CN120567834A - IPPBX voice exchange management system and method based on SIP - Google Patents
IPPBX voice exchange management system and method based on SIPInfo
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Abstract
本申请涉及通信技术领域，具体公开了一种基于SIP的IPPBX语音交换管理系统及方法，方法包括：通过语音管理端对用户进行身份验证和分配内部联系号；基于主被叫号码匹配路由策略生成通话路径，并使用机器学习模型优化SIP路径；根据通话路径和网络状况动态分配媒体资源，启动RTP流传输语音数据，并动态调整语音压缩参数；在通话过程中持续监控会话状态，根据语音会话状态触发对应处理机制。本申请提供了一种安全、高效、智能的IPPBX语音交换管理方法。
This application relates to the field of communications technology and specifically discloses a SIP-based IPPBX voice exchange management system and method. The method includes: authenticating users and assigning internal contact numbers through a voice management terminal; generating call paths based on routing strategies matching calling and called numbers, and optimizing SIP paths using machine learning models; dynamically allocating media resources based on the call path and network conditions, initiating RTP streaming for voice data, and dynamically adjusting voice compression parameters; and continuously monitoring the session status during a call and triggering corresponding processing mechanisms based on the voice session status. This application provides a secure, efficient, and intelligent IPPBX voice exchange management method.
Description
Technical Field
The invention relates to the technical field of communication, in particular to an IPPBX voice exchange management system and method based on SIP.
Background
Voice over Internet Protocol (IP) communication systems, also known as IP telephony systems or IP pbx systems, have greater flexibility, scalability, and cost effectiveness than conventional circuit switched technology. However, existing ip pbx systems still have some problems and challenges in practical applications.
User authentication and account management are one important issue faced by ip pbx systems. How to ensure that only legal users can access the system and effectively manage user accounts is a key for ensuring safe and reliable operation of the system. In the actual voice communication process, how to ensure the call quality is a great challenge. Dynamic changes in network conditions, selection of signaling paths, and scheduling of media resources all affect call quality. How to realize high-quality and low-delay voice communication in complex and changeable network environments is a core problem to be solved by an IPPBX system. Higher requirements are also being placed on the operation and maintenance management of ip pbx systems. How to monitor the running state of the system in real time, discover and process abnormal conditions in time, and optimize and regulate the system is also a problem to be solved urgently.
How to construct a safe, reliable, high-quality, high-efficiency and easy-to-manage IPPBX voice communication system becomes a key technical problem to be solved urgently.
In view of this, the present application proposes an ip pbx voice exchange management system and method based on SIP.
Disclosure of Invention
In order to achieve the above purpose, the present invention provides an ip pbx voice exchange management system and method based on SIP, and the specific technical scheme is as follows:
An IPPBX voice exchange management method based on SIP comprises the following steps:
The voice management terminal receives a registration request of a user terminal, performs identity verification by combining a user account and equipment information, allocates an internal contact number for a new user, and establishes an online state table;
the voice management terminal generates a call path based on the matching of the calling number and the called number with a routing strategy, and simultaneously, a machine learning model is applied to combine with QoS indexes to predict network congestion points and dynamically optimize the SIP path;
Media resources are dynamically allocated according to a call path and network conditions, RTP flow is started, voice data transmission is carried out, and voice compression parameters are dynamically adjusted according to network bandwidth and packet loss rate;
The voice conversation state is continuously monitored in the conversation process, the voice conversation state comprises a Session Initiation Protocol (SIP) signaling flow, a call holding duration and user on-hook signal information, and a corresponding processing mechanism is triggered according to the voice conversation state.
Preferably, after receiving a registration request of a user terminal, the voice management terminal performs identity verification;
A two-way identity verification mechanism based on a certificate is adopted, and when a user terminal initiates a registration request message, the user terminal exchanges the certificate with a voice management terminal and verifies the validity of the certificate;
after the certificate passes verification, the voice management end checks the user account and judges whether the user account has legal registration authority by matching with rules in a management policy;
The matching process of the account attribute and the management policy is abstracted into a set operation problem, namely whether the intersection of the account attribute set and the management policy rule set is empty or not, and if and only if the intersection of the account attribute set and the management policy rule set is not empty, the new user registered account is judged to be a legal account.
Preferably, for a new user account passing the audit, the voice management end distributes a unique internal contact number for the new user account;
the internal contact numbers are numbered by adopting a segmentation representation method and comprise a department number section, a user type section and a user serial number section;
After the voice management terminal distributes the internal contact number, the online state table of the new user is established in the memory, and the online state table is used for recording the user account number, the internal contact number, the IP address, the port number, the registration time and the expiration time information, and is organized in a hash index mode, and the user account number is used as a primary key to realize quick inquiry and update of the state information.
Preferably, after receiving a call request initiated by a user, the voice management end performs routing policy matching according to the calling number and the called number;
the routing strategy consists of predefined matching rules, and each rule comprises a number mode, a calling authority and a routing destination;
the matching process is abstracted into a multi-stage longest prefix matching problem, namely, a routing rule of the longest prefix matched with the calling number and the called number is searched from a routing table.
Preferably, after matching the proper routing rule, the voice management terminal generates a call path according to the routing destination;
The call signaling path is used as a transmission path of voice information, and the media transmission path is used as a transmission path of voice data packets;
introducing a network quality prediction model based on a random forest algorithm at a voice management end, constructing the network quality prediction model based on the random forest algorithm, and constructing a network quality feature vector;
taking a network quality feature vector as input in each decision tree of a random forest algorithm, dividing and judging attributes through a plurality of decision tree nodes, and giving out health scores at leaf nodes;
and selecting the path with the highest health degree score as the optimal path as the call path.
Preferably, when the voice management end selects the optimal path as the call path, the media resource is dynamically allocated and managed, wherein the media resource comprises a media processor, a transmission bandwidth and a coder-decoder;
the voice management end calculates the media resource demand according to the network condition and the load condition of each node in the call path;
after obtaining the media resource demand of each node, the voice management terminal selects an optimal resource allocation scheme from the media resource pool and dynamically allocates the resources to each node.
Preferably, modeling the optimal resource allocation problem as an integer programming model;
the integer programming model aims to minimize the total resource allocation cost on the premise of meeting the media resource demand of each node, and the integer programming model is solved to obtain an optimal resource allocation scheme.
Preferably, after completing the media resource allocation, the voice management end notifies each node on the call path, starts the corresponding media processor and codec according to the allocation scheme, establishes a real-time transmission protocol stream, and transmits voice data;
simultaneously monitoring the bandwidth and the packet loss rate of a network in real time at a voice management end, constructing a dynamic coding and decoding parameter adjustment algorithm, and dynamically adjusting media coding and decoding parameters;
The dynamic coding and decoding parameter adjustment algorithm finds the optimal coding and decoding parameter combination under the constraint of network bandwidth and transmission delay so as to maximize coding and decoding quality;
After the optimal coding and decoding parameter combination is obtained through solving, the optimal coding and decoding parameter combination is issued to each node on the call path, and the node is guided to dynamically adjust coding and decoding behaviors.
Preferably, the voice management end monitors the call flow based on the finite state machine model, calculates average holding time and variance to find an abnormal call mode by tracking the holding time, and starts a session cleaning flow after monitoring the user on-hook signal;
The voice management end periodically executes abnormality detection, which comprises analyzing SIP message log, checking media transmission quality, monitoring system resource occupation and auditing user account information, and automatically executing recovery measures and/or generating alarm information according to detection results.
The SIP-based IPPBX voice exchange management system is used for the SIP-based IPPBX voice exchange management method and comprises a user registration management module, a call path optimization module, a network resource regulation module and a call supervision regulation module;
The user registration management module receives a registration request of a user terminal through a voice management terminal, performs identity verification by combining a user account and equipment information, distributes an internal contact number for a new user, and establishes an online state table;
the call path optimizing module is used for generating a call path based on a calling number and a called number matching routing strategy at a voice management end, simultaneously applying a machine learning model to combine QoS indexes, predicting network congestion points and dynamically optimizing an SIP path;
the network resource adjusting module dynamically allocates media resources according to the call path and the network condition, starts the RTP stream and transmits voice data, and dynamically adjusts voice compression parameters according to the network bandwidth and the packet loss rate;
the call supervision and regulation module is used for continuously monitoring the voice session state in the call process, including the SIP signaling flow, the call holding time length and the user on-hook signal information, and triggering a corresponding processing mechanism according to the voice session state.
The application has the beneficial effects that the communication safety is ensured by combining the user account number and the equipment information for identity verification, the internal contact number is distributed and the online state table is established, thereby being beneficial to managing the user state and improving the system organization and controllability.
The application realizes high-efficiency routing through the matching of the calling number and the called number, and simultaneously utilizes the machine learning model to dynamically predict network congestion and optimize the SIP path, thereby remarkably improving the call quality and the network resource utilization efficiency.
According to the application, media resources are dynamically allocated and voice compression parameters are adjusted according to the real-time network condition, so that packet loss and delay can be effectively reduced, stability and definition of voice data transmission are ensured, and user experience is improved.
The application continuously monitors the session state and responds to event change, effectively supports call holding, abnormality detection and call ending processing, and enhances the intelligent level of the system and the continuity and reliability of service.
The method of the application integrates the SIP protocol and the intelligent optimization mechanism, realizes the whole-flow voice exchange management from registration, routing and transmission to monitoring, and effectively improves the communication quality, the resource utilization rate and the service intelligent level of the system.
Drawings
FIG. 1 is a flow chart of a method for managing voice exchange of an IPPBX based on SIP provided by the invention;
FIG. 2 is a flow chart of user registration and number assignment provided by the present invention;
FIG. 3 is a flow chart of route matching and call optimization provided by the present invention;
FIG. 4 is a flow chart of media resource management and adaptation provided by the present invention;
FIG. 5 is a flow chart of detecting and recovering abnormal call provided by the present invention;
Fig. 6 is a block diagram of an ip pbx voice switching management system based on SIP according to the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will be able to make a similar generalization without departing from the spirit of the invention, so that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Example 1:
Referring to fig. 1, for a first embodiment of the present invention, a method for SIP-based ip pbx voice switching management is provided.
Step 1, the voice management end receives the registration request of the user terminal, performs identity verification by combining the user account number and the equipment information, distributes an internal contact number for a new user, establishes an online state table, and refers to fig. 2 for a user registration and number distribution flow chart in the step.
The voice management terminal receives the registration request of the user terminal and then firstly carries out identity verification, in order to improve the safety, a two-way identity verification mechanism based on certificates is adopted, the user terminal needs to carry a digital certificate issued by a trusted CA when initiating a SIP registration message (SIP REGISTER), the certificate contains public key information of the user, and meanwhile, the voice management terminal also holds a service terminal certificate issued by the trusted CA, and the two parties ensure the identity of the two parties to be true and credible by exchanging the certificates and verifying the legality of the certificates.
It should be noted that Session Initiation Protocol (SIP) is an application-layer control protocol, mainly used for establishing, modifying and terminating a multimedia session between one or more participants, and is formulated by IETF, and the SIP protocol is designed to follow the principles of modularization, scalability and compatibility with existing internet protocols, and is widely used in voice over IP (VoIP), video conferencing, instant messaging and multimedia distribution voice management.
The SIP has a basic function of providing signaling and control mechanisms for communication between users, and the SIP protocol defines a series of message formats and request methods for implementing the processes of user location search, session parameter negotiation, user reachability determination, session establishment and management, session transfer and termination, and the like. The SIP adopts a text format for message interaction, has a structure similar to the HTTP protocol, and has good readability and expandability. SIP REGISTER (SIP register message) is used for the terminal device to register its network address information with the SIP registration server so that other users can locate the terminal by means of the identifier.
It should be noted that the IP pbx voice switching system is an enterprise-level voice communication management system based on IP protocol, and is used for implementing connection, management and control of voice calls between the inside and the outside of an enterprise. Unlike traditional analog or digital PBX system, IPPBX uses IP network to bear voice signal, and realizes signaling control and media transmission of voice data through protocol stack (such as SIP or RTP), so as to have advantages of combining telephone exchange and data network.
After the certificate passes verification, the voice management terminal further checks the user account, and judges whether the user account has legal registration authority or not by checking attribute information of the account, including account type, affiliated department and level, and matching with rules in the management policy, wherein the matching process of the account attribute and the management policy is abstracted into a set operation problem, namely whether an intersection of an account attribute set S a and a management policy rule set S p is empty or not: Wherein S a＝{a1,a2, the..degree } represents the attribute set of the account, S p＝{p1,p2, the..degree } represents the rule set defined in the management policy, and the user account is considered as a legal account only if the intersection of the attribute set of the account and the rule set of the management policy is not a null set, and the user is allowed to register at the voice management terminal.
For the new user account passing the audit, the voice management terminal automatically distributes a unique internal contact number for the new user account according to a preset number numbering rule, and for an enterprise user, the numbering rule of the contact number is flexibly designed according to factors such as an organization structure of the enterprise, user classification and the like. A common numbering convention is the segment representation, i.e. different segments of contact numbers represent different attributes or classifications, an exemplary 8-digit contact number N L may be numbered according to the following convention:
NL＝D1D2D3D4D5D6D7D8;
Where D 1D2 denotes a department number, D 3D4 denotes a user type, and D 5D6D7D8 denotes a serial number of the user under the type. The department attribution and the type of the user can be conveniently and rapidly identified according to the contact number through the numbering rule expressed by the segments, and meanwhile, the contact number is ensured to be unique in the whole system.
In order to maintain the real-time state of the system, the voice management end immediately creates an online state table item of a new user in the memory after the contact number is distributed, records the user account number, the internal contact number, the IP address, the port number, the registration time and the expiration time information, organizes the online state table in a hash index mode, and ensures the quick inquiry and update of the state information by taking the user account number as a main key.
The step adopts the certificate authentication, account attribute matching, flexible number numbering rule and efficient state management mechanism, thereby realizing a safe, reliable, flexible and efficient user registration and number allocation scheme and laying a solid foundation for subsequent communication services.
Step 2, the voice management end generates a call path based on the calling number and called number matching routing strategy, simultaneously, a machine learning model is applied to combine with QoS indexes to predict network congestion points and dynamically optimize the SIP path, and referring to fig. 3, a flow chart of the route matching and call optimization in the step is provided.
The voice management terminal performs routing policy matching according to the calling number and the called number after receiving the call request initiated by the user, wherein the routing policy consists of a set of predefined matching rules, each rule comprises a number mode, a call authority, a routing destination and other attributes, and the matching process is abstracted into a multi-stage longest prefix matching problem, namely the routing rule of the longest prefix matched with the calling number and the called number is searched from a routing table.
Setting the calling number of a call request as a caller, the called number as callee, setting n routing rules in a routing table R, wherein each rule is expressed as a triplet < pa, pe, de >, wherein pa represents a number matching mode, pe represents a call authority, and de represents a routing destination, and the routing matching algorithm is expressed as follows:
Wherein route (cone, callee) represents which routing rule is decided according to the calling number cone and the called number callee, match (number, pa) represents the matching function of the number and the pattern pa, when the number matches pa, the number of matched digits is returned, otherwise 0;n 0 is a subscript, n 0 epsilon [1, n ], and Λ represents logical AND operation. The matching algorithm finds out the routing rule which has the highest matching degree with the calling number and the called number and meets the calling authority, and returns to the corresponding routing destination.
After the voice management terminal is matched with a proper routing rule, a call path is generated according to a routing destination, the call path comprises a call signaling path and a media transmission path, the call signaling path is used for determining a transmission path of an SIP message, the media transmission path is used for determining a transmission path of an RTP (real-time transmission protocol) data packet, and various factors such as network topology, link quality, node load and the like are comprehensively considered in the generation of the call path so as to ensure high availability and high quality of the call.
In order to further optimize the call path, a network quality prediction model based on a random forest algorithm is constructed at the voice management end. Random forests are an integrated learning algorithm that improves the accuracy and robustness of predictions by building multiple decision trees and integrating their predictions.
In the network quality prediction model based on the random forest algorithm, training samples of each decision tree are randomly sampled from an original data set in a self-help sampling mode, and the partition attribute of each node is randomly selected from a candidate attribute set, so that the randomness is beneficial to reducing the variance of the model and improving the generalization capability.
Let F be the network quality feature vector, f= < F 1,f2,...,fm >, where m is the feature quantity,The method is characterized in that the method is used for representing the m 0 th characteristic index such as packet loss rate, time delay, jitter and the like, m 0 epsilon [1, m ], H is the health degree score of a link or a node, the value range is [0,1], and a random forest prediction model can be represented as follows: Wherein K is the number of decision trees, K 0 e [1, k ] is the k 0 th decision tree.
And each decision tree takes the network quality feature vector F as input, and the health degree score is finally given out at the leaf node through the node division and attribute judgment of a plurality of decision trees, wherein the final prediction result of the random forest is the average value of the prediction results of all the decision trees.
A large number of training samples can be obtained by carrying out feature engineering and data cleaning on the historical call data, and the random forest model is trained by utilizing the samples to continuously optimize the parameters and the super parameters of the model so as to obtain the network quality prediction model with stable performance.
When a call path is generated, the voice management end inputs the network quality feature vector of the candidate path into a network quality prediction model to obtain the health degree score of each path, and then the path with the highest health degree score is selected as the optimal path for transmitting call signaling and media data.
The network quality prediction model can also evaluate the health states of all nodes and links in the network in real time to identify potential congestion points, and for the nodes or links with low prediction health degree scores, the voice management end can take active optimization measures, such as dynamically adjusting the transmission path of SIP messages, guiding the call to bypass the congestion nodes, or scheduling standby media processing resources to enhance the reliability of media transmission.
The intelligent routing strategy and the active optimization mechanism can effectively improve call completing rate and call quality of calls, reduce problems of call failure, tone quality reduction and the like caused by network congestion, thereby remarkably improving call experience of users, and simultaneously, network resources can be managed more finely based on a prediction and optimization algorithm of machine learning, and network operation cost is reduced.
Step 3, dynamically distributing media resources according to the call path and network condition, starting RTP flow and transmitting voice data, and dynamically adjusting voice compression parameters according to network bandwidth and packet loss rate, referring to FIG. 4, a media resource management and adaptation flow chart of the step is shown.
After the voice management end completes the generation and optimization of the call path, the voice management end dynamically allocates and manages the media resources, wherein the media resources comprise a media processor, a transmission bandwidth and a coder-decoder, and the media resources determine the tone quality and experience of the call.
The voice management end calculates the media resource demand according to the network condition and the load condition of each node in the call path, wherein the call path is set as P, the node set on P is N p＝{n1,n2,...,nY, Y represents the number of nodes, the network state feature vector of each node is S y＝<sy1,sy2,...,sYm >, ym represents the dimension number of the network state feature vector S y and comprises packet loss rate, time delay and jitter indexes, the load feature vector of the node is L y＝<ly1,ly2,...,lYn, yn represents the dimension number of the node load feature vector and comprises indexes of CPU occupancy rate, memory utilization rate and connection number, Y is E [1, Y ], and the node media resource demand R y is calculated by a resource mapping function f:
Where S y||2 is the two norms of the network state characteristics, reflecting the overall network state strength, phi (L y) is a nonlinear mapping function to the load characteristic vector L y, which, by way of example, Representing the cross-influencing function between the network state and the load, which, by way of example,Gamma and delta are adjustment coefficients for characterizing nonlinear response intensities.
After obtaining the resource demand of each node, the voice management end comprehensively considers the factors of the geographic position, the resource utilization rate and the service quality of the node, selects an optimal resource allocation scheme from a media resource pool and dynamically allocates the optimal resource allocation scheme to each node, and sets the media resource pool as R= { R 1,r2,...,rQ }, wherein Q represents the total number of media resources, R j represents the j-th media resources, such as a media processor, a codec and the like, and models the optimal resource allocation problem as an integer programming model:
Wherein x ij is a non-negative integer decision variable representing the number of the j-th media resources allocated to the node N i, c ij is the cost of allocating the resources to the node N i and is calculated according to the performance, energy consumption, position and other factors of the resources, b ij is the resource contribution of the j-th media resources to the node N i, N j is the available number of the j-th media resources, the model aims to minimize the total resource allocation cost on the premise of meeting the media resource demand of each node, and the integer programming model is solved to obtain the optimal resource allocation scheme, namely
After the media resource allocation is completed, the voice management end informs each node on the call path, starts a corresponding media processor and a corresponding codec according to an allocation scheme, establishes an RTP (real-time transport protocol) stream and starts to transmit voice data, the RTP protocol is based on a UDP protocol, and achieves the functions of time sequence control, synchronization, mixed stream and the like in the real-time data transmission process by adding fields such as a serial number, a time stamp, a synchronous information source identifier and the like into a data packet, and the voice management end serves as an initiator and a controller of an RTP session and is responsible for coordinating RTP parameters of each node and monitoring and managing the RTP stream.
In order to adapt to the dynamic change of the network condition in the call process, the voice management end simultaneously monitors the bandwidth and the packet loss rate of the network in real time and dynamically adjusts media coding and decoding parameters to ensure the tone quality and the fluency of the call, and if the currently detected network bandwidth is B and the packet loss rate is rho, the dynamic coding and decoding parameter adjustment algorithm is expressed as the following optimization problem:
wherein, the The coding and decoding parameter vector comprises coding bit rate, frame length, FEC (forward error correction) strategy and the like, G (-) is a coding and decoding quality evaluation function, influences of coding and decoding parameters, network bandwidth and packet loss rate on tone quality are comprehensively considered, the coding and decoding parameter vector is constructed based on standard algorithms such as PESQ, POLQA and the like, H (-) is a coding bit rate function and represents the coder parameter vectorThe encoded data rate at D (·) is the transmission delay function expressed in encoder parametersAnd an end-to-end transmission delay under the packet loss rate ρ, D max is the maximum allowable transmission delay, and exemplary, D max is generally set to 150-200 ms to ensure real-time interactivity.
The objective of the optimization problem of the dynamic codec parameter adjustment algorithm is to find the optimal codec parameter combination under the constraints of network bandwidth and transmission delayMaximizing the codec quality assessment function G, solving the problem by heuristic search algorithms (such as genetic algorithm, particle swarm optimization, etc.) or reinforcement learning algorithms (such as deep Q learning, strategy gradient, etc.), solving the resulting optimal encoder parameter combinationsThe method and the system can be issued to each node on the call path in real time to guide the node to dynamically adjust the coding and decoding behaviors of the node, so that higher call tone quality and user experience can be maintained under the condition of fluctuation of network conditions.
The method realizes the fine management and dynamic adaptation of media resources by quantifying the resource requirements of nodes, optimizing the media resource allocation, applying a real-time transmission protocol, intelligent coding and decoding control and other key technologies, maximizes the resource utilization efficiency, improves the service capacity and economy of the system on the basis of guaranteeing the conversation tone quality and the user experience, and is the core competitiveness of the IPPBX and the voice exchange.
And 4, continuously monitoring the voice session state in the conversation process, wherein the voice session state comprises a Session Initiation Protocol (SIP) signaling flow, a call holding time length and user on-hook signal information, and triggering a corresponding processing mechanism according to the voice session state, and referring to fig. 5, the conversation abnormality detection and recovery flow chart in the step is provided.
In the conversation process, the voice management end continuously monitors the conversation session state, including the information of SIP signaling flow, call holding time length, user on-hook signal and the like, and is used for timely finding and processing abnormal conditions.
The voice management end is used for describing the SIP signaling flow based on a finite state machine model, each SIP transaction (such as call establishment, call release and the like) corresponds to one state machine instance, the state machines define a state set, a state transition rule and a processing action under each state of the transaction, and a group of state machine templates are predefined at the voice management end according to SIP protocol standards.
When the voice management end receives the SIP request message, instantiating a corresponding state machine according to the request type, updating the current state of the state machine along with the receiving and sending of the subsequent SIP message, and timely detecting abnormal events (such as overtime, invalid response and the like) and triggering a corresponding abnormal processing flow by tracking the state of each SIP transaction in real time.
The voice management end continuously tracks the call holding time length of each call session, calculates the average holding time length and holding time length variance of all active calls at regular intervals (for example, every 30 minutes), and finds abnormal call modes by tracking the change trend of the two indexes. Illustratively, when the average hold time period is significantly higher than the historical average and the hold time period variance is large, this indicates that a small number of calls are held for a long period of time, requiring attention from the administrator.
The voice management end also monitors the on-hook signal of the user in real time, and once the on-hook signal is detected, the session cleaning flow is started immediately, including releasing the media resources occupied by the session, so as to avoid long-time occupation and leakage of the resources.
The voice management end regularly carries out abnormality detection, and the abnormality detection step comprises the following steps:
analyzing the SIP message log, checking the legality and time sequence relation of the SIP message, and identifying suspicious message or transaction;
step b, checking media transmission quality statistics, analyzing indexes such as packet loss rate, jitter and the like in the call process, and judging whether network problems exist or not;
step c, checking the occupation condition of system resources, monitoring the use condition of resources such as a CPU, a memory, a disk and the like, and checking whether resource bottlenecks exist;
And d, inquiring user account information and service data, checking configuration information of the user account and related service data, and checking whether abnormal behaviors caused by account configuration errors or inconsistent service data exist.
And according to the detection result, the voice management terminal automatically executes corresponding recovery measures, including restarting the SIP transaction, switching the media transmission path, adjusting the resource allocation strategy and correcting the service data, and generating alarm information and notifying an administrator of manual intervention processing for serious anomalies which cannot be recovered automatically.
The step realizes the abnormal management of the whole call life cycle by monitoring the SIP signaling flow, the call holding time and the user on-hook signal in real time and introducing an automatic detection and recovery mechanism, ensures the continuity and high availability of voice service, improves the self-healing capacity and the operation and maintenance efficiency of the system and lays a foundation for constructing high-quality voice communication service.
Example 2:
Referring to fig. 6, for a second embodiment of the present invention, an ip pbx voice switching management system based on SIP is provided.
The system comprises a user registration management module, a call path optimization module, a network resource adjustment module and a call supervision adjustment module.
The user registration management module receives a registration request of the user terminal through the voice management terminal, performs identity verification by combining the user account number and the equipment information, distributes an internal contact number for a new user, and establishes an online state table.
The call path optimizing module is used for generating a call path based on the matching of the calling number and the called number and the routing strategy at the voice management end, simultaneously, a machine learning model is applied to combine with QoS indexes, so as to predict network congestion points and dynamically optimize the SIP path.
The network resource adjusting module dynamically allocates media resources according to the call path and the network condition, starts the RTP stream and transmits voice data, and dynamically adjusts voice compression parameters according to the network bandwidth and the packet loss rate.
The call supervision and regulation module is used for continuously monitoring the voice session state in the call process, including the SIP signaling flow, the call holding time length and the user on-hook signal information, and triggering a corresponding processing mechanism according to the voice session state.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and variations, modifications, substitutions and alterations of the above-described embodiments may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the present invention as defined by the claims, which are all within the scope of the present invention.
Claims (10)
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