CN115066032A - 5G-TSN industrial heterogeneous virtual network architecture and virtual resource fine-grained scheduling method - Google Patents
5G-TSN industrial heterogeneous virtual network architecture and virtual resource fine-grained scheduling method Download PDFInfo
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- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
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- H—ELECTRICITY
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Abstract
The invention discloses a 5G-TSN industrial heterogeneous virtual network architecture and a virtual resource fine-grained scheduling method, and relates to the field of industrial communication. Virtualizing a TSN intelligent gateway of an edge computing layer into a virtual machine with a TSN function by adopting an NFV technology; the SDN controller is used for controlling a TSN intelligent gateway supporting an SDN technology and deployed on an edge computing layer in a centralized mode, performing virtual network modeling on a 5G-TSN industrial heterogeneous network from a resource scheduling view by combining with an NFV technology, and performing scheduling management on network slices belonging to different industrial applications and having different QoS. The invention provides a 5G-TSN industrial heterogeneous virtual network architecture and a heterogeneous QoS mapping mechanism by combining 5G data characteristics and aiming at the upper layer dynamic application requirement of flexible manufacturing, considering field communication resources and heterogeneous QoS requirements of data streams, introducing an information age (AoI) as an index from a virtual layer to characterize the information timeliness of data transmission of a 5G access network, and can realize fine-grained on-demand delivery of industrial multi-priority heterogeneous data streams.
Description
Technical Field
The invention relates to the field of industrial communication, in particular to a 5G-TSN industrial heterogeneous virtual network architecture and a virtual resource fine-grained scheduling method.
Background
In the face of a new turn of digitized wave, how to implement digitized intelligence of manufacturing industry becomes one of the strategic directions of the national future industry competitiveness, so it is urgently needed to break through the advanced Technology industrialization barrier, and an emerging Communication Technology represented by a fifth Generation Mobile Communication Technology (5th Generation Mobile Communication Technology, 5G) and a Time Sensitive network protocol (TSN) is applied to an industrial field to implement full-element interconnection and end-to-end delivery as required, such as a man-machine material method ring, etc., in a wireless-wired fusion manner.
Under the future small-batch and customized industrial production requirements, the traditional shaft type industrial deployment cannot meet the dynamic requirements of upper-layer application, and the development of an industrial communication technology is greatly hindered. Software-Defined Networking (SDN) and Network Function Virtualization (NFV) technologies are introduced to the academic and industrial circles to perform Virtualization allocation of Network resources at different levels without considering implementation details of underlying technologies, and a general communication solution is provided for applications with different Quality of service (QoS) through centralized resource scheduling and dynamic instruction issuing. Therefore, the virtual network modeling is carried out on the 5G-TSN industrial heterogeneous network by adopting the SDN and NFV technologies, the technical barrier of heterogeneous protocol conversion can be broken, and the scheduling mechanism design is carried out on the 5G-TSN novel network architecture from the resource perspective.
Although the adoption of the virtualized network modeling does not need to consider the implementation details of technologies such as protocol conversion, precision clock synchronization and the like, the integration of 5G and TSN networks from the resource perspective still has many challenges. First, although 5G technology has a significant improvement in latency and reliability compared to 4G-LTE and other cellular technologies, for future industrial networks with "sense-compute-control" integration as the core, whether field information can be collected in real time and end-to-end deterministic delivery greatly affects data computation efficiency and control quality. And the electromagnetic environment of an industrial field is complex, mobile terminal equipment is numerous, the multipath fading effect is serious, and the inherent uncertainty defect of wireless communication cannot be completely overcome by the improvement of the communication quality and efficiency of a 5G communication mechanism, so that how to ensure the end-to-end deterministic delivery of data when two heterogeneous networks of 5G and TSN are fused is a great challenge. Secondly, for customized production requirements with different QoS, whether the product quality can be guaranteed differently is a large standard for checking the production performance. For this purpose, TSNs and 5G respectively specify mechanisms including frame preemption, Time Aware gating (TAS), stream Filtering (PSFP), and parameters such as 5QI (5G QoS Identifier), ipv (internal Priority value) to provide differentiated services for multi-Priority data. However, as two emerging communication technologies, how to implement the data QoS interworking between the two technologies is the key of 5G-TSN fusion.
As a parameter for measuring the time efficiency of information, the Age of information (AoI) represents the time that a data packet has elapsed since it was generated until it reaches its destination, and is related to the sampling frequency and the control efficiency, which is an important index for reflecting the timeliness of state update in the industrial system. Therefore, AoI is adopted to depict the information time effect of 5G access network data transmission under the 5G-TSN industrial heterogeneous network architecture, so that the industrial communication requirement of integration of sensing, calculation and control can be well matched, and the end-to-end deterministic delivery of data is further ensured.
The search of the existing literature finds that the most approximate realization scheme is that the Chinese patent application numbers are as follows: 202110702240.6, the name is: the utility model provides a support heterogeneous traffic shaper of industrial network of 5G and TSN interconnection, its specific content is: three End-to-End (E2E) communication types of 5G interconnection with the TSN are proposed. The control flow is shaped by adopting a First-In First-Out (FIFO) rule, the non-control flow is shaped by adopting a Credit-based Scheduling (CBS) rule, and different QoS requirements of data are met by the differential shaping mechanism. The method allocates high-priority queues for control flows to transmit independently, but by adopting an FIFO rule, the control flows arriving at the queues cannot be guaranteed to be forwarded in real time, so that queuing delay is generated. The patent application numbers are: 201980020000.9, the name is: the time-sensitive network frame preemption across the cellular interface comprises the following specific contents: and respectively reserving certain time-frequency resources for the high-priority data and the low-priority data to be transmitted. In the time period reserved for the high-priority data, if the high-priority data arrives, the non-waiting forwarding can be realized; and in a time period reserved for the low-priority data, if the high-priority data arrives, the transmission of the low-priority data can be interrupted, and the low-priority data is preempted. However, the reserved resources cause resource waste under the condition of low flow prediction accuracy, and the two types of priorities cannot be adapted to complex industrial situations. The patent application numbers are: 202110718079.1, the name is: A5G-TSN cross-domain QoS and resource mapping method, equipment and a computer readable storage medium are provided, which comprises the following specific contents: and establishing a 5G-TSN resource mapping conversion relation model based on a Markov process according to the service flow, the data packet arrival rate and the service rate, and mapping the service flow to 5G resources in sequence according to the priority of the TSN service flow. But mainly considers the mapping between the physical resource blocks, and does not consider the relation between the priority mapping and the time delay guarantee. The patent application numbers are: 202110718076.8, the name is: the 5G and TSN joint scheduling method based on wireless channel information comprises the following specific contents: and adjusting the retransmission factor of the data in the 5G network and the transmission delay of the data in the TSN network according to the channel quality information CQI to achieve the purpose of deterministic transmission in the 5G-TSN combined network. But the quality grade of the CQI is only divided according to the coarse granularity of the threshold value, and the scheduling is not carried out according to the TSN queue condition and the 5G resource utilization condition in a fine-grained manner. The patent application numbers are: 202080014340.3, the name is: the 5G system support for virtual TSN bridge management, QoS mapping and TSN Qbv scheduling comprises the following specific contents: specific TSN interfaces and their corresponding functions for QoS flow mapping in 5G and TSN are given, but no specific description is given on how to calculate QoS mapping relationship. The patent application numbers are: 202080040110.4, with the name: the TSN and 5GS QoS mapping-user plane based method comprises the following specific contents: specific 5GS interfaces and corresponding functions of QoS flow mapping in 5G and TSN are given, but no specific description is given on how to calculate the QoS mapping relation.
The existing joint research 5G and TSN transmission technologies have less work, mostly aim at the problem of how to guarantee the differentiated transmission of multi-QoS data in the TSN technical research, mostly adopt offline modes such as resource reservation, multi-mechanism differentiated service provision and the like to meet different priority requirements of TSN network data streams, and have low flexibility.
Most of the existing research on 5G-TSN industrial heterogeneous networks considers the problems of clock synchronization of 5G and TSN, resource mapping and the like in a physical heterogeneous network, and the research on cross-domain scheduling of virtual resources under the 5G-TSN industrial heterogeneous virtual network scene is not considered yet.
In the existing research on the TSN technology, attention is mostly paid to a Time aware gate (TAS) mechanism of the IEEE 802.1Qbv technology or a Precision Time Protocol (PTP) mechanism of the IEEE 802.1AS, and no research on mapping of a Virtual Network Function (VNF) based on AoI is considered in the Virtual Network layer.
Most of the existing researches for carrying out multi-priority data scheduling in a TSN network are simply divided into high-priority data streams and low-priority data streams, or divided into control streams and non-control streams, and few researches about fine-grained multi-QoS differential scheduling problems with the priority number larger than 2 are carried out.
Therefore, those skilled in the art are devoted to develop a 5G-TSN industrial heterogeneous virtual network architecture and a fine-grained scheduling method for virtual resources. The method is oriented to the upper layer dynamic application requirement of flexible manufacturing, considers the field communication resource and the heterogeneous QoS requirement of the data flow, provides a 5G-TSN industrial heterogeneous virtual network architecture and a heterogeneous QoS mapping mechanism from a virtual layer, and can achieve fine-grained on-demand delivery of industrial multi-priority heterogeneous data flow.
Disclosure of Invention
In view of the above defects in the prior art, the technical problem to be solved by the present invention is how to provide a specific operation mode of a 5G-TSN industrial heterogeneous virtual network architecture and a cross-domain scheduling scheme of virtual resources in a 5G-TSN network for an intelligent manufacturing production scenario proposed by industry 4.0, in combination with the advantages of wired TSN, wireless 5G communication and network virtualization technologies; under a 5G-TSN industrial heterogeneous virtual network architecture, how to provide adaptive reliable transmission and flexible hierarchical scheduling for multi-QoS data based on a network fragmentation technology so as to meet the requirements of low time delay and high reliability communication of small-batch and customized flexible production; how to guide the differentiated on-demand mapping of the network virtual resources by combining novel communication indexes such as AoI and the like; how to solve the communication requirement of the massive heterogeneous data of the industrial field and carry out fine-grained elastic resource mapping on the data at the virtual layer.
In order to achieve the purpose, the invention provides a 5G-TSN industrial heterogeneous virtual network architecture, which comprises an industrial field layer, an edge computing layer and an SDN controller;
edge calculation layer: the method comprises the following steps of virtualizing a TSN intelligent gateway of an edge computing layer into a virtual machine with a TSN function by adopting an NFV technology, wherein the virtual machine has the functions of a physical TSN intelligent gateway: 5G micro base station and heterogeneous protocol conversion;
an SDN controller: the centralized control is deployed on a TSN intelligent gateway supporting the SDN technology of an edge computing layer, and is combined with the NFV technology to schedule and manage different QoS network slices belonging to different industrial applications.
Furthermore, the devices of the industrial field layer are tiled in a network slice mode to use 5G time-frequency resource blocks, the field devices managed by the same TSN intelligent gateway share frequency spectrum resources, and resource competition relations do not exist among the field devices managed by different TSN intelligent gateways.
Furthermore, after the field data is generated, the field data can only be injected into the TSN network through the TSN intelligent gateway in the management area, that is, the starting point of injecting each slice data stream into the TSN network (the TSN intelligent gateway of the wireless data injection TSN network) is fixed.
Furthermore, the 5G communication network is virtually drawn of the physical 5G communication network, the upper layer application is transmitted in the 5G-TSN industrial heterogeneous network in a network slice form sequentially composed of VNFs, and the data corresponding to the slice is flatly spread to use the site time frequency resource block; the TSN backbone network is a virtual depiction of a physical TSN network, each TSN intelligent gateway is virtualized into a virtual machine with the function of a TSN intelligent gateway, the virtual machine has computing capacity and caching capacity, after an application slice reaches the TSN network, an internal VNF maps the performance of the combined TSN VM to the TSN VM in sequence, the resources of the TSN VM are occupied, and only after all VNFs belonging to one network slice are mapped, the application can be delivered to a remote end through the TSN backbone network.
Further, for the requirement of real-time sampling of data streams in an industrial scene, information freshness AoI indexes are introduced to perform information age measurement on sliced data streams, data starts to grow from AoI from the field generation time, and stops growing after being transmitted to a remote terminal through a 5G network and a TSN network AoI.
Further, slices belonging to different applications and their corresponding data streams have different priorities, so that different slices have different end-to-end upper age bounds a E2E And the 5G-TSN industrial heterogeneous virtual network carries out on-demand scheduling on the multi-priority slice data stream according to the age upper limit of each slice.
The invention also provides a fine-grained scheduling method of the 5G-TSN industrial heterogeneous virtual resources, which is characterized by comprising the following steps of:
step 1, dividing data generated by field equipment into high-priority slice data and low-priority slice data according to slice priorities;
step 2, dividing industrial site time-frequency resources into time-frequency Resource Blocks (RBs), wherein each RB is a minimum irrevocable unit, a corresponding frequency band is a minimum bandwidth which accords with Nyquist intervals, and a corresponding time period is a plurality of OFDM symbol intervals;
step 3, when the upper application slice is issued, triggering the corresponding field device and generating the data belonging to the slice, wherein the priority of the data is consistent with that of the application slice, and the upper age limit A of each slice is determined according to the self age limit of the slice E2E The tiling uses the field time-frequency resource block, the tiling can be carried out in the time domain with lower requirement on the time delay, and the tiling can be carried out in the frequency domain with higher requirement on the time delay; because the high-priority slice data has high requirement on time delay, the high-priority slice data is only allowed to be tiled in a frequency domain, and only one RB time period is occupied in a time domain, and the high-priority slice data can be preempted when arrivingTiled low-priority slice data resources;
step 4, the age of the data linearly increases along with time after the data is generated on site, and the age A of each slice of data in a 5G network can be obtained after transmission is finished 5G According to the upper age limit A of each slice E2E And its age A in the 5G network 5G Fine-grained priority adjustment is performed as follows:
step 5, setting the priority of each VNF belonging to the slice to p TSN That is, the TSN queue priority to which data needs to be injected when the VNF maps the TSN VM, and after all VNFs are mapped to the virtual TSN network in sequence, the 5G-TSN full-flow age of the slice can be obtained, and end-to-end on-demand delivery of field data to a remote end is completed.
Further, in the step 1, the real-time requirement of the low-priority slice data is lower than that of the high-priority slice data, but the real-time requirements of different data of the low-priority slice are different, and the low-priority slice data is tiled to use time-frequency resource blocks.
Furthermore, the high-priority slice data in the step 4 preempts the low-priority data, and the non-waiting fast forwarding can be realized in the 5G network; and transmitting the preempted low-priority slice data after the transmission of the high-priority slice data is finished, and correspondingly prolonging the transmission delay in the 5G network.
Further, in the step 5, fine-grained QoS mapping, original two priority fine-grained are divided into 8 priorities by means of queue injection, and an elastic transmission service is provided based on the TSN network characteristics.
In a preferred embodiment of the present invention, the purpose of the present invention is to provide a 5G-TSN industrial heterogeneous virtual network architecture and a heterogeneous QoS mapping mechanism from a virtual layer in consideration of field communication resources and heterogeneous QoS requirements of data streams for flexible manufacturing upper layer dynamic application requirements, so as to implement fine-grained on-demand delivery of industrial multi-priority heterogeneous data streams.
A5G-TSN industry heterogeneous virtual network architecture based on network function virtualization comprises the following parts:
industrial field layer: the system mainly comprises field devices such as a communication node, a sensor, a controller and an actuator, wherein the devices are communicated in a 5G mode, and the system is responsible for monitoring and uploading field working conditions and issuing instructions according to an upper layer to execute corresponding decisions.
Edge calculation layer: the intelligent gateway system mainly comprises a plurality of TSN intelligent gateways, the gateways are connected through a TSN backbone network, each TSN intelligent gateway has strong calculation power and can execute basic calculation activities, and meanwhile, the intelligent gateway system is responsible for managing adjacent field nodes according to the physical position of the intelligent gateway system, collecting field data and processing the field data. The TSN intelligent gateway has the function of an edge computing node under the framework.
Data communication is carried out between the industrial field layer and the edge computing layer through a 5G technology, field devices managed by the same TSN intelligent gateway share frequency spectrum resources, and resource competition exists; resource competition relation does not exist among field devices managed by different TSN intelligent gateways.
After the field data is generated, the field data can only be injected into the TSN through the TSN intelligent gateway managing the area, namely, the starting point of injecting each slice data stream into the TSN is fixed.
The 5G communication network is a virtual depiction of a physical 5G communication network, and is specifically represented as follows: the upper layer application is transmitted in a 5G-TSN industrial heterogeneous network in a network slice form sequentially composed of VNFs, and data streams corresponding to slices use field time frequency resource blocks in a tiled mode.
The TSN backbone network is a virtual depiction of a physical TSN network, and is specifically represented as follows: each TSN intelligent gateway is virtualized as a Virtual Machine (VM) having TSN intelligent gateway function, and has computing capability and caching capability, after an application slice reaches a TSN network, its internal VNF maps the performance of the TSN VM to the TSN VM in sequence, and occupies the memory of the TSN VM, and only after all VNFs belonging to one network slice are mapped, the application slice can be regarded as being delivered to a remote end through a TSN backbone network.
The information freshness AoI index is introduced to measure the real-time performance of the sliced data stream in consideration of the real-time sampling requirement of the data stream in an industrial scene. The data starts to grow in age from the moment of field generation, and stops growing in age after being transmitted to a remote terminal point through a 5G network and a TSN network.
Because the real-time requirements of the upper-layer applications are different, the positions, functions, data volumes and the like of the industrial field devices are different, and the slices belonging to different applications and corresponding data streams thereof have different priorities, different slices have different end-to-end age upper bounds A E2E . The 5G-TSN industrial heterogeneous virtual network needs to schedule multi-priority slice data streams according to the age of each slice.
A method for scheduling fine granularity of multi-priority virtual resources comprises the following steps:
step 1: data generated by the field device is classified into high-priority slice data and low-priority slice data according to slice priority.
And 2, step: the industrial field time frequency Resource is divided into time frequency Resource Blocks (RBs), each RB is a minimum irrevocable unit, the corresponding frequency band is the minimum bandwidth which accords with the Nyquist interval, and the corresponding time period is a plurality of OFDM symbol intervals.
And step 3: when the upper application slice is issued, triggering the corresponding field device and generating the data belonging to the slice, wherein the priority of the data is consistent with that of the application slice, and the upper age limit A of each slice is determined according to the self age limit of the slice E2E The tiling uses the field time frequency resource block, the tiling can be carried out in the time domain with lower time delay requirement, and the tiling can be carried out in the frequency domain with higher time delay requirement. Since high-priority slice data has high delay requirements, only the tiling in the frequency domain is allowed, which only occupies a time period of one RB in the time domain, and for this reason, when the high-priority slice data arrives, the already tiled low-priority slice data resources can be preempted.
And 4, step 4: the age of the data linearly increases along with time after the data is generated on site, and the age A of each slice of data in a 5G network can be obtained after the data is transmitted 5G According to the upper age limit A of each slice E2E And its age A in the 5G network 5G The fine-grained priority is adjusted as follows:
and 5: setting the priority of each VNF belonging to a slice to p TSN That is, the TSN queue priority to which data needs to be injected when the VNF maps the TSN VM, and the 5G-TSN full-flow age of the slice can be obtained by completing the sequential mapping of all VNFs, so that the end-to-end on-demand delivery of the field data to the remote end is completed.
The real-time requirement of the low-priority slice data in the step 1 is lower than that of the high-priority slice data, but the real-time requirements of different low-priority slice data are different, which is also the reason that the low-priority slice data is tiled to use time-frequency resource blocks.
And 2, selecting a plurality of OFDM symbols in the time period corresponding to the RB.
And (3) preempting the high-priority slice data in the step (3) with the low-priority data, wherein the preempted low-priority slice data is transmitted after the transmission of the high-priority slice data is finished, and the transmission delay of the high-priority slice data in the 5G network is correspondingly prolonged.
For the fine-grained QoS mapping described in step 4, the original two priority levels of fine-grained are divided into 8 priority levels by means of queue injection, so that the flexible transmission service can be better provided based on the TSN network characteristics. The priority of each slice stream inside the TSN network is different from its priority inside the 5G network.
In another preferred embodiment of the present invention, the slice data stream priorities are adjusted for each VNF mapped to the TSN VM, rather than just when injected into the TSN network
Compared with the prior art, the invention has the following obvious substantive characteristics and obvious advantages:
1. the ubiquitous access characteristic of 5G communication and the deterministic transmission characteristic of a TSN (time series network) are combined, the flexibility of network virtualization for physical resource scheduling is considered, a 5G-TSN industrial heterogeneous virtual network architecture is innovatively provided, and how to provide flexible transmission service for different application slices is described from a virtual perspective.
2. Considering the transmission uncertainty of 5G communication caused by environment opening and serious electromagnetic interference of an industrial field, the transmission service is flexibly adjusted through a 5G-TSN fine-grained priority mapping mechanism, and the field-to-remote deterministic on-demand delivery is provided for multi-QoS data.
3. A virtual resource scheduling process under a 5G-TSN industrial heterogeneous virtual network architecture is innovatively provided, network slice tiling in a 5G network and VNF mapping in a TSN network to a TSN virtual machine are included, and a specific virtual network transmission path is designed.
4. A more flexible industrial transmission scheme is provided by adopting a network function virtualization technology, details (clock synchronization, protocol conversion and the like) of a bottom layer technology combined by 5G-TSN do not need to be considered, and the feasibility of the deployment of the industrial heterogeneous network transmission scheme is improved.
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Drawings
FIG. 1 is a diagram of a 5G-TSN industrial heterogeneous virtual network architecture in accordance with a preferred embodiment of the present invention;
FIG. 2 is a 5G network slice tile of a preferred embodiment of the present invention;
fig. 3 is a 5G-TSN fine-grained QoS map of a preferred embodiment of the present invention;
FIG. 4 is a flow diagram of multi-priority data slice 5G scheduling in accordance with a preferred embodiment of the present invention;
fig. 5 is a flow chart of the scheduling of multiple priority data slices TSN according to a preferred embodiment of the present invention.
Detailed Description
The technical contents of the preferred embodiments of the present invention will be more clearly and easily understood by referring to the drawings attached to the specification. The present invention may be embodied in many different forms of embodiments and the scope of the invention is not limited to the embodiments set forth herein.
In the drawings, elements that are structurally identical are represented by like reference numerals, and elements that are structurally or functionally similar in each instance are represented by like reference numerals. The size and thickness of each component shown in the drawings are arbitrarily illustrated, and the present invention is not limited to the size and thickness of each component. The thickness of the components may be exaggerated where appropriate in the figures to improve clarity.
The invention relates to a 5G-TSN industrial heterogeneous virtual network architecture based on network function virtualization, which comprises the following parts:
an SDN controller: the centralized control is deployed on a TSN intelligent gateway supporting the SDN technology of an edge computing layer, and is combined with the NFV technology to schedule and manage different QoS network slices belonging to different industrial applications.
Edge calculation layer: the method comprises the following steps of virtualizing a TSN intelligent gateway of an edge computing layer into a virtual machine with a TSN function by adopting an NFV technology, only considering own computing resources and storage resources and not considering bottom layer operation details, and simultaneously enabling the virtual machine to have the functions of a physical TSN intelligent gateway: 5G micro base station and heterogeneous protocol conversion, etc.
The equipment of the industrial field layer is tiled in a network slice mode to use 5G time-frequency resource blocks, the field equipment managed by the same TSN intelligent gateway shares frequency spectrum resources, and resource competition relation does not exist among the field equipment managed by different TSN intelligent gateways.
After the field data is generated, the field data can only be injected into the TSN network through the TSN intelligent gateway managing the area, that is, the starting point of injecting each slice data stream into the TSN network (the TSN intelligent gateway of the wireless data injection TSN network) is fixed.
The 5G communication network is a virtual depiction of a physical 5G communication network, and is specifically represented as follows: the upper layer application is transmitted in a 5G-TSN industrial heterogeneous network in a network slice form sequentially composed of VNFs, and data streams corresponding to slices use field time frequency resource blocks in a tiled mode. The TSN backbone network is a virtual depiction of a physical TSN network, and is specifically represented as follows: each TSN intelligent gateway is virtualized into a virtual machine with the function of the TSN intelligent gateway, the virtual machine has computing capacity and caching capacity, after an application slice reaches a TSN network, the VNFs in the application slice are mapped to the TSN VMs according to the performance of the TSN VMs in sequence, the memory of the TSN VMs is occupied, and the application can be delivered to a far end through a TSN backbone network only after all the VNFs belonging to one network slice are completely mapped.
Considering the requirement of data stream on real-time sampling in an industrial scene, information freshness AoI index is introduced to perform information age measurement on sliced data stream, data starts to grow from AoI at the moment of field generation, and stops growing after being transmitted to a remote terminal through a 5G network and a TSN network AoI.
Because the real-time requirements of the upper-layer applications are different, the positions, functions, data volumes and the like of the industrial field devices are different, and the slices belonging to different applications and corresponding data streams thereof have different priorities, different slices have different end-to-end age upper bounds A E2E The 5G-TSN industrial heterogeneous virtual network needs to schedule multi-priority slice data streams according to the age upper bound of each slice.
The invention discloses a method for scheduling fine granularity of multi-priority virtual resources, which comprises the following steps:
step 1: data generated by the field device is classified into high-priority slice data and low-priority slice data according to slice priority.
Step 2: the industrial field time frequency Resource is divided into time frequency Resource Blocks (RBs), each RB is a minimum irrevocable unit, the corresponding frequency band is the minimum bandwidth which accords with the Nyquist interval, and the corresponding time period is a plurality of OFDM symbol intervals.
And step 3: when the upper application slice is issued, triggering the corresponding field device and generating the data belonging to the slice, wherein the priority of the data is consistent with that of the application slice, and the upper age limit A of each slice is determined according to the self age limit of the slice E2E The tiling uses the field time frequency resource block, the tiling can be carried out in the time domain with lower time delay requirement, and the tiling can be carried out in the frequency domain with higher time delay requirement. Since high-priority slice data is very time-delay demanding, tiling is only allowed in the frequency domain, which is only in the time domainA time period of one RB is occupied for which the low-priority slice data resources that have been tiled can be preempted when high-priority slice data arrives.
And 4, step 4: the age of the data linearly increases along with time after the data is generated on site, and the age A of each slice of data in a 5G network can be obtained after the data is transmitted 5G According to the upper age limit A of each slice E2E And its age A in the 5G network 5G The fine-grained priority is adjusted as follows:
and 5: setting the priority of each VNF belonging to a slice to p TSN That is, the TSN queue priority to which data needs to be injected when the VNF maps the TSN VM, and the 5G-TSN full-flow age of the slice can be obtained by completing the sequential mapping of all VNFs, so that the end-to-end on-demand delivery of the field data to the remote end is completed.
In step 1, the real-time requirement of the low-priority slice data is lower than that of the high-priority slice data, but the real-time requirements of different data of the low-priority slice are different, which is also the reason why the low-priority slice data is tiled to use time-frequency resource blocks.
Preempting the low-priority data for the high-priority slice data in the step 4, wherein the high-priority slice data can be quickly forwarded without waiting in a 5G network; and transmitting the preempted low-priority slice data after the transmission of the high-priority slice data is finished, and correspondingly prolonging the transmission delay in the 5G network.
For the fine-grained QoS mapping described in step 5, the original two priority levels of fine-grained are divided into 8 priority levels by means of queue injection, so that the flexible transmission service can be better provided based on the TSN network characteristics. The priority of each slice stream inside the TSN network is different from its priority inside the 5G network.
As shown in fig. 1, taking a steel plant whose main industry is hot rolling industry as an example, a 5G-TSN industrial heterogeneous virtual network architecture diagram mainly consists of the following two parts:
industrial field layer: the intelligent monitoring system mainly comprises field devices such as a communication node, a temperature and humidity sensor, a vibration sensor, a PLC (programmable logic controller), a camera and a roller device, wherein the devices are communicated in a 5G mode, and the intelligent monitoring system is responsible for monitoring and uploading field working conditions, roller conditions, thermal imaging and the like and issuing instructions according to the upper layer to execute corresponding decisions.
Edge calculation layer: the intelligent TSN gateway is mainly composed of TSN intelligent gateways, the gateways are connected through a TSN backbone network, each TSN intelligent gateway has strong computing power and can execute some basic computing activities, meanwhile, the TSN intelligent gateways are responsible for managing adjacent field nodes according to physical positions of the TSN intelligent gateways, collecting data and processing, and the TSN intelligent gateways have the functions of edge computing nodes under the framework. Data communication is carried out between the industrial field layer and the edge computing layer through a 5G technology, field devices managed by the same TSN intelligent gateway share frequency spectrum resources, and the field devices managed by different TSN intelligent gateways do not have resource competition relations. After the field data is generated, the field data can only be injected into the TSN through the TSN intelligent gateway managing the area, namely, the starting point of injecting each slice data stream into the TSN is fixed.
A fine-grained scheduling method for virtual resources is shown in fig. 4 and fig. 5, and includes the following steps:
step 1: data generated by the field device is classified into high-priority slice data and low-priority slice data according to slice priority.
And 2, step: the industrial field time frequency Resource is divided into time frequency Resource Blocks (RBs), each RB is a minimum irrevocable unit, the corresponding frequency band is the minimum bandwidth which accords with the Nyquist interval, and the corresponding time period is 2 OFDM symbol intervals.
And step 3: as shown in FIG. 2, when the upper application slice is issued, the corresponding field device is triggered and data belonging to the slice is generated, the priority of the data is consistent with that of the application slice, and the data is processed according to the upper age limit A of each slice E2E The tiling uses the field time frequency resource block, the tiling can be carried out in the time domain with lower time delay requirement, and the tiling can be carried out in the frequency domain with higher time delay requirement.
And 4, step 4: as shown in fig. 2, since the high-priority slice data has a high requirement on the delay, it is only allowed to tile in the frequency domain, and it only occupies a time period of one RB in the time domain, for this reason, when the high-priority slice data arrives, it can preempt the low-priority slice data resources that have already been tiled, and the preempted low-priority slice data is transmitted after the transmission of the high-priority slice data is completed, so that the transmission delay in the 5G network is correspondingly prolonged.
And 5: as shown in FIG. 3, the age of the data linearly increases with time since the data is generated in the field, and the age A of each slice of data in the 5G network can be obtained after the data is transmitted 5G According to the upper age limit A of each slice E2E And its age A in the 5G network 5G Fine-grained priority adjustment is performed by adopting the following formula:
step 6: setting the priority of each VNF belonging to a slice to p TSN That is, the TSN queue priority to which data needs to be injected when the VNF maps the TSN VM, and the 5G-TSN full-flow age of the slice can be obtained by completing the sequential mapping of all VNFs, so that the end-to-end on-demand delivery of the field data to the remote end is completed.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. A5G-TSN industrial heterogeneous virtual network architecture is characterized by comprising an industrial field layer, an edge computing layer and an SDN controller;
edge calculation layer: the method comprises the following steps of virtualizing a TSN intelligent gateway of an edge computing layer into a virtual machine with a TSN function by adopting an NFV technology, wherein the virtual machine has the functions of a physical TSN intelligent gateway: 5G micro base station and heterogeneous protocol conversion;
an SDN controller: the centralized control is deployed on a TSN intelligent gateway supporting the SDN technology of an edge computing layer, and is combined with the NFV technology to schedule and manage different QoS network slices belonging to different industrial applications.
2. The 5G-TSN industrial heterogeneous virtual network architecture of claim 1, wherein devices of the industrial site layer are tiled in a network slice using 5G time-frequency resource blocks, field devices managed by a same TSN smart gateway share spectrum resources, and there is no resource contention relationship between field devices managed by different TSN smart gateways.
3. The 5G-TSN industrial heterogeneous virtual network architecture according to claim 1, wherein the field data can only be injected into the TSN through the TSN intelligent gateway managing the local area after being generated, that is, the starting point of injecting each slice data stream into the TSN (TSN intelligent gateway of wireless data injection TSN) is fixed.
4. The 5G-TSN industrial heterogeneous virtual network architecture of claim 1, wherein the 5G communication network is a virtual depiction of a physical 5G communication network, upper layer applications are transmitted in the 5G-TSN industrial heterogeneous network in a network slice form composed of VNFs in sequence, and data streams corresponding to slices use field resource block time frequencies in a tiled manner; the TSN backbone network is a virtual depiction of a physical TSN network, each TSN intelligent gateway is virtualized into a virtual machine with the function of a TSN intelligent gateway, the virtual machine has computing capacity and caching capacity, after an application slice reaches the TSN network, an internal VNF maps the performance of the combined TSN VM to the TSN VM in sequence, the resources of the TSN VM are occupied, and only after all VNFs belonging to one network slice are mapped, the application can be delivered to a remote end through the TSN backbone network.
5. The 5G-TSN industrial heterogeneous virtual network architecture of claim 1, wherein for a data stream requirement in an industrial scenario for real-time sampling, an information freshness AoI index is introduced to perform information age measurement on a sliced data stream, data starts to grow from a field generation time point of AoI, and stops growing after being transmitted to a remote end point of AoI through a 5G network and a TSN network.
6. The 5G-TSN industrial heterogeneous virtual network architecture of claim 1, wherein slices belonging to different applications and their corresponding data streams have different priorities, such that different slices have different end-to-end upper age bounds A E2E And the 5G-TSN industrial heterogeneous virtual network carries out on-demand scheduling on the multi-priority slice data stream according to the age upper limit of each slice.
7. A fine-grained scheduling method for 5G-TSN industrial heterogeneous virtual resources is characterized by comprising the following steps:
step 1, dividing data generated by field equipment into high-priority slice data and low-priority slice data according to slice priorities;
step 2, dividing industrial field time frequency resources into time frequency Resource Blocks (RBs), wherein each RB is a minimum irreparable unit, a corresponding frequency band is a minimum bandwidth which accords with a Nyquist interval, and a corresponding time period is a plurality of OFDM symbol intervals;
step 3, when the upper application slice is issued, triggering the corresponding field device and generating the data belonging to the slice, wherein the priority of the data is consistent with that of the application slice, and the upper age limit A of each slice is determined according to the self age limit of the slice E2E The tiling uses the field time-frequency resource block, the tiling can be carried out in the time domain with lower requirement on the time delay, and the tiling can be carried out in the frequency domain with higher requirement on the time delay; because the high-priority slice data has high requirement on time delay, the high-priority slice data is only allowed to be tiled in a frequency domain, and only occupies a time period of one RB in a time domain, and when the high-priority slice data arrives, the low-priority slice data resources which are already tiled can be preempted;
step 4, the age of the data linearly increases along with the time after the data are generated on site, and the data can be obtained after the data are transmittedAge a of each slice data in 5G network 5G According to the upper age limit A of each slice E2E And its age A in the 5G network 5G Fine-grained priority adjustment is performed as follows:
step 5, setting the priority of each VNF belonging to the slice to p TSN That is, the TSN queue priority to which data needs to be injected when the VNF maps the TSN VM, and after all VNFs are mapped to the virtual TSN network in sequence, the 5G-TSN full-flow age of the slice can be obtained, and end-to-end on-demand delivery of field data to a remote end is completed.
8. The fine-grained scheduling method for 5G-TSN industrial heterogeneous virtual resources of claim 7, wherein in the step 1, the real-time requirement of the low-priority slice data is lower than that of the high-priority slice data, but the real-time requirements of different data of the low-priority slice are different, and the low-priority slice data is tiled to use time-frequency resource blocks.
9. The fine-grained scheduling method for 5G-TSN industrial heterogeneous virtual resources according to claim 7, wherein the high-priority slice data in the step 4 preempts the low-priority data, so that the non-waiting fast forwarding can be realized in a 5G network; and transmitting the preempted low-priority slice data after the transmission of the high-priority slice data is finished, and correspondingly prolonging the transmission delay in the 5G network.
10. The fine-grained scheduling method for 5G-TSN industrial heterogeneous virtual resources of claim 7, wherein in the step 5 of fine-grained QoS mapping, original two priority levels of fine-grained are divided into 8 priority levels by a queue injection mode, and an elastic transmission service is provided based on TSN network characteristics.
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