CN117749721A - Static schedule generation and optimization method and system for time triggered service - Google Patents
Static schedule generation and optimization method and system for time triggered service Download PDFInfo
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Abstract
The invention provides a static schedule generating and optimizing method and a system for time triggering service, comprising the following steps: step S1: establishing a time triggering service scheduling model according to the network topology structure and the time triggering service information; step S2: solving and optimizing the scheduling model by using a heuristic algorithm; the heuristic algorithm comprises: scheduling a transmission time for each time-triggered service in a monotonically increasing rate; the tuning results are optimized using a tabu search algorithm. The invention combines the quick characteristic of the heuristic rule and the global optimization characteristic of the meta heuristic algorithm, and can obtain the scheduling result with smaller message delay in a shorter time compared with the time-triggered message scheduling algorithm based on the SMT solver which is widely used at present.
Description
Technical Field
The invention relates to the technical field of network communication, in particular to a static schedule generation and optimization method and system for time trigger service.
Background
Because the conventional ethernet is mainly suitable for event triggering, and cannot guarantee delay and jitter of data, many researches based on the conventional ethernet need to be improved in real-time performance. The time triggered communication provides deterministic transmission for data in the network, ensures that the data has fixed time delay and jitter, and can make up the defects of the traditional Ethernet. The time trigger message needs to pre-configure the transmission time point of the message under a global unified time to avoid network congestion, and the static scheduling time table solves the problem that different messages occupy the same communication link in a time sharing way.
The most widely applied scheduling table generating algorithm is an SMT algorithm-based scheduling table generating algorithm, namely an SMT solver is used for solving, but the algorithm is too slow in solving in a complex network and a scene with large-scale traffic, and results which cannot be solved often appear.
In chinese patent document with publication number CN116170108A, a time triggered service schedule generating method suitable for through switching is disclosed, comprising: the scheduling planning problem on the multi-link is converted into the scheduling planning problem irrelevant to the link, so that the time-triggered TT service link information is simplified, and the solving complexity of the time-triggered TT service scheduling planning problem is reduced.
In the chinese patent document with publication number CN114285541B, a method for generating an ethernet schedule triggered based on a delay error time is disclosed, which includes: the time triggering Ethernet scheduling table is generated under the condition of considering time synchronization errors and error jitter, so that the end-to-end time delay of TT messages in an actual network is reduced, and the reliability of the time triggering Ethernet is ensured.
In chinese patent document with publication number CN115412191a, a schedule generating method based on time triggered ethernet is disclosed, comprising: and determining a basic communication period of the system according to the TT frame period of the highest priority, reserving bandwidth according to the maximum number of RC messages in the basic communication period on bandwidth allocation in the basic communication, ensuring that the RC messages in each basic period meet the constraint of message period and communication time delay, and finally adjusting the communication quantity of BE messages in the basic period to avoid frame loss.
In chinese patent document publication No. CN114531444B, a method for generating an incremental schedule with decreasing conflict level is disclosed, comprising: constructing a service conflict graph through whether conflicts exist between every two services, acquiring a maximum connected subgraph of the service conflict graph, selecting one maximum connected subgraph, dividing the time-triggered TT services in the selected subgraph into groups, obtaining groups with successively decreasing conflict degrees, performing incremental scheduling on each group, judging whether the unselected maximum connected subgraph exists, if yes, repeating the steps, otherwise, generating a scheduling table.
In the chinese patent document with publication number CN112866398A, a method for generating and dynamically updating a time-triggered ethernet schedule is disclosed, which includes: abstracting link resources as empty boxes, abstracting time triggering tasks as two-dimensional objects, and utilizing the characteristics of non-overlapping boxing problems to meet ordered and collision-free transmission of time triggering data frames, so that the existing mature boxing algorithm can be utilized; the virtual link path is utilized to integrate the communication tasks, and the method for dynamically updating the scheduling table on line is provided, so that the scheduling table work of the current communication tasks can not be influenced.
In the chinese patent document with publication number CN114374640a, a service scheduling method based on time triggered ethernet is disclosed, which includes: according to the service flow parameters, calculating the number of end systems and switches, determining a topological structure, establishing a port connection matrix, and planning the shortest path; and distributing the service in each matrix period, sequencing the service in each basic period, and establishing an overall scheduling table in one matrix period so as to generate the service scheduling tables of all the end nodes and the switches.
Through the investigation of the prior art, the existing time-triggered service scheduling algorithm mostly adopts the following three modes: 1. the solution complexity is reduced through the simplified model, and then the SMT solver is used for solving; 2. converting the message scheduling problem into a boxing problem, and solving by using a mature boxing algorithm; 3. and sequencing the service priority according to a rule of periodic increment, and planning the transmission time one by one. However, the former two ways cannot fundamentally solve the problem of high complexity, with the increase of scale, the solution of the model is still difficult, and the forward search mechanism of the third planning way is not very friendly to the time delay of the message, which may cause the message to wait for too long in the switch to increase the storage burden of the switch and even cause the scheduling failure.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a static schedule generating and optimizing method and system for time triggering service.
The static schedule generating and optimizing method for time triggering service provided by the invention comprises the following steps:
step S1: establishing a time triggering service static scheduling model according to the network topology structure and the time triggering service information;
step S2: solving and optimizing the scheduling model by using a heuristic algorithm to obtain a time-triggered service static scheduling table;
the heuristic algorithm comprises: scheduling a transmission time for each time-triggered service in a monotonically increasing rate; the tuning results are optimized using a tabu search algorithm.
Preferably, the time triggered business static scheduling model includes: a transmission link model and a time triggered service model;
the transmission link model: from M physical links PL 1 、PL 2 、…、PL M Dividing continuous time in whole dispatching period into N discrete time slots with fixed length to obtain link stateA matrix X;
wherein, when x mn When=1, the link PL is represented m Data transmission is carried out in a time slot n; when x is mn When=0, the link PL is represented m No data transmission occurs in time slot n;
the time triggered business model: comprising I periodic time-triggered services f 1 、f 2 、…、f I Each time triggered service is represented by the following tuples:
f i ＝{f i .period,f i .paths,f i .offsets}
wherein f i Period is the transmission period of the time triggered service; f (f) i Paths is a transmission path of time triggered service, and is represented by a link set; f (f) i Offsets are the time offsets of time triggered traffic within its transmission period, denoted by the set of slot numbers.
Preferably, the scheduling period is the least common multiple of all time triggered service periods;
the length of the fixed time slot is determined by the transmission rate and the longest data, and each time slot can accommodate the transmission of the longest data;
the transmission path of the time triggered traffic is determined by a shortest path algorithm.
Preferably, the step S2 includes:
step S2.1: the priority ordering of the time triggering service is carried out in a monotonic rate increasing mode, and the service priority with smaller period is higher;
step S2.2: scheduling a transmission time slot for each service on each link of its path;
step S2.3: optimizing and adjusting the scheduling result by using a tabu search algorithm;
the step S2.2 includes:
step S2.2.1: determining a selectable time slot set of the service on each link according to the constraint condition of scheduling;
step S2.2.2: selecting the time slot closest to the left end in the selectable time slot set as the transmission time slot of the service on the link;
step S2.2.3: steps S2.2.1 and S2.2.2 are repeated to schedule a transmission slot for each service.
Preferably, the constraint condition includes:
no competition constraint: one data link does not transmit a plurality of services at the same time, and the time slots used by the link are removed by the optional time slot set;
path-dependent constraints: the scheduling time on the next data link must be after the previous one, and the set of selectable time slots needs to remove time slots smaller than the time slots selected by the previous data link;
maximum delay constraint: the associated traffic has to complete the transmission before the maximum delay and the set of alternative slots has to remove slots larger than the maximum delay.
The static schedule generating and optimizing system for time triggering service provided by the invention comprises the following components:
module M1: establishing a time triggering service static scheduling model according to the network topology structure and the time triggering service information;
module M2: solving and optimizing the scheduling model by using a heuristic algorithm to obtain a time-triggered service static scheduling table;
the heuristic algorithm comprises: scheduling a transmission time for each time-triggered service in a monotonically increasing rate; the tuning results are optimized using a tabu search algorithm.
Preferably, the time triggered business static scheduling model includes: a transmission link model and a time triggered service model;
the transmission link model: from M physical links PL 1 、PL 2 、…、PL M Dividing continuous time in the whole dispatching period into N discrete time slots with fixed length to obtain a link state matrix X;
wherein, when x mn When=1, the link PL is represented m Data transmission is carried out in a time slot n; when x is mn When=0, the link PL is represented m No data transmission occurs in time slot n;
the time triggered business model: comprising I periodic time-triggered services f 1 、f 2 、…、f I Each time triggered service is represented by the following tuples:
f i ＝{f i .period,f i .paths,f i .offsets}
wherein f i Period is the transmission period of the time triggered service; f (f) i Paths is a transmission path of time triggered service, and is represented by a link set; f (f) i Offsets are the time offsets of time triggered traffic within its transmission period, denoted by the set of slot numbers.
Preferably, the scheduling period is the least common multiple of all time triggered service periods;
the length of the fixed time slot is determined by the transmission rate and the longest data, and each time slot can accommodate the transmission of the longest data;
the transmission path of the time triggered traffic is determined by a shortest path algorithm.
Preferably, the module M2 comprises:
module M2.1: the priority ordering of the time triggering service is carried out in a monotonic rate increasing mode, and the service priority with smaller period is higher;
module M2.2: scheduling a transmission time slot for each service on each link of its path;
module M2.3: optimizing and adjusting the scheduling result by using a tabu search algorithm;
the module M2.2 comprises:
module M2.2.1: determining a selectable time slot set of the service on each link according to the constraint condition of scheduling;
module M2.2.2: selecting the time slot closest to the left end in the selectable time slot set as the transmission time slot of the service on the link;
module M2.2.3: the triggering module M2.2.1 and the module M2.2.2 are repeated to schedule a transmission time slot for each service.
Preferably, the constraint condition includes:
no competition constraint: one data link does not transmit a plurality of services at the same time, and the time slots used by the link are removed by the optional time slot set;
path-dependent constraints: the scheduling time on the next data link must be after the previous one, and the set of selectable time slots needs to remove time slots smaller than the time slots selected by the previous data link;
maximum delay constraint: the associated traffic has to complete the transmission before the maximum delay and the set of alternative slots has to remove slots larger than the maximum delay.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a static schedule generating and optimizing method for time triggering service, which integrates the quick characteristic of heuristic rules and the global optimizing characteristic of meta-heuristic algorithm, solves the problem of local optimization of the former, and solves the problem of initial value dependence of the latter. And the scheduling problem of the time-triggered service is solved rapidly by utilizing a rule of monotonic rate increment, and then the scheduling result is optimized by utilizing a tabu search algorithm, so that the message time delay is shortened.
Other advantages of the present invention will be set forth in the description of specific technical features and solutions, by which those skilled in the art should understand the advantages that the technical features and solutions bring.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of time triggered business static scheduling;
fig. 2 is a schematic diagram of a transmission link connection relationship;
fig. 3 is a single service scheduling flow.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present invention.
Example 1
As shown in fig. 1, the present invention provides a static schedule generating and optimizing method for time triggered service, comprising the following steps:
step S1: establishing a time triggering service static scheduling model according to the network topology structure and the time triggering service information;
the time-triggered business static scheduling model comprises the following steps: a transmission link model and a time-triggered service model;
the transmission link model: from M physical links PL 1 、PL 2 、…、PL M Dividing continuous time in the whole dispatching period into N discrete time slots with fixed length to obtain a link state matrix X;
wherein, when x mn When=1, the link PL is represented m With data transmission in slot n, when x mn When=0, the link PL is represented m No data transmission occurs in time slot n;
the scheduling period is the least common multiple of all time-triggered service periods.
The length of the fixed time slots is determined by the transmission rate and the longest data, and each time slot should be able to accommodate the transmission of the longest data.
The time triggered business model: comprising I periodic time-triggered services f 1 、f 2 、…、f I Each time triggered service may be represented by the following tuples:
f i ＝{f i .period,f i .paths,f i .offsets}
wherein f i Period is the transmission period of time triggered service, f i Paths is a transmission path of time triggered traffic, denoted by a link set, f i Offsets are the time offsets of time triggered traffic within its transmission period, denoted by the set of slot numbers.
The transmission path of the time triggered service is determined by a shortest path algorithm.
Step S2: because the SMT solver solves too slowly and often results that can not be solved appear, the invention utilizes heuristic algorithm to solve and optimize the scheduling model, thus obtaining the static scheduling table of the time-triggered service;
specifically, the algorithm comprises the following substeps:
step S2.1: the priority ordering of the time triggering service is carried out in a monotonic rate increasing mode, and the service priority with smaller period is higher;
step S2.2: scheduling a transmission time slot for each service on each link of its path;
the specific operation process of the method is as follows:
1) Determining a selectable time slot set of the service on each link according to the constraint condition of scheduling;
the constraint conditions include:
without competition constraint, one data link can not transmit a plurality of services at the same time, and the optional time slot set needs to remove the time slots used by the link;
the path dependency constraint that the scheduling time on the next data link must be after the previous one, the set of selectable time slots requires the removal of time slots smaller than the selected time slot of the previous data link;
the maximum delay constraint, the related traffic must complete transmission before the maximum delay, and the set of selectable slots requires removal of slots greater than the maximum delay.
2) Selecting the time slot closest to the left end in the selectable time slot set as the transmission time slot of the service on the link;
3) Repeating the steps 1) to 2), and planning a transmission time slot for each service.
Step S2.3: and optimizing and adjusting the scheduling result by using a tabu search algorithm.
The foregoing is a basic embodiment of the present invention, and the following further describes the solution of the present invention by means of a preferred embodiment;
example 2
Example 2 is a preferred example of example 1.
The embodiment discloses a static schedule generating and optimizing method for time triggering service, which comprises the following steps:
step S1: establishing a time triggering service static scheduling model according to the network topology structure and the time triggering service information;
the time-triggered business static scheduling model comprises the following steps: a transmission link model and a time-triggered service model;
referring to fig. 2, in this embodiment, a transmission network is constructed by using a switching topology, the network includes 5 links, and the time trigger service periods are respectively 1ms, 4ms, 5ms and 20ms, so that the whole scheduling period is 20ms, the transmission rate is 1000Mbps, the maximum data length is 1518 bytes, the slot length is 20us, and the slot number is 1-1000.
Link state matrix X:
in the initial condition, the link state matrix is an all 0 matrix.
The shortest path algorithm can know that the transmission path from A to C is [ PL 1 ，PL 3 ，PL 4 ]。
The period is 20ms, and the time-triggered service available tuple fi= {20, [ PL ] sent from node a to node C 1 ，PL 3 ，PL 4 ]Fi.offsets }, where f i Offsets are the solution targets.
Step S2: solving and optimizing the scheduling model by using a heuristic algorithm to obtain a time-triggered service static scheduling table;
specifically, the algorithm comprises the following substeps:
step S2.1: the priority ordering of the time triggering service is carried out in a monotonic rate increasing mode, and the service priority with smaller period is higher;
step S2.2: scheduling a transmission time slot for each service on each link of its path;
referring to fig. 3, the specific operation procedure of this step is as follows:
1) Determining a selectable time slot set of the service on each data link according to the constraint condition of scheduling;
the constraint conditions include:
without competition constraint, one data link can not transmit a plurality of services at the same time, and the optional time slot set needs to remove the time slots used by the link;
the path dependency constraint that the scheduling time on the next data link must be after the previous one, the set of selectable time slots requires the removal of time slots smaller than the selected time slot of the previous data link;
the maximum delay constraint, the related traffic must complete transmission before the maximum delay, and the set of selectable slots requires removal of slots greater than the maximum delay.
2) Selecting the time slot closest to the left end in the selectable time slot set as the transmission time slot of the service on the link;
3) Repeating the steps 1) to 2), and planning a transmission time slot for each service.
Step S2.3: and optimizing and adjusting the scheduling result by using a tabu search algorithm.
Example 3
The invention also provides a static schedule generating and optimizing system for time-triggered service, which can be realized by executing the flow steps of the static schedule generating and optimizing method for time-triggered service, namely, the skilled person can understand the static schedule generating and optimizing method for time-triggered service as the preferred implementation mode of the static schedule generating and optimizing system for time-triggered service.
The static schedule generating and optimizing system for time triggering service provided by the invention comprises the following components: module M1: establishing a time triggering service static scheduling model according to the network topology structure and the time triggering service information; module M2: solving and optimizing the scheduling model by using a heuristic algorithm to obtain a time-triggered service static scheduling table; the heuristic algorithm comprises: scheduling a transmission time for each time-triggered service in a monotonically increasing rate; the tuning results are optimized using a tabu search algorithm.
The time-triggered business static scheduling model comprises the following steps: a transmission link model and a time triggered service model;
the transmission link model: from M physical links PL 1 、PL 2 、…、PL M Dividing continuous time in the whole dispatching period into N discrete time slots with fixed length to obtain a link state matrix X;
wherein, when x mn When=1, the link PL is represented m Data transmission is carried out in a time slot n; when x is mn When=0, the link PL is represented m No data transmission occurs in time slot n;
the time triggered business model: comprising I periodic time-triggered services f 1 、f 2 、…、f I Each time triggered service is represented by the following tuples:
f i ＝{f i .period,f i .paths,f i .offsets}
wherein f i Period is the transmission period of the time triggered service; f (f) i Paths is a transmission path of time triggered service, and is represented by a link set; f (f) i Offsets are the time offsets of time triggered traffic within its transmission period, denoted by the set of slot numbers.
The scheduling period is the least common multiple of all time trigger service periods; the length of the fixed time slot is determined by the transmission rate and the longest data, and each time slot can accommodate the transmission of the longest data; the transmission path of the time triggered traffic is determined by a shortest path algorithm.
The module M2 includes: module M2.1: the priority ordering of the time triggering service is carried out in a monotonic rate increasing mode, and the service priority with smaller period is higher; module M2.2: scheduling a transmission time slot for each service on each link of its path; module M2.3: optimizing and adjusting the scheduling result by using a tabu search algorithm;
the module M2.2 comprises: module M2.2.1: determining a selectable time slot set of the service on each link according to the constraint condition of scheduling; module M2.2.2: selecting the time slot closest to the left end in the selectable time slot set as the transmission time slot of the service on the link; module M2.2.3: the triggering module M2.2.1 and the module M2.2.2 are repeated to schedule a transmission time slot for each service.
The constraint conditions include: no competition constraint: one data link does not transmit a plurality of services at the same time, and the time slots used by the link are removed by the optional time slot set; path-dependent constraints: the scheduling time on the next data link must be after the previous one, and the set of selectable time slots needs to remove time slots smaller than the time slots selected by the previous data link; maximum delay constraint: the associated traffic has to complete the transmission before the maximum delay and the set of alternative slots has to remove slots larger than the maximum delay.
Those skilled in the art will appreciate that the systems, apparatus, and their respective modules provided herein may be implemented entirely by logic programming of method steps such that the systems, apparatus, and their respective modules are implemented as logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc., in addition to the systems, apparatus, and their respective modules being implemented as pure computer readable program code. Therefore, the system, the apparatus, and the respective modules thereof provided by the present invention may be regarded as one hardware component, and the modules included therein for implementing various programs may also be regarded as structures within the hardware component; modules for implementing various functions may also be regarded as being either software programs for implementing the methods or structures within hardware components.
The foregoing describes specific embodiments of the present invention. It is to be understood that the invention is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the invention. The embodiments of the present application and features in the embodiments may be combined with each other arbitrarily without conflict.
Claims (10)
1. A static schedule generation and optimization method for time triggered services, comprising:
step S1: establishing a time triggering service static scheduling model according to the network topology structure and the time triggering service information;
step S2: solving and optimizing the scheduling model by using a heuristic algorithm to obtain a time-triggered service static scheduling table;
the heuristic algorithm comprises: scheduling a transmission time for each time-triggered service in a monotonically increasing rate; the tuning results are optimized using a tabu search algorithm.
2. The static schedule generating and optimizing method for time-triggered service according to claim 1, wherein the time-triggered service static schedule model comprises: a transmission link model and a time triggered service model;
the transmission link model: from M physical links PL 1 、PL 2 、…、PL M Dividing continuous time in the whole dispatching period into N discrete time slots with fixed length to obtain a link state matrix X;
wherein, when x mn When=1, the link PL is represented m Data transmission is carried out in a time slot n; when x is mn When=0, tableLink PL m No data transmission occurs in time slot n;
the time triggered business model: comprising I periodic time-triggered services f 1 、f 2 、…、f I Each time triggered service is represented by the following tuples:
f i ＝{f i .period,f i .paths,f i .offsets}
wherein f i Period is the transmission period of the time triggered service; f (f) i Paths is a transmission path of time triggered service, and is represented by a link set; f (f) i Offsets are the time offsets of time triggered traffic within its transmission period, denoted by the set of slot numbers.
3. The static schedule generation and optimization method for time-triggered service according to claim 1, wherein the scheduling period is a least common multiple of all time-triggered service periods;
the length of the fixed time slot is determined by the transmission rate and the longest data, and each time slot can accommodate the transmission of the longest data;
the transmission path of the time triggered traffic is determined by a shortest path algorithm.
4. The static schedule generating and optimizing method for time triggered service according to claim 1, wherein said step S2 comprises:
step S2.1: the priority ordering of the time triggering service is carried out in a monotonic rate increasing mode, and the service priority with smaller period is higher;
step S2.2: scheduling a transmission time slot for each service on each link of its path;
step S2.3: optimizing and adjusting the scheduling result by using a tabu search algorithm;
the step S2.2 includes:
step S2.2.1: determining a selectable time slot set of the service on each link according to the constraint condition of scheduling;
step S2.2.2: selecting the time slot closest to the left end in the selectable time slot set as the transmission time slot of the service on the link;
step S2.2.3: steps S2.2.1 and S2.2.2 are repeated to schedule a transmission slot for each service.
5. The static schedule generation and optimization method for time-triggered business of claim 4, wherein the constraint condition comprises:
no competition constraint: one data link does not transmit a plurality of services at the same time, and the time slots used by the link are removed by the optional time slot set;
path-dependent constraints: the scheduling time on the next data link must be after the previous one, and the set of selectable time slots needs to remove time slots smaller than the time slots selected by the previous data link;
maximum delay constraint: the associated traffic has to complete the transmission before the maximum delay and the set of alternative slots has to remove slots larger than the maximum delay.
6. A static schedule generation and optimization system for time triggered services, comprising:
module M1: establishing a time triggering service static scheduling model according to the network topology structure and the time triggering service information;
module M2: solving and optimizing the scheduling model by using a heuristic algorithm to obtain a time-triggered service static scheduling table;
the heuristic algorithm comprises: scheduling a transmission time for each time-triggered service in a monotonically increasing rate; the tuning results are optimized using a tabu search algorithm.
7. The static schedule generation and optimization system for time-triggered services of claim 6, wherein the time-triggered services static schedule model comprises: a transmission link model and a time triggered service model;
the transmission link model: from M physical links PL 1 、PL 2 、…、PL M Composition, to be wholeThe continuous time in each scheduling period is divided into N discrete time slots with fixed length, and a link state matrix X is obtained;
wherein, when x mn When=1, the link PL is represented m Data transmission is carried out in a time slot n; when x is mn When=0, the link PL is represented m No data transmission occurs in time slot n;
the time triggered business model: comprising I periodic time-triggered services f 1 、f 2 、…、f I Each time triggered service is represented by the following tuples:
f i ＝{f i .period,f i .paths,f i .offsets}
wherein f i Period is the transmission period of the time triggered service; f (f) i Paths is a transmission path of time triggered service, and is represented by a link set; f (f) i Offsets are the time offsets of time triggered traffic within its transmission period, denoted by the set of slot numbers.
8. The static schedule generation and optimization system for time-triggered service of claim 6 wherein the scheduling period is the least common multiple of all time-triggered service periods;
the length of the fixed time slot is determined by the transmission rate and the longest data, and each time slot can accommodate the transmission of the longest data;
the transmission path of the time triggered traffic is determined by a shortest path algorithm.
9. The static schedule generating and optimizing system for time-triggered business according to claim 6, wherein said module M2 comprises:
module M2.1: the priority ordering of the time triggering service is carried out in a monotonic rate increasing mode, and the service priority with smaller period is higher;
module M2.2: scheduling a transmission time slot for each service on each link of its path;
module M2.3: optimizing and adjusting the scheduling result by using a tabu search algorithm;
the module M2.2 comprises:
module M2.2.1: determining a selectable time slot set of the service on each link according to the constraint condition of scheduling;
module M2.2.2: selecting the time slot closest to the left end in the selectable time slot set as the transmission time slot of the service on the link;
module M2.2.3: the triggering module M2.2.1 and the module M2.2.2 are repeated to schedule a transmission time slot for each service.
10. The static schedule generation and optimization system for time-triggered services of claim 9, wherein said constraints comprise:
no competition constraint: one data link does not transmit a plurality of services at the same time, and the time slots used by the link are removed by the optional time slot set;
path-dependent constraints: the scheduling time on the next data link must be after the previous one, and the set of selectable time slots needs to remove time slots smaller than the time slots selected by the previous data link;
maximum delay constraint: the associated traffic has to complete the transmission before the maximum delay and the set of alternative slots has to remove slots larger than the maximum delay.
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