Asynchronous flow scheduling method of 5G + TSN fusion network

Abstract

The invention discloses an asynchronous traffic scheduling method for a 5G + TSN fusion network, and relates to the technical field of deterministic real-time transmission of computer networks, and the method comprises the following steps: S1, in the 5G and TSN fusion network, firstly, a central controller collects the overall information of the network through a network control protocol; s2, the central controller plans a route, then runs an asynchronous traffic scheduling model according to the planned route to obtain a scheduling result of the asynchronous traffic, and minimizes the consumption of network resources while meeting the transmission requirement of hard real-time traffic; and S3, calculating the configuration information of each network device according to the scheduling result obtained in the previous step. According to the invention, the problem of how to realize deterministic transmission of the asynchronous traffic in the TSN is solved through the asynchronous deterministic access mechanism; and the asynchronous traffic scheduling method provided by the invention provides a solution for scheduling traffic allocation resources when the asynchronous deterministic access mechanism is applied.

Description

Technical Field

[0001] The present invention relates to the technical field of deterministic real-time transmission of computer networks, and specifically to an asynchronous traffic scheduling method for a 5G+TSN fused network. Background Art

[0002] The fifth generation of mobile communication technology, referred to as 5G, and the time-sensitive network, referred to as TSN, are important technologies for realizing flexible manufacturing and mobile applications. TSN is based on standard Ethernet and introduces a time-triggered transmission mechanism in IEEE802.1Qbv. In industrial control, hard real-time traffic is generally modeled as periodic traffic. This mechanism periodically reserves transmission resources on the transmission link for such periodic data flows, that is, plans the sending time of each data packet on the routing device. Therefore, clock synchronization of the entire network is required. One of the three major technical visions of 5G is to achieve ultra-reliable and low-latency transmission. For this purpose, semi-persistent scheduling is introduced, which is similar to the time-triggered transmission of TSN. It also reserves periodic transmission resources for data packets, making it very suitable for networking with TSN to achieve more flexible data transmission. In the existing traffic scheduling of 5G and TSN converged networks, the common practice is to estimate the worst latency of traffic in the 5G network and reserve transmission resources in the TSN network according to the 5G worst latency, so that traffic accesses the TSN network according to the worst latency. This solution has the following two problems: (1) The worst latency is difficult to estimate; (2) It may be difficult to meet the end-to-end latency requirements of traffic according to the worst latency. Therefore, treating the traffic accessing TSN from the 5G network as traffic sent by asynchronous terminals and performing asynchronous traffic scheduling is a very promising solution.

[0003] In the prior art, such as the "A transmission deterministic access method for asynchronous terminals" with Chinese patent number: CN202110583698.4, it includes two mechanisms, one is the asynchronous to synchronous mechanism, and the other is the delay adaptation mechanism. Specifically, after the first switch receives the message, it stays at the nearest sending time point before sending it out. The message is transmitted to the edge switch in the synchronization domain according to the time-triggered transmission mechanism of TSN. The edge switch keeps the message for a period of time before sending it to the receiving terminal. The delayed sending time is equal to the difference between the sending period of the data stream and the residence time of the message, so as to eliminate the uncertainty of the end-to-end delay.

[0004] However, the current deterministic access method for asynchronous terminals is applied in the networking scheduling of 5G and TSN, and there are two unresolved issues:

[0005] (1) How to allocate the resource period T for each flow: The deterministic access method will directly introduce T into the TSN latency of a flow. In order to reduce the TSN latency, you can choose to reduce T, that is, provide more bandwidth resources to this flow, but the resources left for other flows will also be reduced accordingly. Faced with complex heterogeneous traffic in the network and its latency requirements, how to comprehensively consider allocating an appropriate resource period T to each flow?

[0006] (2) How to coordinate 5G and TSN network resources: In a heterogeneous network of 5G and TSN, the end-to-end latency includes both TSN latency and 5G latency. If the resource allocation in the 5G network changes, it will also affect the resource scheduling of TSN. For example, if data packets occupy more frequency resources and consume fewer time domain resources, the 5G latency will be reduced, and the scheduling pressure on the TSN network will be reduced, but more frequency resources will be consumed. In the face of complex traffic in the network, how to coordinate the allocation of 5G and TSN network resources? Summary of the invention

[0007] The purpose of the present invention is to provide an asynchronous traffic scheduling method for a 5G+TSN converged network to solve the problems of how to allocate the resource period T of each flow and how to coordinate 5G and TSN network resources proposed in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solution: an asynchronous traffic scheduling method for a 5G+TSN converged network, comprising the following steps:

[0009] S1. In the converged network of 5G and TSN, the central controller first collects the overall information of the network through the network control protocol;

[0010] S2. The central controller plans the route, and then runs the asynchronous traffic scheduling model according to the planned route to obtain the scheduling result of the asynchronous traffic, and minimizes the consumption of network resources while meeting the transmission requirements of hard real-time traffic;

[0011] S3. Calculate the configuration information of each network device based on the scheduling result obtained in the previous step. The configuration information includes the queue access control list of the TSN switch, the resource time configuration of the gateway and edge switch in the asynchronous access deterministic mechanism.

[0012] Preferably, in step S2, the asynchronous traffic scheduling model includes a 5G network resource scheduling model and a TSN network resource scheduling model.

[0013] Preferably, the transmission resources in the 5G network resource scheduling model are located in two dimensions: time domain and frequency domain. In the 5G resource grid, the basic scheduling unit occupies 1 resource block RB in frequency and a transmission time interval TTI in time domain. One scheduling unit can carry a certain number of byte transmissions.

[0014] Preferably, it is assumed that the RB set that can be used by the 5G network is expressed as F = {1, 2, .., k max}, where k max Represents the number of RBs, i.e. l∈L in 5G networks 5GS , the resources allocated to a flow are composed of the following decision variables:

[0015]

[0016]

[0017]

[0018] in, For the resource cycle, is the start time of the resource, is the duration of the resource, Represents the flow f i Whether to occupy the kth RB of 5G link l;

[0019] The lowest common multiple of the traffic cycles is defined as the macrocycle, denoted by T 5GS , the formula is as follows:

[0020] T 5GS =LCM({f i .period|f i ∈F});

[0021] In the formula, f i .period is the flow period of the traffic.

[0022] Preferably, the decision variables need to satisfy the following constraints: transmission opportunity constraint, transmission resource constraint, OFDMA constraint and RB constraint.

[0023] Preferably, in the TSN network resource scheduling model, l∈L TSN , the resources allocated to a flow are composed of the following decision variables:

[0024]

[0025]

[0026] in, and are decision making variables, It is only related to the link rate and the packet size of the traffic;

[0027] The lowest common multiple of resource cycles of all flows in TSN is T TSN ,Right now:

[0028] T TSN =LCM({T i |f i ∈F});

[0029] The above decision variables need to satisfy the following constraints: window constraint, frame constraint, transmission order constraint, TDMA constraint, frame isolation constraint and end-to-end delay constraint.

[0030] Preferably, the number of TDMA constraints and frame isolation constraints is determined using a linearization method based on an optional periodic list;

[0031] The specific process is as follows: The minimum resource cycle that TSN can provide is minP. For a flow f i For example, the resource cycles that can be selected can only be selected from the list list i =[minP,minP*2,…,T i,max ], where the length of the list is s i , parameter T i,max The following relations are satisfied:

[0032]

[0033]

[0034]

[0035] Then for each flow f i Introducing i A binary variable {b i,j |j=0,1,…,s i -1}, and introduce the following constraints:

[0036]

[0037]

[0038] The final resource cycle can be expressed as:

[0039]

[0040] After adopting this linearization method, the set T max ={T i,max |f i The macrocycle of ∈F} is the set T = {Ti |f i ∈F} is an integer multiple of the macrocycle, so the check interval of the constraint can be changed from Expand to And the range is fixed.

[0041] Preferably, in step S2, the meeting of the transmission requirements of hard real-time traffic while minimizing the consumption of network resources includes a 5G network part and a TSN network part;

[0042] The 5G network part minimizes the number of RBs allocated for hard real-time critical traffic, and the formula is as follows:

[0043]

[0044] The TSN network part provides a smaller T for traffic, so less time domain resources can be used for low-priority traffic, thus maximizing the T allocated to the data flow, that is:

[0045]

[0046] In summary, by changing the optimization direction and adding the weight factor γ, the final optimization goal is:

[0047]

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. The present invention solves the problem of how to achieve deterministic transmission of asynchronous traffic in TSN through an asynchronous deterministic access mechanism. The asynchronous traffic scheduling method of the present invention provides a solution for allocating resources for traffic and scheduling when applying the asynchronous deterministic access mechanism.

[0050] 2. The present invention models end-to-end transmission, comprehensively considers the network and resource characteristics of 5G and TSN, the delay experienced by traffic in 5G and TSN, and leaves as many resources as possible for low-priority traffic while meeting traffic transmission requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 Schematic diagram of the time-triggered transmission process in an ideal 5G and TSN converged network;

[0052] Figure 2 A schematic diagram of a deterministic access solution for an asynchronous terminal of the present invention;

[0053] Figure 3 This is a schematic diagram of 5G network transmission resources of the present invention;

[0054] Figure 4 It is a schematic diagram of the implementation of the asynchronous traffic scheduling method of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the implementation regulations described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The conventions of symbol marking in the present invention are as follows without loss of generality: Figure 1 The network topology shown in the figure, in which the 5G network contains only one cell. The traffic considered is transmitted from the 5G network to the receiving end through the TSN network. The two networks can work asynchronously. The TSN network can be regarded as an undirected graph G(V,E), in which the node set V contains TSN end devices, switches and gateways, and the edge set E contains physical wired links. Since TSN uses full-duplex Ethernet links, we use,v1,v2- to represent a transmission direction, forming a set L TSN , for l∈L TSN , l,0-represents the sending node of the link, l,1-represents the receiving node. Similarly, in the 5G network, there is also such a transmission direction, namely the 5G uplink, which constitutes the set L 5GS ; All flows form a set F, each flow f i ∈F is completely determined by a five-tuple: <f i .src,f i .dst,f i .period,f i .length,f i .delay>, which represent the sending node, receiving node, flow period, packet length, and end-to-end delay requirements of the flow. i ∈F, whose route is determined in advance where h i Represents the number of hops.

[0057] See also Figure 1 - Figure 4 The present invention provides a technical solution: an asynchronous traffic scheduling method for a 5G+TSN fusion network, comprising the following steps:

[0058] Step 1: In the converged network of 5G and TSN, the central controller first collects the overall information of the network through the network control protocol; this information includes but is not limited to the channel conditions and frequency resources in the 5G network, the network topology and link rate of the TSN network, etc.

[0059] Step 2: The central controller plans the route, and then runs the asynchronous traffic scheduling model according to the planned route to obtain the scheduling result of the asynchronous traffic, and minimize the consumption of network resources while meeting the transmission requirements of hard real-time traffic;

[0060] The asynchronous traffic scheduling model includes a 5G network resource scheduling model and a TSN network resource scheduling model;

[0061] In the 5G network resource scheduling model, transmission resources are located in two dimensions: time domain and frequency domain. In the 5G resource grid, the basic scheduling unit occupies one resource block RB in frequency and one transmission time interval TTI in time domain. One scheduling unit can carry a certain number of bytes for transmission. Assume that the RB set that can be used by the 5G network is expressed as F = {1,2,..,k max}, where k max Represents the number of RBs, i.e. l∈L in 5G networks 5GS , the resources allocated to a flow are composed of the following decision variables:

[0062]

[0063]

[0064]

[0065] in, For the resource cycle, is the start time of the resource, is the duration of the resource, Represents the flow f i Whether to occupy the kth RB of 5G link l;

[0066] The lowest common multiple of the traffic cycles is defined as the macrocycle, denoted by T 5GS , the formula is as follows:

[0067] T 5GS =LCM({f i .period|f i ∈F});

[0068] In the formula, f i .period is the flow period of the traffic;

[0069] The above decision variables need to satisfy the following constraints: transmission opportunity constraint, transmission resource constraint, OFDMA constraint and RB constraint;

[0070] Specifically: (1) Transmission opportunity constraint: Data packets can only be transmitted at integer times of TTI, and the transmission duration must also be an integer multiple of TTI. For the convenience of modeling, data packets must also be transmitted within one cycle. Therefore:

[0071]

[0072]

[0073]

[0074]

[0075]

[0076]

[0077]

[0078] The variables The meaning is flow f i The TTI number to start sending on 5G link l, Represents the number of TTIs sent continuously;

[0079] (2) Transmission resource constraint: The resources allocated for a data packet should be sufficient to transmit the data. Represents f i The number of bytes that can be transmitted in one TTI on the kth RB on 5G link l is thus:

[0080]

[0081]

[0082]

[0083]

[0084] The above two constraints ensure that the allocated resources are just enough to transmit data;

[0085] (3) OFDMA constraints: The first two constraints ensure the validity of resource allocation for a single stream. The OFDMA constraint ensures that resources between multiple streams do not conflict, that is, an RB-TTI block can be occupied by at most one stream. Therefore:

[0086]

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] in, It means that when the i-th stream and the j-th stream are both transmitted through the k-th RB of the 5G link l (i.e. ), only then the time domain resources of the two streams are constrained not to overlap;

[0093] (4) RB constraint: We introduce the variable To indicate whether the kth RB of 5G link l is allocated to traffic transmission. Specifically, if any traffic is allocated to the kth RB, the indicator variable is set to 1, so:

[0094]

[0095]

[0096] In the TSN network resource scheduling model, l∈L TSN , the resources allocated to a flow consist of the following decision variables:

[0097]

[0098]

[0099] in, and are decision making variables, It is only related to the link rate and the packet size of the traffic;

[0100] The lowest common multiple of resource cycles of all flows in TSN is T TSN ,Right now:

[0101] T TSN =LCM({T i |f i ∈F});

[0102] The above decision variables need to satisfy the following constraints: window constraint, frame constraint, transmission order constraint, TDMA constraint, frame isolation constraint and end-to-end delay constraint;

[0103] Specifically, (1) Window constraint: The resource period reserved by TSN is the same for each link in the route and cannot be larger than the period of the flow itself. We do not schedule the last hop (i.e., l,1-≠f i.dst, the same below), therefore:

[0104]

[0105]

[0106]

[0107]

[0108] (2) Frame Constraint: The offset of any transmission resource should be non-negative. To simplify, the data packet should be transmitted within the period. Therefore:

[0109]

[0110]

[0111]

[0112]

[0113] (3) Transmission order constraint: A switch in the network can only transmit data packets on the next link after it has completely received the data packet on the previous link. Let ldelay l represents the propagation delay of link l, so:

[0114]

[0115]

[0116]

[0117] (4) TDMA constraints: On a TSN link, reserved transmission time slots cannot overlap with each other and must comply with TDMA constraints. Therefore:

[0118]

[0119]

[0120]

[0121]

[0122]

[0123]

[0124] (5) Frame isolation constraint: The same queue can only store packets from one flow at a time, so:

[0125]

[0126]

[0127]

[0128]

[0129]

[0130] (6) End-to-end delay constraint: End-to-end transmission needs to meet the delay requirement of the traffic. Let T proc represents the base station processing delay, so:

[0131]

[0132]

[0133]

[0134]

[0135] According to the asynchronous deterministic access mechanism:

[0136]

[0137]

[0138] wherein the number of TDMA constraints and frame isolation constraints is determined using a linearization method based on an optional periodic list;

[0139] The specific process is as follows: The minimum resource cycle that TSN can provide is minP. For a flow f i For example, the resource cycles that can be selected can only be selected from the list list i =[minP,minP*2,…,T i,max ], where the length of the list is s i , parameter T i,max The following relations are satisfied:

[0140]

[0141]

[0142]

[0143] Then for each flow f i Introducing i A binary variable {b i,j |j=0,1,…,si -1}, and introduce the following constraints:

[0144]

[0145]

[0146] The final resource cycle can be expressed as:

[0147]

[0148] After adopting this linearization method, the set T max ={T i,max |f i The macrocycle of ∈F} is the set T = {T i |f i ∈F} is an integer multiple of the macrocycle, so the check interval of the constraint can be changed from Expand to And that range is fixed;

[0149] Specifically, the method of meeting the transmission requirements of hard real-time traffic while minimizing the consumption of network resources includes a 5G network part and a TSN network part;

[0150] The 5G network part minimizes the number of RBs allocated for hard real-time critical traffic, and the formula is as follows:

[0151]

[0152] The TSN network part provides a smaller T for traffic, so less time domain resources can be used for low-priority traffic, thus maximizing the T allocated to the data flow, that is:

[0153]

[0154] In summary, by changing the optimization direction and adding the weight factor γ, the final optimization goal is:

[0155]

[0156] Step 3: Calculate the configuration information of each network device based on the scheduling result obtained in the previous step. The configuration information includes but is not limited to the queue access control list of the TSN switch, the resource time configuration of the gateway and edge switch in the asynchronous access deterministic mechanism.

[0157] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An asynchronous traffic scheduling method for a 5G+TSN fusion network, characterized in that: The following steps are involved: S1. In the converged network of 5G and TSN, the central controller first collects the overall information of the network through the network control protocol; S2. The central controller plans the route, and then runs the asynchronous traffic scheduling model according to the planned route to obtain the scheduling result of the asynchronous traffic, and minimizes the consumption of network resources while meeting the transmission requirements of hard real-time traffic; S3. Calculate the configuration information of each network device based on the scheduling result obtained in the previous step. The configuration information includes the queue access control list of the TSN switch, the resource time configuration of the gateway and edge switch in the asynchronous access deterministic mechanism.

2. According to claim 1, the asynchronous traffic scheduling method of the 5G+TSN fusion network is characterized in that: In step S2, the asynchronous traffic scheduling model includes a 5G network resource scheduling model and a TSN network resource scheduling model.

3. According to claim 2, the asynchronous traffic scheduling method of the 5G+TSN fusion network is characterized in that: In the 5G network resource scheduling model, transmission resources are located in two dimensions: time domain and frequency domain. In the 5G resource grid, the basic scheduling unit occupies 1 resource block RB in frequency and a transmission time interval TTI in time domain. One scheduling unit can carry a certain number of bytes for transmission.

4. According to claim 3, the asynchronous traffic scheduling method of the 5G+TSN fusion network is characterized in that: The RB set that can be used by the 5G network is expressed as F = {1, 2, .., k max }, where k ma x represents the number of RBs. In 5G networks, l∈L 5GS , the resources allocated to a flow are composed of the following decision variables: in, For the resource cycle, is the start time of the resource, is the duration of the resource, Represents the flow f i Whether to occupy the kth RB of 5G link l; The lowest common multiple of the traffic cycles is defined as the macrocycle, denoted as The formula is as follows: T 5GS =LCM({f i .period|f i ∈F}); In the formula, f i .period is the flow period of the traffic.

5. According to claim 4, the asynchronous traffic scheduling method of the 5G+TSN fusion network is characterized in that: The decision variables need to satisfy the following constraints: transmission opportunity constraint, transmission resource constraint, OFDMA constraint and RB constraint.

6. The asynchronous traffic scheduling method of a 5G+TSN fusion network according to claim 2, characterized in that: In the TSN network resource scheduling model, l∈L TSN , the resources allocated to a flow consist of the following decision variables: in, and are decision making variables, It is only related to the link rate and the packet size of the traffic; The lowest common multiple of resource cycles of all flows in TSN is T TSN ,Right now: T TSN =LCM({T i |f i ∈F}); The above decision variables need to satisfy the following constraints: window constraint, frame constraint, transmission order constraint, TDMA constraint, frame isolation constraint and end-to-end delay constraint.

7. The asynchronous traffic scheduling method of a 5G+TSN fusion network according to claim 6 is characterized in that: The number of TDMA constraints and frame isolation constraints is determined using a linearization method based on an optional periodic list; The specific process is as follows: The minimum resource cycle that TSN can provide is minP. For a flow f i For example, the resource cycles that can be selected can only be selected from the list list i =[minP,minP*2,…,T i,max ], where the length of the list is s i , parameter T i,max The following relations are satisfied: Then for each flow f i Introducing i binary variable {b i,j |j=0,1,…,s i -1}, and introduce the following constraints: The final resource cycle can be expressed as: After adopting this linearization method, the set T max ={T i,max |f i The macrocycle of ∈F} is the set T = {T i |f i ∈F} is an integer multiple of the macrocycle, so the check interval of the constraint can be changed from Expand to And the range is fixed.

8. The asynchronous traffic scheduling method of a 5G+TSN fusion network according to claim 1, characterized in that: In step S2, the method of satisfying the transmission requirements of hard real-time traffic while minimizing the consumption of network resources includes a 5G network part and a TSN network part; The 5G network part minimizes the number of RBs allocated for hard real-time critical traffic, and the formula is as follows: The TSN network part provides a smaller T for traffic, so less time domain resources can be used for low-priority traffic, thus maximizing the T allocated to the data flow, that is: In summary, by changing the optimization direction and adding the weight factor γ, the final optimization goal is:

Images