CN117914829A - Intelligent agent fusion communication architecture and method based on neural network model - Google Patents
Intelligent agent fusion communication architecture and method based on neural network model Download PDFInfo
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Abstract
The invention discloses an intelligent agent fusion communication architecture and method based on a neural network model. The scheme of the invention comprises at least one intelligent agent unit for converting audio and video data, a converged communication switching center unit and at least one intelligent terminal unit, wherein the converged communication switching center unit and the at least one intelligent terminal unit are respectively communicated with the intelligent agent unit; the intelligent agent converged communication architecture adopts a distributed intelligent agent cluster to realize group call control, learns link quality control through an intelligent agent neural network model, and a method and a platform corresponding to the architecture, introduces artificial intelligence and a blockchain into the IMS converged communication architecture, solves the problem that multi-protocol converged exchange communication of different systems and types is accessed in a complex environment of a large-scale terminal, forms uninterrupted transmission capacity of various links, and supports safe, reliable and high-quality communication transmission of various business application data such as voice, video, conferences and the like.
Description
Technical Field
The invention belongs to the technical field of communication processing, and particularly relates to an intelligent agent fusion communication architecture and method based on a neural network model.
Background
The IMS is a network architecture for realizing a large convergence scheme of a next generation communication network (NGN), can realize VoIP service, more effectively manage network resources, user resources and application resources, improve the intelligence of the network, enable users to cross various networks and use various terminals, and feel converged communication experience.
The traditional telecommunication network adopts an independent signaling network to complete the processes of call establishment, routing, control and the like, and the security of the signaling network can ensure the security of the network. And the transmission adopts a special line of Time Division Multiplexing (TDM), and the users communicate by adopting a connection-oriented channel, so that various eavesdropping and attacks from other terminal users are avoided. The IMS network is connected with the Internet, and based on an IP protocol and an open network architecture, various services such as voice, data, multimedia and the like can be shared by adopting various different access modes, so that the flexibility of the network and the interoperability among terminals are improved, and different operators can effectively and rapidly develop and provide various services.
Since IMS is based on IP, the security requirements of IMS are much higher than conventional operators operating on a separate network, whether by mobile or fixed access, the security issues of IMS are not negligible. The security threat of IMS comes mainly from several aspects: unauthorized access to sensitive data to break confidentiality; unauthorized tampering with the sensitive data to break integrity; interference or abuse of network traffic results in denial of service or reduced system availability; the user or the network denies the completed operation; unauthorized access to services, etc. Mainly related to IMS access security (3 GPP TS 33.203), including user and network authentication and protection of services between IMS terminals and networks; and network security of IMS (3 gpp ts 33.210), handling traffic protection between network nodes belonging to the same operator or different operators. In addition, the security of the user terminal equipment and universal integrated circuit card/IP multimedia service identity module (UICC/ISIM) is threatened.
Therefore, aiming at the technical defects, there is an urgent need to design and develop an intelligent agent fusion communication architecture and method based on a neural network model.
Disclosure of Invention
In order to overcome the defects and difficulties in the prior art, the invention aims to provide an intelligent agent fusion communication architecture and method based on a neural network model, and introduce artificial intelligence and blockchain into an IMS fusion communication architecture, thereby solving the problem of accessing multi-protocol fusion exchange communication of different systems and types under a complex environment of a large-scale terminal, forming uninterrupted transmission capability of various links, and supporting safe, reliable and high-quality communication transmission of various business application data such as voice, video, conference and the like.
The first object of the present invention is to provide an intelligent agent fusion communication architecture based on a neural network model;
the second object of the invention is to provide an intelligent agent fusion communication method based on a neural network model;
the third object of the invention is to provide an intelligent agent fusion communication platform based on a neural network model;
The first object of the present invention is achieved by: the intelligent agent converged communication architecture comprises at least one intelligent agent unit for converting audio and video data, a converged communication switching center unit and at least one intelligent terminal unit, wherein the converged communication switching center unit and the at least one intelligent terminal unit are respectively communicated with the intelligent agent unit;
The intelligent agent converged communication architecture adopts a distributed intelligent agent cluster to realize group call control, and learns link quality control through an intelligent agent neural network model.
Further, the converged communication switching center unit broadcasts data transmission in a network transmission layer in a TCP, UDP unicast or multicast mode.
Furthermore, the intelligent agent fusion communication architecture is also provided with a synchronous processing unit, and the synchronous processing unit is used for synchronously coordinating the clusters and synchronously collecting, transmitting and playing voice video data streams respectively.
Further, the intelligent agent fusion communication architecture is further provided with a first creation unit, and the first creation module is used for building a multi-intelligent agent network pinning consistency model of the distributed intelligent agents.
Further, the first creation unit further includes:
The generation and acquisition module is used for generating an intelligent agent and acquiring a connection address corresponding to MECS (multiple Access edge computing Server);
the first calculation module is used for calculating delay data to the intelligent agent in the fully-connected network;
The self-checking generating module is used for checking whether the self group calling state reaches stability or not and generating action control instruction data corresponding to the stability or the instability, wherein the action control comprises the following steps: control is established, collection control, transmission control, play control and termination control.
The second object of the present invention is achieved by: the method comprises the following steps:
respectively acquiring audio and video data corresponding to the intelligent terminal, and forwarding the audio and video data in real time by combining an intelligent agent;
And according to the data which is forwarded and processed by the intelligent agent, broadcasting data transmission at a network transmission layer by integrating a communication switching center cluster and adopting a TCP (transmission control protocol), UDP (user datagram protocol) unicast or multicast mode.
Further, the steps of respectively obtaining the audio and video data corresponding to the intelligent terminal, and forwarding the audio and video data in real time by combining with the intelligent agent, and further include:
Acquiring first synchronous control data corresponding to trunked group call communication; the first synchronous control data are consistent synchronous control data among distributed intelligent agents;
and establishing a multi-intelligent agent network pinning consistency model of the distributed intelligent agents according to the first synchronous control data.
Further, the establishing a multi-intelligent agent network pinning consistency model of the distributed intelligent agents according to the first synchronous control data further comprises:
Generating an intelligent agent, acquiring a connection address corresponding to the MECS, establishing an intelligent agent TCP connection corresponding to the MECS, and simultaneously establishing a fully-connected multi-intelligent agent network;
Calculating and generating shortest time delay data to other intelligent agents in the fully connected network according to a shortest path algorithm;
the method comprises the steps of sending a self group calling state through an intelligent agent, receiving the group calling state sent by all neighbors, and updating the group calling state in real time according to a self dynamics equation;
Checking whether the group calling state of the intelligent agent reaches stability or not, and generating action control instruction data corresponding to the stability or instability; wherein the motion control includes: control is established, collection control, transmission control, play control and termination control.
The third object of the present invention is achieved by: the intelligent agent fusion communication platform control program based on the neural network model comprises a processor, a memory and an intelligent agent fusion communication platform control program based on the neural network model; the processor executes the intelligent agent fusion communication platform control program based on the neural network model, the intelligent agent fusion communication platform control program based on the neural network model is stored in the memory, and the intelligent agent fusion communication platform control program based on the neural network model realizes the intelligent agent fusion communication method based on the neural network model.
The intelligent agent converged communication architecture comprises at least one intelligent agent unit for converting audio and video data, and a converged communication switching center unit and at least one intelligent terminal unit which are respectively communicated with the intelligent agent unit; the intelligent agent converged communication architecture adopts a distributed intelligent agent cluster to realize group call control, learns link quality control through an intelligent agent neural network model, and a method and a platform corresponding to the architecture, introduces artificial intelligence and a blockchain into the IMS converged communication architecture, solves the problem that multi-protocol converged exchange communication of different systems and types is accessed in a complex environment of a large-scale terminal, forms uninterrupted transmission capacity of various links, and supports safe, reliable and high-quality communication transmission of various business application data such as voice, video, conferences and the like.
That is, the scheme of the invention provides guarantee for high-quality communication of audio and video through self-adaptive learning link quality control of the intelligent agent neural network model; each intelligent terminal is responsible for interaction by an intelligent agent, and the converged communication switching center only needs to communicate with the intelligent agent, so that the reliability of large-scale broadcast communication is improved; the intelligent agent and the converged communication switching center uniformly use the SIP protocol, so that the butt joint among various protocols of the converged communication switching center is reduced; the intelligent agent is used as UA to be integrated into advanced IMS architecture, which can obtain the needed service quality and better support the services of registration, security, charging, bearing control, roaming and the like in the integrated communication. The intelligent agent is used as a blockchain node, and authentication protection, authorization and encryption are performed based on the blockchain, so that the safety of the system is ensured, and the threat of theft, tampering and the like is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an embodiment of an intelligent agent fusion communication architecture based on a neural network model;
FIG. 2-a is a schematic diagram of a second flow chart of an embodiment of an intelligent agent fusion communication architecture based on a neural network model according to the present invention;
FIG. 2-b is a schematic diagram illustrating a third flow chart of an embodiment of an intelligent agent fusion communication architecture based on a neural network model according to the present invention;
FIG. 3 is a schematic diagram of an intelligent agent converged communication architecture based on a neural network model;
FIG. 4 is a schematic flow chart of an intelligent agent fusion communication method based on a neural network model;
FIG. 5 is a schematic diagram of an intelligent agent converged communication platform based on a neural network model;
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
For a better understanding of the present invention, its objects, technical solutions and advantages, further description of the present invention will be made with reference to the drawings and detailed description, and further advantages and effects will be readily apparent to those skilled in the art from the present disclosure.
The invention may be practiced or carried out in other embodiments and details within the scope and range of equivalents of the various features and advantages of the invention.
It should be noted that, if directional indications (such as up, down, left, right, front, and rear … …) are included in the embodiments of the present invention, the directional indications are merely used to explain the relative positional relationship, movement conditions, etc. between the components in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indications are correspondingly changed.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present invention, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. Secondly, the technical solutions of the embodiments may be combined with each other, but it is necessary to be based on the fact that those skilled in the art can realize the technical solutions, and when the technical solutions are contradictory or cannot be realized, the technical solutions are considered to be absent and are not within the scope of protection claimed in the present invention.
Preferably, the intelligent agent fusion communication method based on the neural network model is applied to one or more terminals or servers. The terminal is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and its hardware includes, but is not limited to, a microprocessor, an Application SPECIFIC INTEGRATED Circuit (ASIC), a Programmable gate array (Field-Programmable GATE ARRAY, FPGA), a digital Processor (DIGITAL SIGNAL Processor, DSP), an embedded device, and the like.
The terminal can be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server and the like. The terminal can perform man-machine interaction with a client through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.
The invention discloses an intelligent agent fusion communication architecture, method and platform based on a neural network model.
Fig. 4 is a flowchart of an intelligent agent fusion communication method based on a neural network model according to an embodiment of the present invention.
In this embodiment, the intelligent agent fusion communication method based on the neural network model may be applied to a terminal or a fixed terminal with a display function, where the terminal is not limited to a personal computer, a smart phone, a tablet computer, a desktop computer or an all-in-one machine with a camera, and the like.
The intelligent agent fusion communication method based on the neural network model can also be applied to a hardware environment formed by a terminal and a server connected with the terminal through a network. Networks include, but are not limited to: a wide area network, a metropolitan area network, or a local area network. The intelligent agent fusion communication method based on the neural network model can be executed by a server, a terminal or both.
For example, for an intelligent agent fusion communication terminal that needs to perform a neural network model, the intelligent agent fusion communication function based on the neural network model provided by the method of the present invention may be directly integrated on the terminal, or a client for implementing the method of the present invention may be installed. For another example, the method provided by the invention can also be operated on devices such as a server in the form of a software development kit (Software Development Kit, SDK), an interface of the intelligent agent fusion communication function based on the neural network model is provided in the form of the SDK, and the terminal or other devices can realize the intelligent agent fusion communication function based on the neural network model through the provided interface.
The invention is further elucidated below in connection with the accompanying drawings.
As shown in fig. 1-5, the present invention provides an intelligent agent fusion communication architecture based on a neural network model,
The intelligent agent converged communication architecture comprises at least one intelligent agent unit for converting audio and video data, a converged communication switching center unit and at least one intelligent terminal unit, wherein the converged communication switching center unit and the at least one intelligent terminal unit are respectively communicated with the intelligent agent unit;
The intelligent agent converged communication architecture adopts a distributed intelligent agent cluster to realize group call control, and learns link quality control through an intelligent agent neural network model.
The converged communication switching center unit broadcasts data transmission in a network transmission layer in a TCP, UDP unicast or multicast mode.
The intelligent agent fusion communication architecture is also provided with a synchronous processing unit, and the synchronous processing unit is used for synchronously coordinating the clusters and synchronously collecting, transmitting and playing voice video data streams respectively.
The intelligent agent fusion communication architecture is further provided with a first creation unit, and the first creation module is used for building a multi-intelligent agent network pinning consistency model of the distributed intelligent agents.
The first creation unit further includes:
The generation and acquisition module is used for generating an intelligent agent and acquiring a connection address corresponding to the MECS;
the first calculation module is used for calculating delay data to the intelligent agent in the fully-connected network;
The self-checking generating module is used for checking whether the self group calling state reaches stability or not and generating action control instruction data corresponding to the stability or the instability, wherein the action control comprises the following steps: control is established, collection control, transmission control, play control and termination control.
Specifically, in the embodiment of the invention, the link quality control is learned through the intelligent agent neural network model, the complex transmission time sequence problem is solved based on the modes of reliable retransmission, forward correction (FEC), service priority, end-to-end speed control and the like, the stability of the transmission link is ensured, the delay is reduced, the central bottleneck is eliminated, the network cost is reduced, and the guarantee is provided for high-quality audio and video communication; as shown in fig. 2-a.
As shown in fig. 1, each intelligent terminal is responsible for interaction by an intelligent agent, all audio and video data are converted by the intelligent agent, the converged communication switching center only needs to communicate with the intelligent agent, and a TCP (transmission control protocol) and UDP (user datagram protocol) unicast or multicast mode can be used for accelerating broadcast data transmission at a network transmission layer, so that the reliability of large-scale broadcast communication is improved;
In the aspect of coordination, according to the cluster communication characteristics, the group calling is a key service, in the traditional cluster system, the group calling control is realized through a central centralized control terminal, the invention is realized by adopting a distributed intelligent agent cluster, and the cluster is required to be synchronously coordinated, so that synchronous acquisition, transmission and playing of voice and video data streams are ensured.
The distributed cooperative control comprises a distributed coordination technology and a consistency synchronous control technology, and the distributed coordination technology can be realized by adopting a mature Zookeeper component. The Zookeeper is a distributed coordination service for managing a large number of hosts, has the characteristics of reliability, expandability, transparency and the like, and can provide services such as naming service, load balancing, configuration management, cluster management, node leader election, distributed queues, distributed locks, data registry and the like required by coordination among distributed intelligent agents.
Aiming at the consistency synchronous control requirement among distributed intelligent agents of cluster group call communication, the states among the intelligent agents and the changes thereof need to be consistent, which has high similarity with a multi-intelligent agent network system, and can be solved by establishing a multi-intelligent agent network hold-down consistency model of the distributed intelligent agents.
Considering a network comprising N nodes, a node is represented as a first order N-dimensional dynamics system, the nodes are coupled by interaction state information, and the dynamics of the i-th node in the network can be described as the following equation:
Where x i(t)∈Rn, c is the coupling strength, Γ is the internal coupling matrix, a ij is the adjacency matrix, u i(t)∈Rn is the linear feedback controller, d i τ (t) is the controller gain, s τ (t) is the desired system equilibrium state, τ is the desired equilibrium state change time.
When (when)In this case, the network system can achieve consistent drag through the feedback control input u i (t), L is Lapacian matrix of the system, and d=diag (D 1,…,dN),di is the control gain of node i).
When the system reaches consistency equilibrium, x r(t)→sτ(t),xi(t)→xr (t), and thus x i(t)→sτ (t), the system consistently reaches s τ (t) state, thus changing the state of the pinned node s τ (t) will cause all nodes of the network to change state consistently and synchronously.
According to a multi-intelligent agent network consistency model, the following intelligent agent-to-intelligent agent consistency synchronous control algorithm is proposed:
1. And in the initialization state, generating an intelligent agent in the MECS, communicating with the center, acquiring connection addresses of other MECS, establishing TCP connection with the intelligent agents in other MECS in the network by the intelligent agent as connection of the intelligent agent, forming a full-connection multi-intelligent agent network, and interactively acquiring communication delay T ij of the connection with all the multi-intelligent agents through the TCP connection.
2. According to Dijkstra (Dikkstra) shortest path algorithm, the intelligent agent calculates the shortest time delay to other intelligent agents in the fully connected network, reserves neighbor connection with the shortest time delay, and takes the communication time delay T ij as a ij to form an adjacency list.
3. Through reserved TCP connection with neighbors, intelligent agent i sends own group call state x i (t) to all neighbor intelligent agents, and receives group call state x j (t) sent by all neighbors j not equal i.
4. The intelligent agent i updates the group call state x i (t) according to its own dynamics equation (1). The control gain d of the intelligent agent r can be set to be 1, the intelligent agent r adjusts the network consistency by changing s τ (t) according to the group call state, and the loop state change of acquisition, transmission and playing is automatically carried out at the time interval tau until the group call state is terminated after the group call state is established.
5. The intelligent agent i checks whether the self group calling state reaches stability (meeting the requirements of II x i(t+Δτ)-xi (t) II </epsilon), and if so, corresponding actions (building, collecting, transmitting, playing, terminating and the like) are executed.
6. Step3 is repeated at time intervals T.
Through the cooperative control algorithm, when a plurality of intelligent agent networks reach consistency, and the dynamics update clock T and the longest time delay of the networks are far smaller than the state change time tau, the intelligent agent can ensure that the state change is consistent with the whole network only by updating the state through the neighbor change, and a center does not need to be fixed for coordination. When the planning state is used as the sampling and output control state of voice, a consistent synchronous acquisition, distribution and play network can be formed, and the group calling function is realized.
As shown in fig. 1, the intelligent agent and the converged communication switching center uniformly use the SIP protocol, and exchange audio, video, data and messages based on the same communication system, so as to reduce the interfacing among multiple protocols of the converged communication switching center;
The intelligent agent is integrated into an advanced IMS architecture as UA, so that various types of terminals can establish peer-to-peer IP communication, obtain required service quality, and complete functions necessary for service, such as registration, security, charging, bearing control, roaming and the like.
The intelligent agent is used as a blockchain node, performs authentication protection and authorization functions based on the blockchain, stores all authentication security information in a uplink manner, limits access of illegal users, ensures the security of a system, ensures the confidentiality of conversation through a digital encryption technology, and protects against threats such as theft, tampering and the like.
Intelligent agents are an important concept in the fields of computer science and artificial intelligence in recent years, which refers to computing entities that reside in a particular environment, are capable of sensing the environment, and are capable of autonomous operation to achieve a set of goals on behalf of their designer or user. Intelligent agents can simulate human social behavior, i.e., have intelligence, after training based on knowledge base by sensing, learning, reasoning, and actions. Has the following key attributes: autonomy: the intelligent agent can control state and behavior by itself, and can operate and run without human intervention or other programs. Sensing capability and reaction capability: the intelligent agent is able to timely sense and respond to changes in the environment in which it is located. Motility: the intelligent agent can actively show the target-driven behavior, and can automatically select proper time to take proper action. Communication capability: intelligent agents are able to exchange information and interact with other entities in some way of communication. Persistence: intelligent agents are continuous or continuously running processes, the state of which should be consistent throughout the process. Reasoning and planning capabilities: intelligent agents have the ability to make relevant inferences and intelligent calculations based on learning knowledge and experience.
The block chain technology is a brand new distributed infrastructure and calculation paradigm for verifying and storing data by using a block chain data structure, generating and updating the data by using a distributed node consensus algorithm, ensuring the safety of data transmission and access by using a cryptography mode, and programming and operating the data by using an intelligent contract consisting of an automatic script code. Has the following characteristics: decentralizing: the blockchain technology does not depend on an additional third party management mechanism or hardware facility, is not controlled by a center, and except for the self-integrated blockchain, each node realizes information self-verification, transmission and management through distributed accounting and storage, and the decentralization is the most prominent and essential characteristic of the blockchain; patency: the blockchain technology foundation is open-source, except that private information of each transaction party is encrypted, the blockchain data is open to all people, and anyone can inquire the blockchain data and develop related applications through a public interface, so that the whole system information is highly transparent; independence: based on agreed specifications and protocols (such as various mathematical algorithms such as hash algorithm) the whole blockchain system does not depend on other third parties, and all nodes can automatically and safely verify and exchange data in the system without any human intervention; safety: as long as 51% of all data nodes cannot be mastered, network data cannot be mastered and modified wantonly, so that the blockchain becomes relatively safe, and subjective artificial data change is avoided; anonymity: unless required by legal regulations, identity information of each block node is not required to be disclosed or verified in terms of technology alone, and information transmission can be performed anonymously.
In order to achieve the above objective, the present invention further provides an intelligent agent fusion communication method based on a neural network model, as shown in fig. 4, the method includes the following steps:
S1, respectively acquiring audio and video data corresponding to an intelligent terminal, and forwarding the audio and video data in real time by combining an intelligent agent;
s2, forwarding the processed data according to the intelligent agent, and broadcasting data transmission in a network transmission layer by fusing a communication switching center cluster and adopting a TCP (transmission control protocol) and UDP (user datagram protocol) unicast or multicast mode.
The method comprises the steps of respectively acquiring audio and video data corresponding to the intelligent terminal, forwarding the audio and video data in real time by combining an intelligent agent, and further comprising the following steps:
S11, acquiring first synchronous control data corresponding to trunked group call communication; the first synchronous control data are consistent synchronous control data among distributed intelligent agents;
And S12, establishing a multi-intelligent agent network drag consistency model of the distributed intelligent agents according to the first synchronous control data.
The establishing a multi-intelligent agent network drag consistency model of the distributed intelligent agents according to the first synchronous control data further comprises:
S121, generating an intelligent agent, acquiring a connection address corresponding to the MECS, establishing an intelligent agent TCP connection corresponding to the MECS, and simultaneously establishing a fully-connected multi-intelligent agent network;
s122, calculating and generating shortest time delay data to other intelligent agents in the fully-connected network according to a shortest path algorithm;
s123, sending a self group calling state through an intelligent agent, receiving the group calling states sent by all neighbors, and updating the group calling states in real time according to a self dynamics equation;
S124, checking whether the group calling state of the intelligent agent reaches stability or not, and generating action control instruction data corresponding to the stability or the instability; wherein the motion control includes: control is established, collection control, transmission control, play control and termination control.
That is, in the scheme of the invention, the intelligent agent fusion communication method based on the neural network model comprises the following specific steps:
S00, the intelligent terminal is connected to an intelligent agent, the intelligent agent is used as a blockchain participating node to carry out identity authentication by using a regional chain network, if the authentication is passed, the connection is kept for continuing the session, otherwise, the connection is disconnected for ending the session; s01, after the intelligent terminal passes authentication, sending audio and video time sequence data to an intelligent agent when calling is needed, wherein the intelligent agent firstly receives the audio and video time sequence data and puts the audio and video time sequence data into a receiving queue, inputs the audio and video time sequence data into a link neural network model to respectively carry out link quality evaluation, forward correction and end-to-end speed control, outputs next-level priority and retransmission control processing, and puts the audio and video data into corresponding sending queue cache by combining reliable retransmission and service priority, and then forwards the audio and video data in real time to be sent to a converged communication switching center cluster;
As shown in fig. 2-b, the link quality evaluation is performed based on GNN graph neural network, the forward correction is completed based on LSTM long-term memory network, and the end-to-end rate control is realized based on DNN deep neural network; when a plurality of intelligent agent audio and video time sequence data are input into the GNN, the GNN comprehensively evaluates and forms the link quality of each intelligent terminal, LSTM synchronously converts the audio and video time sequence data and carries out forward prediction error correction, the GNN evaluation result and the LSTM corrected audio and video data are input into the DNN, the DNN carries out self-adaptive rate adjustment of a plurality of terminals, the overall coordination ensures the audio and video transmission quality, and the audio and video data are output to the next stage for retransmission and priority control.
S02, according to the data after the intelligent agent forwarding processing, the mixed gating or forwarding distribution is carried out through the converged communication switching center cluster, and the data transmission is broadcasted at a network transmission layer by adopting a TCP, UDP unicast or multicast mode.
The method comprises the steps of respectively acquiring audio and video data corresponding to the intelligent terminal, forwarding the audio and video data in real time by combining an intelligent agent, and further comprising the following steps:
S011, acquiring first synchronous control data corresponding to trunked group call communication; the first synchronous control data are consistent synchronous control data among distributed intelligent agents;
s012, establishing a multi-intelligent agent network drag consistency model of the distributed intelligent agents according to the first synchronous control data.
The establishing a multi-intelligent agent network drag consistency model of the distributed intelligent agents according to the first synchronous control data further comprises:
s0121, generating an intelligent agent, acquiring a connection address corresponding to the MECS, establishing an intelligent agent TCP connection corresponding to the MECS, and simultaneously establishing a fully-connected multi-intelligent agent network;
S0122, calculating and generating shortest time delay data to other intelligent agents in the fully-connected network according to a shortest path algorithm;
S0123, sending self group calling state through intelligent agent, receiving group calling state sent by all neighbors, and updating group calling state in real time according to self dynamics equation;
s0124, checking whether the group calling state of the intelligent agent reaches stability or not, and generating action control instruction data corresponding to the stability or instability; wherein the motion control includes: control is established, collection control, transmission control, play control and termination control.
S03, merging audio and video time sequence data transmitted to the intelligent terminal by the communication switching center cluster, and similarly to S1 processing, firstly receiving and putting the audio and video time sequence data into a receiving queue by the intelligent agent, inputting the audio and video time sequence data into a link neural network model to respectively evaluate link quality, correct forward and control end to end speed, outputting the next-level priority and retransmission control processing, putting the audio and video time sequence data into a corresponding transmission queue for buffering by combining reliable retransmission and service priority, and then forwarding the audio and video data in real time and transmitting the audio and video data to the intelligent terminal.
In the embodiment of the method scheme of the invention, the intelligent agent based on the neural network model fuses the functional modules involved in the communication method, and the specific details are already described above and are not repeated here.
In order to achieve the above objective, the present invention further provides an intelligent agent fusion communication platform based on a neural network model, as shown in fig. 5, including a processor, a memory, and an intelligent agent fusion communication platform control program based on the neural network model; executing the intelligent agent fusion communication platform control program based on the neural network model on the processor, wherein the intelligent agent fusion communication platform control program based on the neural network model is stored in the memory, and the intelligent agent fusion communication platform control program based on the neural network model realizes the intelligent agent fusion communication method steps based on the neural network model, such as:
S1, respectively acquiring audio and video data corresponding to an intelligent terminal, and forwarding the audio and video data in real time by combining an intelligent agent;
s2, forwarding the processed data according to the intelligent agent, and broadcasting data transmission in a network transmission layer by fusing a communication switching center cluster and adopting a TCP (transmission control protocol) and UDP (user datagram protocol) unicast or multicast mode.
The details of the steps are set forth above and are not repeated here.
In the embodiment of the invention, the intelligent agent fusion communication platform built-in processor based on the neural network model can be composed of integrated circuits, for example, can be composed of single packaged integrated circuits, can also be composed of a plurality of integrated circuits packaged with the same function or different functions, and comprises one or a plurality of central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphic processors, various control chips and the like. The processor utilizes various interfaces and line connections to take various components, and executes various functions and processes data by running or executing programs or units stored in the memory and calling data stored in the memory to execute intelligent agent fusion communication based on the neural network model;
The memory is used for storing program codes and various data, is installed in the intelligent agent fusion communication platform based on the neural network model, and realizes high-speed and automatic access of programs or data in the running process.
The memory includes read-only memory (ROM), random-access memory (Random Access Memory, RAM), programmable read-only memory (Programmable Read-only memory, PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (Compact Disc Read-only memory, CD-ROM) or other optical disk memory, magnetic disk memory, tape memory, or any other medium from which a computer can be used to carry or store data.
The intelligent agent converged communication architecture comprises at least one intelligent agent unit for converting audio and video data, and a converged communication switching center unit and at least one intelligent terminal unit which are respectively communicated with the intelligent agent unit; the intelligent agent converged communication architecture adopts a distributed intelligent agent cluster to realize group call control, and learns link quality control through an intelligent agent neural network model; and the method and the platform corresponding to the architecture are used for introducing artificial intelligence and blockchain into the IMS converged communication architecture, solving the problem of accessing multi-protocol converged exchange communication of different systems and types under the complex environment of a large-scale terminal, forming uninterrupted transmission capacity of various links, and supporting safe, reliable and high-quality communication transmission of various business application data such as voice, video, conference and the like.
That is, the scheme of the invention provides guarantee for high-quality communication of audio and video through self-adaptive learning link quality control of the intelligent agent neural network model; each intelligent terminal is responsible for interaction by an intelligent agent, and the converged communication switching center only needs to communicate with the intelligent agent, so that the reliability of large-scale broadcast communication is improved; the intelligent agent and the converged communication switching center uniformly use the SIP protocol, so that the butt joint among various protocols of the converged communication switching center is reduced; the intelligent agent is used as UA to be integrated into advanced IMS architecture, which can obtain the needed service quality and better support the services of registration, security, charging, bearing control, roaming and the like in the integrated communication. The intelligent agent is used as a blockchain node, and authentication protection, authorization and encryption are performed based on the blockchain, so that the safety of the system is ensured, and the threat of theft, tampering and the like is avoided.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (9)
1. The intelligent agent converged communication architecture based on the neural network model is characterized by comprising at least one intelligent agent unit for converting audio and video data, a converged communication switching center unit and at least one intelligent terminal unit, wherein the converged communication switching center unit and the at least one intelligent terminal unit are respectively communicated with the intelligent agent unit;
The intelligent agent converged communication architecture adopts a distributed intelligent agent cluster to realize group call control, and learns link quality control through an intelligent agent neural network model.
2. The intelligent agent converged communication infrastructure based on the neural network model of claim 1, wherein the converged communication switching center unit broadcasts data transmission at a network transport layer by means of TCP, UDP unicast or multicast.
3. The intelligent agent fusion communication architecture based on the neural network model according to claim 1 or 2, wherein the intelligent agent fusion communication architecture is further provided with a synchronization processing unit, and the synchronization processing unit is used for synchronously coordinating the clusters and synchronously collecting, transmitting and playing voice video data streams respectively.
4. The intelligent agent fusion communication architecture based on the neural network model according to claim 3, wherein the intelligent agent fusion communication architecture is further provided with a first creation unit, and the first creation module is used for building a multi-intelligent agent network pinning consistency model of the distributed intelligent agents.
5. The intelligent agent fusion communication architecture based on a neural network model of claim 4, wherein the first creation unit further comprises:
The generation and acquisition module is used for generating an intelligent agent and acquiring a connection address corresponding to the MECS;
the first calculation module is used for calculating delay data to the intelligent agent in the fully-connected network;
The self-checking generating module is used for checking whether the self group calling state reaches stability or not and generating action control instruction data corresponding to the stability or the instability, wherein the action control comprises the following steps: control is established, collection control, transmission control, play control and termination control.
6. An intelligent agent fusion communication method based on a neural network model is characterized by comprising the following steps:
respectively acquiring audio and video data corresponding to the intelligent terminal, and forwarding the audio and video data in real time by combining an intelligent agent;
And according to the data which is forwarded and processed by the intelligent agent, broadcasting data transmission at a network transmission layer by integrating a communication switching center cluster and adopting a TCP (transmission control protocol), UDP (user datagram protocol) unicast or multicast mode.
7. The intelligent agent fusion communication method based on the neural network model according to claim 6, wherein the steps of respectively acquiring audio and video data corresponding to the intelligent terminal, and forwarding the audio and video data in real time by combining the intelligent agent are further performed, and the method further comprises:
Acquiring first synchronous control data corresponding to trunked group call communication; the first synchronous control data are consistent synchronous control data among distributed intelligent agents;
and establishing a multi-intelligent agent network pinning consistency model of the distributed intelligent agents according to the first synchronous control data.
8. The intelligent agent fusion communication method based on the neural network model of claim 7, wherein the establishing a multi-intelligent agent network pinning consistency model of the distributed intelligent agents according to the first synchronization control data further comprises:
Generating an intelligent agent, acquiring a connection address corresponding to the MECS, establishing an intelligent agent TCP connection corresponding to the MECS, and simultaneously establishing a fully-connected multi-intelligent agent network;
Calculating and generating shortest time delay data to other intelligent agents in the fully connected network according to a shortest path algorithm;
the method comprises the steps of sending a self group calling state through an intelligent agent, receiving the group calling state sent by all neighbors, and updating the group calling state in real time according to a self dynamics equation;
Checking whether the group calling state of the intelligent agent reaches stability or not, and generating action control instruction data corresponding to the stability or instability; wherein the motion control includes: control is established, collection control, transmission control, play control and termination control.
9. The intelligent agent fusion communication platform based on the neural network model is characterized by comprising a processor, a memory and an intelligent agent fusion communication platform control program based on the neural network model; the processor executes the intelligent agent fusion communication platform control program based on the neural network model, the intelligent agent fusion communication platform control program based on the neural network model is stored in the memory, and the intelligent agent fusion communication platform control program based on the neural network model realizes the intelligent agent fusion communication method based on the neural network model according to any one of claims 6 to 8.
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