned first core network 102 , and the second packet data network 206 may include but is not limited to the above-mentioned first packet data network 103 .

[0060] like Figure 2 As shown, at least one second base station 202 may include but is not limited to: the above-mentioned first base station 101, and may also include but is not limited to the third base station 202-1, the fourth base station 202-2, etc. A second data processing device 2021-1 may be set in the first base station 101, a second data processing device 2021-2 may be set in the third base station 202-1, and a second data processing device 2021-3 may be set in the fourth base station 202-2. The second core network 205 may include but is not limited to EPC (Evolved Packet Core), 5GC (5G core network), etc.

[0061] The local traffic distribution device 201 is a hardware board, which can be a dedicated service processing hardware board, and can be deployed alone or deployed together with the second base station 202 for shared network management and operation. This significantly shortens the data transmission link of the perceived object data, which is very valuable for application scenarios requiring low latency.

[0062] The local traffic distribution device 201 may further include: a synaesthesia computing power processing module 2012;

[0063] The synaesthesia computing power processing module 2012 is used to have high-performance AI (artificial intelligence) computing power, and can process the massive amount of perceived object data (or synaesthesia data) collected, thereby sinking the core network user plane data processing function to the local diversion device 201, and transferring the process that originally required the consumption of base station computing power to the second local server 204 for implementation, which significantly reduces the pressure on the base station and does not affect the communication services of ordinary users under the base station.

[0064] The local traffic distribution device 201 may further include at least one of the following: a base station frame backplane connection interface 2013, an expansion module 2014, and a third-party interface 2015;

[0065] The base station frame backplane connection interface 2013 is used to connect to the base station frame backplane; the base station frame backplane connection interface 2013 complies with the communication protocol of the second base station 202 main control board and can be plug-and-play without prior site survey.

[0066] Extension module 2014, used for function extension;

[0067] A third-party interface 2015, which may be used to connect to a third-party device other than the second base station 202;

[0068] The configuration of the extension module 2014 and the third-party interface 2015 enables the local diversion device 201 to interact with the second local server 204 for subsequent functional expansion, and on the other hand, to serve as a backup as the data of the perceived objects increases explosively.

[0069] A set of local diversion device 201 can simultaneously support 4G public network / 4G private network / 5G public network / 5G private network services. Only one service IP (Internet Protocol) address and one management IP address need to be added to achieve data interoperability with ultra-low energy consumption.

[0070] Compared with the traditional wireless communication system 100, the new networking architecture 200 of the disclosed embodiment retains the collection and transmission process of the upstream telepathic base station 202, and innovatively proposes to add a local diversion device 201, which can flexibly allocate uplink data, relieve the computing pressure of the base station 202, and avoid the leakage of personal privacy of the perceived object. For public network services initiated by ordinary terminals, the base station 202 directly sends them to the transmission equipment and finally to the core network; for uplink data initiated by the perceived object, the base station 202 and the local diversion device 201 can directly send them to the second local server 204, or select to send the data to the second local server 204 or the public network core network after screening. For data diverted to the local diversion device 201 and transmitted to the second local server 204 via the local diversion device 201, it does not need to pass through the core network, which effectively reduces the data transmission volume, relieves the pressure of the core network, and reduces the uplink data flow forwarding delay. In addition, if data needs to be encrypted or has network security requirements, it can be transmitted from the local diversion device 201 to the second local server 204 for encryption, authentication and other operations after local diversion, and then transmitted to the public network core network, reducing the possibility of the perceived object data being exposed in the public network and improving data security. In addition, when the local diversion device 201 fails, the public network services under the base station are not affected.

[0071] Based on the above-mentioned novel networking architecture 200, the data processing method of the embodiment of the present disclosure is described in detail below. Figure 2 The second base station, the second core network, the second packet data network, the second perceived object, the second terminal, etc. are respectively referred to as the base station, the core network, the packet data network, the perceived object, and the terminal.

[0072] Reference Figure 3 , Figure 5 , the present disclosure embodiment provides a data processing method, which is applied to a base station. The method may include steps S101-S103:

[0073] S101. Receive uplink data; the uplink data includes type identification information.

[0074] The type identification information may include but is not limited to any one or more of the following: data ID (identity identifier), source address, destination address, service type, and data packet length.

[0075] Before receiving the uplink data, the method may further include: starting a sensing function and a local offload function.

[0076] The base station can turn on the perception function switch and the local diversion switch, and the base station sends a perception request notification to the perceived object, and the perceived object generates a behavior action according to the perception request notification and generates regular behavior data. For example, the perceived object can be a camera, and the camera changes the camera shooting angle after receiving the perception request notification.

[0077] The sensed object can upload the sensed object data (including but not limited to the above-mentioned regular behavior data, the sensed object's collected data, etc.) to the base station as uplink data. Since not only the sensed object but also various terminals access the base station, the uplink data also includes terminal communication data.

[0078] The uplink data received by the base station may be the data of the perceived object or the terminal communication data.

[0079] Terminal communication data can be sent to the core network through the base station. If the perceived object data is also sent to the core network, it will seriously affect the computing power of the base station and increase the latency of the perceived object data, affecting the real-time perception. Therefore, the disclosed embodiment considers diverting the perceived object data and processing it by a local diversion device. Prior to this, the base station needs to first classify the received uplink data and distinguish the perceived object data from the uplink data.

[0080] S102: Classify the uplink data according to the type identification information.

[0081] The classification task can be completed by a diversion service preset in the base station. The diversion service receives uplink data, obtains type identification information contained in the uplink data, compares the obtained type identification information with the pre-stored type identification information, and when it is determined that the obtained type identification information is consistent with the pre-stored type identification information, the uplink data can be classified as perceived object data.

[0082] In some embodiments, the uplink data can be classified according to the data id. For example, the data id can be the id of the corresponding perceived object. According to the data id, it can be confirmed that the received uplink data is the data sent by the perceived object, and thus the uplink data is classified as perceived object data.

[0083] In some embodiments, the uplink data can be classified according to the task type. For example, the task of analyzing pedestrian flow can be determined as data sent by a camera, and the received uplink data can be confirmed to be data sent by a sensed object, so the uplink data is classified as sensed object data.

[0084] S103. When the uplink data is classified as perceived object data, the perceived object data is diverted to a preset local diversion device, so that the perceived object data is processed by the local diversion device, and the processed perceived object data is sent to a second local server.

[0085] The second local server connected to the local diversion device may be a private network server.

[0086] Before the sensed object data is diverted to the local diversion device, a user plane data transmission tunnel can be established in advance between the local diversion device and the base station for data interaction between the base station and the local diversion device. The base station can divert the classified sensed object data to the local diversion device through the user plane data transmission tunnel.

[0087] After the diversion service classifies the perceived object data, the perceived object data can be directly diverted to the local diversion device, or the perceived object data can be preliminarily screened to select the perceived object data that meets the conditions, and then the perceived object data that meets the conditions can be diverted to the local diversion device. The perceived object data that does not meet the preset conditions can be sent to the preset core network or directly discarded.

[0088] The diversion service can divide the perceived object data into multiple groups according to preset diversion rules [for example, network slicing rules and / or PLMN (Public Land Mobile Network) rules], and detect whether each group of perceived object data meets the preset conditions.

[0089] The preset conditions may include but are not limited to any one or more of the following:

[0090] The data accuracy of the sensed object data is greater than or equal to a preset accuracy threshold;

[0091] The sensed object data is unencrypted data;

[0092] The identity identifier of the sensed object data is consistent with the preset identity identifier;

[0093] The target address of the sensed object data is consistent with the preset address; and

[0094] The business type of the sensed object data is consistent with the preset business type.

[0095] In some embodiments, the diversion service may first filter out unencrypted perceived object data, and / or perceived object data with data accuracy greater than or equal to a preset accuracy threshold, and divert it to a local diversion device. By diverting the unencrypted perceived object data, the risk of personal privacy leakage caused by the unencrypted perceived object data being sent to the public network core network can be avoided; by diverting the perceived object data with data accuracy greater than or equal to a preset accuracy threshold, it can be avoided that the perceived object data with very low accuracy cannot be used after being sent to the local diversion device and its corresponding second local server, thereby wasting traffic and computing power. For the encrypted perceived object data, since it has been encrypted, it can be sent directly to the core network without the risk of privacy leakage; for the perceived object data with data accuracy less than the preset accuracy threshold, it can be directly discarded.

[0096] The local splitting device can transmit the processed perceived object data to the second local server via optical fiber transmission.

[0097] In some embodiments, the diversion service may divide the perceived object data into multiple groups of perceived object data according to preset diversion rules; the diversion rules may include but are not limited to: network slicing rules and / or PLMN (Public Land Mobile Network) rules; and each group of perceived object data is detected separately to see whether it meets preset conditions.

[0098] If any group of perceived object data meets the preset conditions, the offload service discards the group of perceived object data or sends it to the core network. If any group of perceived object data does not meet the preset conditions, the offload service discards the group of perceived object data or sends it to the core network.

[0099] Network slicing is an on-demand networking method that allows operators to separate multiple virtual end-to-end networks on a unified infrastructure. Each network slice is logically isolated from the wireless access network to the bearer network and then to the core network to adapt to a variety of applications.

[0100] PLMN refers to a cellular mobile communication network of a certain standard of a certain operator in a certain country or region. PLMN is a network established and operated by the government or operators approved by the government to provide land mobile communication services to the public. This network can be interconnected with other communication networks such as PSTN (Public Swithed Telephone Network) to form a communication network on the scale of the entire region or country.

[0101] Based on network slicing technology or PLMN technology, the perceived object data can be divided into multiple networks according to different division factors (for example, destination address, service type, identity, data accuracy, encryption, etc.). The perceived object data on each network can be regarded as a group of perceived object data. Each group of perceived object data can be detected separately to see whether it meets the preset conditions. If a group of perceived object data does not meet the preset requirements, the group of perceived object data will be discarded or sent to the core network through the corresponding network. If a group of perceived object data meets the preset requirements, it can be transmitted to the second local server via optical fiber.

[0102] The embodiments of the present disclosure perform initial screening of the perceived object data based on network slicing rules and / or PLMN rules, and process the perceived data that does not meet preset conditions based on network slicing rules and / or PLMN rules, so that the processing between multiple groups of data is not affected, avoiding data confusion.

[0103] In some embodiments, after classifying the uplink data according to the type identification information, the method may further include:

[0104] In the case where the uplink data is classified as terminal communication data, the terminal communication data is sent to a preset core network.

[0105] Because the base station communicates not only with the perceived object but also with multiple terminals, the uplink data contains not only the perceived object data but also the terminal communication data. When the offload service identifies that the uplink data is classified as terminal communication data according to the type identification information, the terminal communication data can be directly sent to the preset core network. Similarly, the downlink data of the core network is also directly transmitted to the base station.

[0106] Based on the addition of a local diversion device, the disclosed embodiment can flexibly transmit the data acquired by the integrated synaesthesia (including the perceived exclusive data and the terminal communication data) to the second local server or the third local server. The diverted perceived object data does not need to pass through the public network core network, and does not need to be processed in the base station. It can increase security authentication and improve data security. At the same time, it does not affect public network consumer users. Ordinary terminal users can use conventional data transmission paths to transmit terminal communication data to the core network for communication.

[0107] In some embodiments, after the sensed object data is diverted to a preset local diversion device, the method may further include:

[0108] receiving the sensed object data that does not meet the preset requirements and is returned by the local diversion device; the sensed object data that does not meet the preset requirements is detected by the local diversion device before data processing is performed on the sensed object data;

[0109] The perceived object data that does not meet the preset requirements is sent to the preset core network.

[0110] In some embodiments, after receiving the diverted sensed object data, the local diversion device may further screen the sensed object data before processing the sensed object data and sending the processed sensed object data to the second local server, that is, detecting whether the sensed object data meets the preset requirements. The local diversion device only processes the sensed object data that meets the preset requirements and sends it to the second local server. The sensed object data that does not meet the preset requirements may be directly discarded or returned to the base station, which is transmitted to the third local server through the core network. The third local server connected to the core network through the packet data network is a public network server.

[0111] The preset requirements may include but are not limited to any one or more of the following:

[0112] The data accuracy of the sensed object data is greater than or equal to a preset accuracy threshold;

[0113] The sensed object data is unencrypted data;

[0114] The identity identifier of the sensed object data is consistent with the preset identity identifier;

[0115] The target address of the sensed object data is consistent with the preset address; and

[0116] The business type of the sensed object data is consistent with the preset business type.

[0117] In some embodiments, after the sensed object data is diverted to a preset local diversion device, the method may further include:

[0118] Receiving the perception feedback data forwarded by the local diversion device; the perception feedback data is sent by a second local server connected to the local diversion device;

[0119] The perception feedback data is sent to the perceived object corresponding to the perceived object data and / or a preset core network.

[0120] In some embodiments, the sensory feedback data may include, but is not limited to, any one or more of the following:

[0121] data processed by the second local server on the sensed object data;

[0122] control data of the sensed object sent by the second local server, and

[0123] Downlink service data sent by the second local server.

[0124] After the second local server receives the perceived object data sent by the local diversion device, it can process the perceived object data, for example, encryption processing, authentication processing, etc. The perceived object data encrypted by the second local server can be returned to the base station as perception feedback data and sent to the core network through the base station to avoid privacy leakage.

[0125] After the second local server receives the perceived object data sent by the local diversion device, it can generate control data of the corresponding perceived object according to the behavior data or status data contained in the perceived object data, and return the control data to the base station through the diversion device of the local team as perception feedback data, and the base station returns it to the corresponding perceived object, so that the perceived object can be controlled by the control data, for example, adjusting the angle of the camera, etc.

[0126] After the second local server receives the sensed object data sent by the local diversion device, it can generate corresponding downlink business data based on the sensed object data. For example, if the current sensed object data indicates that the camera is turned on and ready, the second local server can generate downlink business data of the camera based on the sensed object data. For example, it can collect pedestrian flow data within a certain period of time, or schedule multiple set cameras according to preset priorities, and return the downlink business data to the corresponding camera through the local diversion device and the base station as perception feedback data, so that the corresponding camera performs the corresponding business.

[0127] The above-mentioned perception feedback data is transmitted to the base station through the local diversion device, and then transmitted downlink by the base station to the perceived object, achieving the closed-loop data processing purpose of collection-processing-feedback-adjustment.

[0128] Reference Figure 4 , Figure 5 , the embodiment of the present disclosure provides a data processing method, which is applied to a local distribution device. The method may include steps S201-S203:

[0129] S201. Receive the sensed object data diverted by the base station.

[0130] After receiving the sensed object data diverted by the base station and before performing data processing on the sensed object data, the method may further include:

[0131] Detect whether the data of the perceived object meets the preset requirements;

[0132] When the data of the sensed object meets the preset requirements, the process of processing the data of the sensed object is started;

[0133] In the case where the sensed object data does not meet the preset requirements, the sensed object data is discarded or returned to the base station, so that the returned sensed object data is sent to a preset core network through the base station.

[0134] After receiving the diverted perceived object data, the local diversion device can screen the perceived object data again, that is, detect whether the perceived object data meets the preset requirements. The local diversion device only processes the perceived object data that meets the preset requirements and sends it to the second local server. The perceived object data that does not meet the preset requirements can be directly discarded or returned to the base station, which will be transmitted to the third local server through the core network.

[0135] The preset requirements may include but are not limited to any one or more of the following:

[0136] The data accuracy of the sensed object data is greater than or equal to a preset accuracy threshold;

[0137] The sensed object data is unencrypted data;

[0138] The identity identifier of the sensed object data is consistent with the preset identity identifier;

[0139] The target address of the sensed object data is consistent with the preset address; and

[0140] The business type of the sensed object data is consistent with the preset business type.

[0141] In some embodiments, the local diversion device can again filter out the perceived object data whose target address is consistent with the preset address and / or the perceived object data whose service type is consistent with the preset service type for data processing and divert to the local diversion device. By secondary screening of the target address and service type, the main perception services can be screened out, which is convenient for intercepting unnecessary perception services or interference data.

[0142] In some embodiments, detecting whether the sensed object data meets the preset requirements may include:

[0143] Dividing the sensed object data into multiple groups of sensed object data according to a preset diversion rule; the diversion rule may include but is not limited to: a network slicing rule and / or a PLMN (public land mobile network) rule;

[0144] Each group of perceived object data is tested separately to see whether it meets the preset requirements.

[0145] In some embodiments, when the sensed object data does not meet the preset requirements, returning the sensed object data to the base station may include: returning one or more groups of sensed object data that do not meet the preset requirements to the base station.

[0146] Based on network slicing technology or PLMN technology, the perceived object data can be divided into multiple networks according to different division factors (for example, destination address, service type, identity, data accuracy, encryption, etc.), and the perceived object data on each network can be regarded as a group of perceived object data. Each group of perceived object data can be checked separately to see whether it meets the preset requirements. If a group of perceived object data does not meet the preset requirements, the group of perceived object data will be discarded or returned to the base station through the corresponding network. If a group of perceived object data meets the preset requirements, it can be transmitted to the second local server via optical fiber.

[0147] The disclosed embodiments re-screen the perceived object data based on network slicing rules and / or PLMN rules, and return the perceived data that does not meet preset requirements to the base station based on network slicing rules and / or PLMN rules, so that the processing between multiple groups of data is not affected, avoiding data confusion and data transmission confusion when returning data.

[0148] S202: Process the perceived object data.

[0149] In some embodiments, data processing is performed on the perceived object data, including but not limited to any one or more of the following: data encoding, data modulation, data calculation, data prediction, and data analysis.

[0150] In addition to completing the most basic data encoding and decoding, data modulation and demodulation and other processing operations, the local diversion device can also process the massive amount of perceived object data collected, sink the core network user plane data processing function to the local diversion device, and transfer the process that originally required the consumption of base station computing power to the local diversion device to reduce the pressure on the base station without affecting the communication services of ordinary users under the base station. For example, the local diversion device can perform data preprocessing on the camera acquisition data (including but not limited to data format conversion, abnormal data cleaning, etc.), predict the data volume and data content of the camera data transmitted by the corresponding camera in the future based on the data volume and data content of the current camera data; analyze the camera data to see if there is any content that does not comply with regulations, etc.

[0151] S203: Send the processed data of the sensed object to a second local server.

[0152] After the local shunt device processes the data of the sensed object, it can directly send it to the second local server (for example, it can be sent via optical fiber). Since the sensed object data is directly transmitted through the local shunt device, there is no large amount of routing forwarding in the middle, which greatly shortens the physical link, reduces the delay, and improves the data transmission efficiency.

[0153] In some embodiments, after sending the processed perceived object data to the second local server, the method may further include:

[0154] Receiving the perception feedback data returned by the second local server;

[0155] The sensing feedback data is forwarded to the base station, so that the base station sends it to the sensed object corresponding to the sensed object data and / or a preset core network.

[0156] In some embodiments, the sensory feedback data may include, but is not limited to, any one or more of the following:

[0157] data processed by the second local server on the sensed object data;

[0158] control data of the sensed object sent by the second local server, and

[0159] Downlink service data sent by the second local server.

[0160] After the second local server receives the perceived object data sent by the local diversion device, it can process the perceived object data, for example, encrypt it. The perceived object data encrypted by the second local server can be returned to the base station as perception feedback data and sent to the core network through the base station to avoid privacy leakage.

[0161] After the second local server receives the perceived object data sent by the local diversion device, it can generate control data of the corresponding perceived object according to the behavior data or status data contained in the perceived object data, and return the control data to the base station through the diversion device of the local team as perception feedback data, and the base station returns it to the corresponding perceived object, so that the perceived object can be controlled by the control data, for example, adjusting the angle of the camera, etc.

[0162] After the second local server receives the sensed object data sent by the local diversion device, it can generate corresponding downlink business data based on the sensed object data. For example, if the current sensed object data indicates that the camera is turned on and ready, the second local server can generate downlink business data of the camera based on the sensed object data. For example, it can collect pedestrian flow data within a certain period of time, or schedule multiple set cameras according to preset priorities, and return the downlink business data to the corresponding camera through the local diversion device and the base station as perception feedback data, so that the corresponding camera performs the corresponding business.

[0163] The above-mentioned perception feedback data is transmitted to the base station through the local diversion device, and then transmitted downlink by the base station to the perceived object, achieving the closed-loop data processing purpose of collection-processing-feedback-adjustment.

[0164] Example:

[0165] Based on the aforementioned data processing method applied to the base station and the local diversion device, the following is an exemplary introduction to the method for processing camera data, taking the case where the perceived object is a camera as an example.

[0166] like Figure 6 As shown, the camera data processing method may include steps S301-S315:

[0167] S301, the base station starts a sensing function and a local traffic diversion function;

[0168] S302, the base station sends a perception request notification to the camera;

[0169] S303, the camera takes action according to the perception request notification and generates camera data;

[0170] S304, the camera uploads camera data;

[0171] S305, the base station receives uplink data;

[0172] S306, obtaining the service type of the uplink data, and classifying the uplink data according to the service type;

[0173] S307, determining that the service type of the camera data is a monitoring service, and dividing the camera data into sensed object data;

[0174] S308, preliminarily screening the camera data according to data accuracy and whether it is encrypted;

[0175] S309, discarding data whose data accuracy does not meet the preset conditions, sending data whose data accuracy meets the preset conditions and has been encrypted to the core network; sending data whose data accuracy meets the preset conditions but is not encrypted to the local diversion device;

[0176] S310, the local traffic diversion device re-screens the camera data diverted from the base station;

[0177] S311, filtering out the camera data whose target address is inconsistent with the preset address and returning it to the base station, and processing the camera data whose target address is consistent with the preset address and sending it to the second local server;

[0178] S312, the base station sends the returned camera data to the core network;

[0179] S313, the second local server generates perception feedback data according to the received camera data, and sends it to the local diversion device;

[0180] S314: The local offloading device forwards the sensing feedback data to the base station;

[0181] S315. When the perception feedback data is downlink service data or control data, the base station feeds back the perception feedback data to the camera; when the perception feedback data is return data after the second local server encrypts the camera data, the base station sends the perception feedback data to the core network.

[0182] In the above steps, steps S308 and S309 may not be implemented, that is, the base station directly sends the camera data to the local distribution device, and the local distribution device screens the camera data to reduce the computing pressure of the base station. Steps S310 and S311 may not be implemented, that is, the local distribution device directly sends the camera data to the second local server.

[0183] In summary:

[0184] 1. Traffic is diverted through local diversion devices without having to pass through the core network, effectively reducing data transmission volume and alleviating pressure on the core network.

[0185] 2. Traffic is diverted through local diversion devices without a large amount of routing forwarding in the middle, which greatly shortens the physical link, reduces the upstream data flow forwarding delay, and improves data transmission efficiency.

[0186] 3. The data of the sensed object is processed by the local diversion device, saving the computing power of the base station.

[0187] 4. Divert data through local diversion devices without passing through the core network, reducing the possibility of data of the sensed object being exposed on the public network and improving data security.

[0188] 5. The new networking architecture of the disclosed embodiment can transmit the perceived object data to the second local server through local diversion, after which the local diversion device performs encryption, authentication and other operations, and then transmits it to the public network core network, which can add additional security authentication and local cloud storage to improve data security.

[0189] 6. The local diversion device does not need to be connected to the core network. Operators, government and enterprises can sell local diversion services, the local diversion device, and the local diversion device's synaesthesia computing power processing module, expansion module, etc. in a retail manner to improve economic benefits.

[0190] 7. A packaged 2B (business-to-business) charging model can be implemented without the need for traditional traffic billing.

[0191] 8. The resource requirements are lightweight, and there is no need to apply for additional resources, avoiding lengthy approval processes. Local wireless networks can meet the requirements. It supports 5G / 4G / NSA (non-independent networking) / SA (independent networking), wireless local operation and maintenance, wholesale and retail, and is suitable for rapid promotion.

[0192] like Figure 7 As shown, the embodiment of the present disclosure further provides a data processing device 700, which is applied to a base station and may include:

[0193] The first receiving module 701 is used to receive uplink data; the uplink data includes type identification information;

[0194] A classification module 702, configured to classify uplink data according to type identification information;

[0195] The diversion module 703 is used to divert the perceived object data to a preset local diversion device when the uplink data is classified as perceived object data, so as to process the perceived object data through the local diversion device and send the processed perceived object data to the second local server.

[0196] In some embodiments, the communication-aware data processing device further includes: a return data sending module 704;

[0197] After the diversion module 703 diverts the sensed object data to the preset local diversion device, the return data sending module 704 is used to:

[0198] receiving the sensed object data that does not meet the preset requirements and is returned by the local diversion device; the sensed object data that does not meet the preset requirements is detected by the local diversion device before data processing is performed on the sensed object data;

[0199] The sensed object data that does not meet the preset requirements is sent to a preset core network.

[0200] In some embodiments, the communication perception data processing device further includes: a perception feedback data sending module 705;

[0201] After the shunting module 703 shuns the sensed object data to the preset local shunting device, the sensed feedback data sending module 705 is used to:

[0202] Receiving the perception feedback data forwarded by the local distribution device; the perception feedback data is sent by the second local server;

[0203] The perception feedback data is sent to the perceived object corresponding to the perceived object data and / or a preset core network.

[0204] In some embodiments, the communication-aware data processing device further includes: an uplink data sending module 706;

[0205] After the classification module 702 classifies the uplink data according to the type identification information, the uplink data sending module 706 is used to:

[0206] In the case where the uplink data is classified as terminal communication data, the terminal communication data is sent to a preset core network.

[0207] In some embodiments, the communication awareness data processing device further includes: a starting module 707;

[0208] Before the first receiving module receives the uplink data, the starting module 707 is used to start the sensing function and the local offloading function.

[0209] Any embodiment of the aforementioned data processing method applied to a base station is applicable to the data processing device 700 and will not be described in detail herein.

[0210] like Figure 8 As shown, the embodiment of the present disclosure further provides a data processing device 800, which is applied to a local distribution device and may include:

[0211] The second receiving module 801 is used to receive the sensed object data distributed by the base station;

[0212] The processing module 802 is used to process the data of the sensed object;

[0213] The third sending module 803 is used to send the processed perceived object data to the second local server.

[0214] In some embodiments, the processing module 802 performs data processing on the perceived object data, including any one or more of the following: data encoding, data modulation, data calculation, data prediction, and data analysis.

[0215] In some embodiments, the data processing device 800 further includes: a detection module 803;

[0216] Before the processing module processes the perceived object data, the detection module 803 is used to:

[0217] Detect whether the data of the perceived object meets the preset requirements;

[0218] When the data of the sensed object meets the preset requirements, the process of processing the data of the sensed object is started;

[0219] In the case where the sensed object data does not meet the preset requirements, the sensed object data is discarded or returned to the base station, so that the returned sensed object data is sent to a preset core network through the base station.

[0220] In some embodiments, the detection module 803 detects whether the sensed object data meets the preset requirements, including:

[0221] Dividing the sensed object data into multiple groups of sensed object data according to a preset diversion rule; the diversion rule includes: a network slicing rule and / or a public land mobile network PLMN rule;

[0222] Each group of perceived object data is tested separately to see whether it meets the preset requirements.

[0223] In some embodiments, the detection module 803 returns the sensed object data to the base station when the sensed object data does not meet the preset requirements, including: returning one or more groups of sensed object data that do not meet the preset requirements to the base station.

[0224] In some embodiments, the data processing device 800 further includes: a forwarding module 804; after the third sending module 803 sends the processed perceived object data to the second local server, the forwarding module 804 is used to:

[0225] Receiving the perception feedback data returned by the second local server;

[0226] The sensing feedback data is forwarded to the base station, so that the base station sends it to the sensed object corresponding to the sensed object data and / or a preset core network.

[0227] Any of the aforementioned embodiments of the data processing method applied to the local distribution device is applicable to the embodiment of the data processing device 800 and will not be described in detail here.

[0228] like Fig. 9 As shown, the embodiment of the present disclosure further provides a data processing device 900, which is applied to a base station. The data processing device 900 includes a first memory 901 and a first processor 902. The first memory 901 stores a first computer program that can be executed by the first processor 902. When the first computer program is executed by the first processor 902, a data processing method applied to the base station is implemented. The data processing device 900 may also include: one or more first I / O (input / output) interfaces 903, connected between the first processor 902 and the first memory 901.

[0229] like Fig.10As shown, the embodiment of the present disclosure further provides a data processing device 1000, which is applied to a local distribution device. The data processing device 1000 includes a second memory 1001 and a second processor 1002. The second memory 1001 stores a second computer program that can be executed by the second processor 1002. When the second computer program is executed by the second processor 1002, a data processing method applied to the local distribution device is implemented. The data processing device 1000 may also include: one or more second I / O (input / output) interfaces 1003, connected between the second processor 1002 and the second memory 1001.

[0230] Among them, the first processor and the second processor are both devices with data processing capabilities, including but not limited to a central processing unit (CPU), etc.; the first memory and the second memory are both devices with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory (FLASH); the I / O interface (read-write interface) is connected between the processor and the memory (for example, the first I / O interface is connected between the first processor and the first memory, and the second I / O interface is connected between the second processor and the second memory), which can realize information interaction between the memory and the processor, including but not limited to a data bus (Bus), etc.

[0231] The embodiment of the present disclosure also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the communication perception data processing method is implemented.

[0232] Those skilled in the art will appreciate that all or some of the steps, systems, and functional modules / units in the apparatus disclosed above may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0233] In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation.

[0234] Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit (CPU), a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-temporary medium) and a communication medium (or temporary medium). As known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory (FLASH) or other disk storage; read-only compact disk (CD-ROM), digital versatile disk (DVD) or other optical disk storage; magnetic cassettes, magnetic tapes, disk storage or other magnetic storage; any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0235] The present disclosure has disclosed example embodiments, and although specific terms are employed, they are used and should be interpreted only in a general illustrative sense and not for limiting purposes. In some instances, it will be apparent to those skilled in the art that, unless otherwise expressly stated, features, characteristics, and / or elements described in conjunction with a particular embodiment may be used alone or in combination with features, characteristics, and / or elements described in conjunction with other embodiments. Therefore, those skilled in the art will appreciate that various changes in form and detail may be made without departing from the scope of the present disclosure as set forth in the appended claims.

Claims

1. A data processing method, characterized in that: Applied to a base station, the method comprises: Receiving uplink data; the uplink data including type identification information; Classifying the uplink data according to the type identification information; In the case where the uplink data is classified as perceived object data, the perceived object data is diverted to a preset local diversion device, so that the perceived object data is processed by the local diversion device, and the processed perceived object data is sent to a second local server.

2. The data processing method according to claim 1, characterized in that: After the sensed object data is diverted to a preset local diversion device, the method further includes: receiving the sensed object data that does not meet the preset requirements and is returned by the local diversion device; the sensed object data that does not meet the preset requirements is detected before the local diversion device performs data processing on the sensed object data; The sensed object data that does not meet the preset requirements is sent to a preset core network.

3. The data processing method according to claim 2, characterized in that: The preset requirements include any one or more of the following: The data accuracy of the sensed object data is greater than or equal to a preset accuracy threshold; The sensed object data is unencrypted data; The identity identifier of the sensed object data is consistent with the preset identity identifier; The target address of the sensed object data is consistent with the preset address; as well as, The business type of the sensed object data is consistent with the preset business type.

4. The data processing method according to claim 1, characterized in that: After the sensed object data is diverted to a preset local diversion device, the method further includes: receiving the perception feedback data forwarded by the local traffic distribution device; the perception feedback data is sent by the second local server; The perception feedback data is sent to the perceived object corresponding to the perceived object data and / or a preset core network.

5. The data processing method according to claim 4, characterized in that: The perception feedback data includes any one or more of the following: data processed by the second local server on the sensed object data; control data on the sensed object sent by the second local server, and The downlink service data sent by the second local server.

6. The data processing method according to claim 1, characterized in that: After classifying the uplink data according to the type identification information, the method further includes: In a case where the uplink data is classified as terminal communication data, the terminal communication data is sent to a preset core network.

7. A data processing method, characterized in that: Applied to a local shunt device, the method comprises: Receiving the sensed object data diverted from the base station; Performing data processing on the sensed object data; The processed data of the sensed object is sent to the second local server.

8. The data processing method according to claim 7, characterized in that: Before processing the perceived object data, the method further includes: Detecting whether the perceived object data meets preset requirements; When the sensed object data meets the preset requirements, a process of processing the sensed object data is entered; In the case that the sensed object data does not meet the preset requirement, the sensed object data is discarded or returned to the base station, so that the returned sensed object data is sent to a preset core network through the base station.

9. The data processing method according to claim 8, characterized in that: The detecting whether the sensed object data meets preset requirements includes: Dividing the sensed object data into multiple groups of sensed object data according to a preset diversion rule; the diversion rule includes: a network slicing rule and / or a public land mobile network PLMN rule; Each group of the sensed object data is detected separately to see whether it meets the preset requirements.

10. The data processing method according to claim 9, characterized in that: When the sensed object data does not meet the preset requirement, returning the sensed object data to the base station includes: returning one or more groups of the sensed object data that do not meet the preset requirement to the base station.

11. The data processing method according to claim 7, characterized in that: After sending the processed data of the sensed object to the second local server, the method further includes: Receiving the perception feedback data returned by the second local server; The perception feedback data is forwarded to a base station, so that the base station sends it to a perceived object corresponding to the perceived object data and / or a preset core network.

12. A data processing device, characterized in that: Applied to a base station, comprising: a first memory and a first processor; the first memory stores a first computer program that can be executed by the first processor, and when the first computer program is executed by the first processor, the data processing method as described in any one of claims 1-6 is implemented.

13. A data processing device, characterized in that: Applied to a local diversion device, comprising: a second memory and a second processor; the second memory stores a second computer program that can be executed by the second processor, and when the second computer program is executed by the second processor, it implements the data processing method as described in any one of claims 7-11.

14. A networking architecture, characterized in that: include: A local distribution device and at least one base station; the local distribution device comprises the data processing device according to claim 13, and the base station comprises the data processing device according to claim 12; One or more of the at least one base station communicates with the sensed object; The data processing device in the local distribution device is connected to the data processing device in each base station and is connected to the second local server.

15. The networking architecture according to claim 14, characterized in that: Also includes: Core network and packet data network; Each base station is respectively connected to the core network corresponding to itself; The core network is connected to the corresponding packet data network; The packet data network is connected to a third local server.

16. The networking architecture according to claim 14, characterized in that: The local traffic distribution device further includes: a base station frame backplane connection interface, an expansion module and / or a third-party interface; The base station frame backplane connection interface is used to connect to the base station frame backplane; The expansion module is used to expand functions; The third-party interface is used to connect to a third-party device.

17. The networking architecture according to claim 14, characterized in that: The local traffic distribution device is deployed separately or together with the base station.

18. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program implements the data processing method according to any one of claims 1 to 6 or claims 7 to 11.

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