CN116055377A - Time-sensitive network traffic scheduling method for power service - Google Patents

Time-sensitive network traffic scheduling method for power service Download PDF

Info

Publication number
CN116055377A
CN116055377A CN202210964931.8A CN202210964931A CN116055377A CN 116055377 A CN116055377 A CN 116055377A CN 202210964931 A CN202210964931 A CN 202210964931A CN 116055377 A CN116055377 A CN 116055377A
Authority
CN
China
Prior art keywords
time
triggered
path
representing
stream
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210964931.8A
Other languages
Chinese (zh)
Inventor
王晔
冯国礼
马润
李勃
马梦轩
张立中
闫舒怡
赵桉
李鸿儒
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Ningxia Electric Power Co Ltd
Information and Telecommunication Branch of State Grid Ningxia Electric Power Co Ltd
Original Assignee
Information and Telecommunication Branch of State Grid Ningxia Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Information and Telecommunication Branch of State Grid Ningxia Electric Power Co Ltd filed Critical Information and Telecommunication Branch of State Grid Ningxia Electric Power Co Ltd
Priority to CN202210964931.8A priority Critical patent/CN116055377A/en
Publication of CN116055377A publication Critical patent/CN116055377A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/38—Flow based routing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/02—Topology update or discovery
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/12—Shortest path evaluation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/12—Shortest path evaluation
    • H04L45/121—Shortest path evaluation by minimising delays
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/18—Loop-free operations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/24—Multipath

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

The invention discloses a time sensitive network flow scheduling method for power service, which provides a K-short path algorithm optimized route plan based on a TAS scheduling mode, provides an improved tabu search preferred algorithm fast scheduling solution flow scheduling scheme, and provides port gate control list calculation. The two heuristic algorithms provided by the invention are tested for multiple times, so that the schedulability, the total end-to-end time delay and the algorithm execution time of the two heuristic algorithms are evaluated for different algorithms, the tabu search algorithm provided by the invention can be solved in a shorter time, the capability of finally meeting the deterministic transmission requirement of time-triggered traffic is obviously stronger than that of the shortest path algorithm, the total transmission time delay of all traffic is minimized, and an effective port gate control list is quickly solved.

Description

Time-sensitive network traffic scheduling method for power service
Technical Field
The invention relates to the technical field of time-sensitive networks, in particular to a time-sensitive network traffic scheduling method for power service.
Background
For a long time, the service types carried by the power communication network and the differentiated requirements thereof are continuously growing, and some power services which are highly sensitive to time delay are difficult to realize real-time monitoring of service states and flexible scheduling of resources, and quick recovery of network influence minimization is also difficult to realize in fault states. The TSN technology is introduced, so that the differentiated requirements of the power service are met, and reliable operation of the service and conflict-free scheduling of time trigger streams are ensured. The control layer in the power service needs to be capable of receiving the information such as the current state of each node and the like, and needs to send control signals to the target for control, and the internet communication technology based on TSN is applied, so that the high-reliability and deterministic service can be provided in the process of coordinated control service scheduling, the control flow information is ensured to be highly sensitive to time, the scheduling task finishes operations such as transmission, processing and response within a specified end-to-end time delay, and the transmission of periodic control flow data and aperiodic best effort data flow in the same network in the scheduling control is realized.
In the TSN technology, an excellent flow scheduling strategy is used for scheduling the flow transmission time in the switch at a specific time as one of key points of the flow scheduling strategy, so that real-time flexible scheduling of time-sensitive power service is guaranteed in a shorter time, and the differentiated requirements of smart grid service are met.
In order to understand the development state of the prior art, the prior papers and patents are searched, compared and analyzed, and the following technical information with higher correlation degree with the invention is screened out:
literature scheme 1: in ILP-Based Routing and Scheduling of Multicast Realtime Traffic in Time-Sensitive Networks, authors constraint and model network topology and traffic scheduling in real time, and propose to use a linear integer programming algorithm to complete route planning and simultaneous solution of port gate control lists, thereby minimizing end-to-end transmission delay.
Literature scheme 2: in Genetic Algorithm for Scheduling Time-Triggered Traffic in Time-Sensitive Networks, authors comprehensively consider network topology, traffic scheduling, combining multiple constraints such as scheduling and routing into a set of constraints, and optimizing path planning to solve a port gate control list using genetic algorithm, thereby minimizing total transmission delay. And in the study multicast and inter-stream dependency issues were taken into account.
Literature scheme 3: in Scheduling in Time Sensitive Networks (TSN) for mixed-criticality industrial applications, authors design a greedy random adaptive search process (Greedy Randomized Adaptive Search Procedure, GRASP) algorithm by maximizing schedulability of time-triggered streams, minimizing waiting queues and transmission delays of time-triggered streams, and comprehensively considering influence of AVB and other traffic in a TSN system on transmission.
The solution of the document scheme 1 is completed by the route planning and the port gate control list and solved at the same time, but the algorithm based on the linear integer programming increases the algorithm solving process, so that the solution is not feasible in a large-scale network. The solution 2 of the document comprehensively considers the routing and scheduling constraints, but the algorithm has a loss in performance, and the running performance of the algorithm is poor in specific simulation. Document scheme 3 uses a greedy random adaptive search algorithm, but adopts fixed routing without considering the possible impact of routing planning on traffic scheduling results.
Disclosure of Invention
The invention aims to provide a time-sensitive network traffic scheduling method for power service, which is used for solving the problems in the background technology.
The utility model provides a time sensitive network flow scheduling method for electric power business, includes the K short-circuit algorithm based on Yen and the preferred algorithm based on tabu search, characterized in that: the method comprises the following steps:
s100, setting constraint conditions: the feasible solution of the flow scheduling problem of the time trigger flow is to meet certain constraint conditions in the solving process;
s200, setting an objective function: the method comprises the steps of completing an objective function of transmission of all time trigger streams within a specified transmission delay and minimizing an objective function of total transmission delay of all time trigger streams in one-time delay sensitive network flow scheduling;
s300, scheduling algorithm: the verification of the constraint condition corresponding to the steps of the solution is realized through different scheduling of a path generation algorithm based on the KSP algorithm and a preferred algorithm based on the tabu search.
Preferably, the method comprises the steps of,
2. the power service oriented time sensitive network traffic scheduling method of claim 1, wherein the method comprises the steps of: the constraint conditions required to be set in S100 include path constraint, link constraint and transmission constraint, where:
path constraint: the forwarding route of any time trigger flow cannot be free of loops, when the time trigger flow is scheduled, the time trigger flow can only pass through a certain switching node once, and then the time trigger flow can be routed through a specific link:
Figure BDA0003794452880000031
for a pair of
Figure BDA0003794452880000032
There is l ab ＝(n a ，n b )a∈{1，2，...，|f i route |-1}，b＝a+1 (2)
where l ab ∈L * (3)
The characters in the method are all based on network topology environment (N * ，F * ) A representation; n (N) * Representing a set of switch nodes, N being N * Inside the switch nodes, a and b are N * Coordinates of switch node n within, l ab For slave switch node n a To switch node n b F of the chain of (F) * Representing a set of time-triggered streams, f i round Indicating the number of times that the time triggered stream i needs to be transmitted in an overcycle, |f i route I represents the length of the forwarding routing table of time triggered flow i, |f * I represents the number of time-triggered streams, L * Is a set of physical links;
link constraint: only one time trigger stream is transmitted on one physical link at the same time, namely the transmission time of the subsequent stream on the link from the node i to the node j is strictly more than or equal to the transmission time of the previous time trigger stream plus the link propagation time, and the link l is passed through ab ＝(n a ，n b ) Is defined by the flow constraints of (a):
Figure BDA0003794452880000033
Figure BDA0003794452880000034
f in i ，f j Time trigger stream i and time trigger stream j are represented,
Figure BDA0003794452880000035
representing time triggered flows i from switch node n a To switch node n b Start time of->
Figure BDA0003794452880000041
Representing time triggered streams j from switch node n a To switch node n b Start time of->
Figure BDA0003794452880000042
Representing slave switch node n a To switch node n b Propagation delay of the physical link in mus;
transmission constraints: since the ethernet frame has a maximum data load of 1500 bytes, the excessive time triggered stream needs to be split into multiple ethernet frames for transmission:
Figure BDA0003794452880000043
Figure BDA0003794452880000044
wherein n is a ∈f i route ，a∈{1，2，...，|f i route |-1}，i∈{1，2，…，|F * |}；
F in i size The size of the time-triggered stream i is indicated,
Figure BDA0003794452880000045
representing a switch node n a The time spent in transmitting the time triggered stream in mus, f i frag Representing the number of segments of the time triggered stream i.
3. The power service oriented time sensitive network traffic scheduling method of claim 1, wherein the method comprises the steps of: the objective function specific setting of S200 includes two parts:
1) All time trigger flows complete transmission within a specified transmission delay, namely, in each period, the sum of the processing delay of a switch node and the propagation delay of a link, through which the time trigger flows pass, is smaller than the transmission delay of the flow:
Figure BDA0003794452880000046
Figure BDA0003794452880000047
Figure BDA0003794452880000048
Figure BDA0003794452880000051
Figure BDA0003794452880000052
in the middle of
Figure BDA0003794452880000053
Representing the superseriod of a time-triggered stream set, f i cycle Representing the period of the time-triggered stream, f i trans Representing the actual transmission delay +.>
Figure BDA0003794452880000054
Representing a switch node n a The time taken to trigger the flow is processed in units of μs +.>
Figure BDA0003794452880000055
Representing a switch node n a The time spent for transmitting the time trigger stream is expressed in mu s, lcm is the least common multiple function of the solution;
2) And (3) the total transmission delay of all time trigger streams in the primary delay-sensitive network traffic scheduling is reduced:
Figure BDA0003794452880000056
Figure BDA0003794452880000057
Figure BDA0003794452880000058
in the middle of
Figure BDA0003794452880000059
Represents the sum of the actual transmission delays, in mus,
Figure BDA00037944528800000510
representing the total transmission delay of the time triggered stream set.
Preferably, the K-path algorithm based on Yen in the scheduling algorithm of S300 is:
s311, input network topology (N * ，L * ) Link start point n i Link endpoint n j ；
S312, traversing the sending node S and the receiving node d, setting the generating node S as a source point, setting the receiving node d as a destination point, and solving a K short path from the source point to the destination point:
a) Solving the shortest path from the source point s to the end point d;
b) Traversing all the deviation points choice;
c) Adding the alternative path into a list alter_route according to the rule;
d) Completing traversal, searching an alternative list, and finding out a K short path K_path;
s313, returning a K short path from the source point S to the destination point d;
s314, completing K short-path solving of the whole network;
s315, propagation delay matrix between output nodes
Figure BDA0003794452880000061
Or (n) i ，n j ) cost 。
Preferably, the preferred algorithm based on tabu search in the scheduling algorithm of S300 is:
s321, input network topology (N * ，L * ) Link start point n i Link endpoint n j ；
S322, solving an alternative path by using a K-short path algorithm based on Yen;
s323, acquiring flow information triggered at all times in a flow scheduling task;
s324, constructing an initial path by using a shortest path algorithm
S325, for i-0 generates a new routing plan according to the provided policy:
a) i++1, adding the new route plan to candidatelist in the tabu list;
b) The if current path is then continuous in the routing table;
C)else；
a) The if new route planning cannot guarantee deterministic transmission of the succession;
b)else；
c) Calculating the current route planning cost, and adding the cost into a candidate_cost list;
d) if the current route plan is not the optimal route plan then continuous;
e)else break；
D)if i＞iterations num then break
s326, selecting an existing optimal routing scheme, and determining a control list of each switch port door;
s327, outputting a GCL gate control list.
Compared with the prior art, the invention has the beneficial effects that:
the invention mainly researches the route and the scheduling method of time sensitive data flow in the power communication service network, provides a K-short path algorithm optimized route plan based on a TAS scheduling mode, provides an improved tabu search preferred algorithm fast speed solving flow scheduling scheme, and provides port gate control list calculation. The two heuristic algorithms provided by the invention are tested for multiple times, so that the schedulability, the total end-to-end time delay and the algorithm execution time of the two heuristic algorithms are evaluated for different algorithms, the tabu search algorithm provided by the invention can be solved in a shorter time, the capability of finally meeting the deterministic transmission requirement of time-triggered traffic is obviously stronger than that of the shortest path algorithm, the total transmission time delay of all traffic is minimized, and an effective port gate control list is quickly solved.
Drawings
Fig. 1 is a flow chart of a time delay sensitive network flow scheduling algorithm of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Referring to fig. 1, the present invention provides a technical solution: the utility model provides a time sensitive network flow scheduling method for electric power business, includes based on the K short-circuit path algorithm of Yen and based on the preferred algorithm of tabu search, characterized in that: the method comprises the following steps:
s100, setting constraint conditions: the feasible solution of the flow scheduling problem of the time trigger flow is to meet certain constraint conditions in the solving process;
s200, setting an objective function: the method comprises the steps of completing an objective function of transmission of all time trigger streams within a specified transmission delay and minimizing an objective function of total transmission delay of all time trigger streams in one-time delay sensitive network flow scheduling;
s300, scheduling algorithm: the verification of the constraint condition corresponding to the steps of the solution is realized through different scheduling of a path generation algorithm based on the KSP algorithm and a preferred algorithm based on the tabu search.
Specifically, the constraint conditions required to be set in S100 include path constraint, link constraint, and transmission constraint, where:
path constraint: the forwarding route of any time trigger flow cannot be free of loops, when the time trigger flow is scheduled, the time trigger flow can only pass through a certain switching node once, and then the time trigger flow can be routed through a specific link:
Figure BDA0003794452880000081
for a pair of
Figure BDA0003794452880000082
There is l ab ＝(n a ，n b )a∈{1，2，...，|f i route |-1}，b＝a+1 (2)
where l ab ∈L * (3)
The characters in the method are all based on network topology environment (N * ，F * ) A representation; n (N) * Representing a set of switch nodes, N being N * Inside the switch nodes, a and b are N * Coordinates of switch node n within, l ab For slave switch node n a To switch node n b F of the chain of (F) * Representing a set of time-triggered streams, f i round Indicating the number of times that the time triggered stream i needs to be transmitted in an overcycle, |f i route I represents the length of the forwarding routing table of time triggered flow i, |f * I represents the number of time-triggered streams, L * Is a set of physical links;
link constraint: only one time trigger stream is transmitted on one physical link at the same time, namely the transmission time of the subsequent stream on the link from the node i to the node j is strictly more than or equal to the transmission time of the previous time trigger stream plus the link propagation time, and the link l is passed through ab ＝(n a ，n b ) Is defined by the flow constraints of (a):
Figure BDA0003794452880000083
Figure BDA0003794452880000084
f in i ，f j Time trigger stream i and time trigger stream j are represented,
Figure BDA0003794452880000085
representing time triggered flows i from switch node n a To switch node n b Start time of->
Figure BDA0003794452880000086
Representing time triggered streams j from switch node n a To switch node n b Start time of->
Figure BDA0003794452880000087
Representing slave switch node n a To switch node n b Propagation delay of the physical link in mus;
transmission constraints: since the ethernet frame has a maximum data load of 1500 bytes, the excessive time triggered stream needs to be split into multiple ethernet frames for transmission:
Figure BDA0003794452880000091
Figure BDA0003794452880000092
wherein n is a ∈f i route ，a∈{1，2，…，|f i route |-1}，i∈{1，2，...，|F * |}；
F in i size The size of the time-triggered stream i is indicated,
Figure BDA0003794452880000093
representing a switch node n a The time spent in transmitting the time triggered stream in mus, f i frag Representing the number of segments of the time triggered stream i.
Specifically, the objective function specific setting of S200 includes two parts:
1) All time trigger flows complete transmission within a specified transmission delay, namely, in each period, the sum of the processing delay of a switch node and the propagation delay of a link, through which the time trigger flows pass, is smaller than the transmission delay of the flow:
Figure BDA0003794452880000094
Figure BDA0003794452880000095
Figure BDA0003794452880000096
Figure BDA0003794452880000097
f i trans ≤f i delay (12)
in the middle of
Figure BDA0003794452880000098
Representing the superseriod of a time-triggered stream set, f i cycle Representing the period of the time-triggered stream, f i trans Representing the actual transmission delay +.>
Figure BDA0003794452880000101
Representing a switch node n a The time it takes to process the time-triggered stream, in mus,/>
Figure BDA0003794452880000102
representing a switch node n a The time spent for transmitting the time trigger stream is expressed in mu s, lcm is the least common multiple function of the solution;
2) And (3) the total transmission delay of all time trigger streams in the primary delay-sensitive network traffic scheduling is reduced:
Figure BDA0003794452880000103
Figure BDA0003794452880000104
Figure BDA0003794452880000105
in the middle of
Figure BDA0003794452880000106
Represents the sum of the actual transmission delays, in mus,
Figure BDA0003794452880000107
representing the total transmission delay of the time triggered stream set.
Specifically, the K-path algorithm based on Yen in the scheduling algorithm of S300 is:
s311, input network topology (N * ，L * ) Link start point n i Link endpoint n j ；
S312, traversing the sending node S and the receiving node d, setting the generating node S as a source point, setting the receiving node d as a destination point, and solving a K short path from the source point to the destination point:
a) Solving the shortest path from the source point s to the end point d;
b) Traversing all the deviation points choice;
c) Adding the alternative path into a list alter_route according to the rule;
d) Completing traversal, searching an alternative list, and finding out a K short path K_path;
s313, returning a K short path from the source point S to the destination point d;
s314, completing K short-path solving of the whole network;
s315, propagation delay matrix between output nodes
Figure BDA0003794452880000108
Or (n) i ，n j ) cost 。
Specifically, the preferred algorithm based on tabu search in the scheduling algorithm of S300 is:
s321, input network topology (N * ，L * ) Link start point n i Link endpoint n j ；
S322, solving an alternative path by using a K-short path algorithm based on Yen;
s323, acquiring flow information triggered at all times in a flow scheduling task;
s324, constructing an initial path by using a shortest path algorithm
S325, for i≡0 generates a new routing plan according to the provided policy:
a) i++1, adding the new route plan to the candidate_list list in the tabu table;
b) The if current path is then continuous in the routing table;
C)else；
a) The if new route planning cannot guarantee deterministic transmission of the succession;
b)else；
c) Calculating the current route planning cost, and adding the cost into a candidate_cost list;
d) if the current route plan is not the optimal route plan then continuous;
e)else break；
D)if i>iterations_num then break
s326, selecting an existing optimal routing scheme, and determining a control list of each switch port door;
s327, outputting a GCL gate control list.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (5)

1. The utility model provides a time sensitive network flow scheduling method for electric power business, includes the K short-circuit algorithm based on Yen and the preferred algorithm based on tabu search, characterized in that: the method comprises the following steps:
s100, setting constraint conditions: the feasible solution of the flow scheduling problem of the time trigger flow is to meet certain constraint conditions in the solving process;
s200, setting an objective function: the method comprises the steps of completing an objective function of transmission of all time trigger streams within a specified transmission delay and minimizing an objective function of total transmission delay of all time trigger streams in one-time delay sensitive network flow scheduling;
s300, scheduling algorithm: the verification of the constraint condition corresponding to the steps of the solution is realized through different scheduling of a path generation algorithm based on the KSP algorithm and a preferred algorithm based on the tabu search.
2. The power service oriented time sensitive network traffic scheduling method of claim 1, wherein the method comprises the steps of: the constraint conditions required to be set in S100 include path constraint, link constraint and transmission constraint, where:
path constraint: the forwarding route of any time trigger flow cannot be free of loops, when the time trigger flow is scheduled, the time trigger flow can only pass through a certain switching node once, and then the time trigger flow can be routed through a specific link:
Figure FDA0003794452870000011
for a pair of
Figure FDA0003794452870000012
There is->
Figure FDA0003794452870000013
where l ab ∈L * (3)
The characters in the method are all based on network topology environment (N * ，F * ) A representation; n (N) * Representing a set of switch nodes, N being N * Inside the switch nodes, a and b are N * Coordinates of switch node n within, l ab For slave switch node n a To switch node n b F of the chain of (F) * Representing a set of time-triggered streams, f i round Indicating the number of times that the time triggered stream i needs to be transmitted in an overcycle, |f i route I represents the length of the forwarding routing table of time triggered flow i, |f * I represents the number of time-triggered streams, L * Is a set of physical links;
link constraint: only one time trigger stream is transmitted on one physical link at the same time, namely the transmission time of the subsequent stream on the link from the node i to the node j is strictly more than or equal to the transmission time of the previous time trigger stream plus the link propagation time, and the link l is passed through ab ＝(n a ，n b ) Is defined by the flow constraints of (a):
Figure FDA0003794452870000021
Figure FDA0003794452870000022
f in i ，f j Time trigger stream i and time trigger stream j are represented,
Figure FDA0003794452870000023
representing time triggered flows i from switch node n a To switch node n b Start time of->
Figure FDA0003794452870000024
Representing time triggered streams j from switch node n a To switch node n b Start time of->
Figure FDA0003794452870000025
Representing slave switch node n a To switch node n b Propagation delay of the physical link in mus;
transmission constraints: since the ethernet frame has a maximum data load of 1500 bytes, the excessive time triggered stream needs to be split into multiple ethernet frames for transmission:
Figure FDA0003794452870000026
Figure FDA0003794452870000027
wherein n is a ∈f i route ，a∈{1，2，...，|f i route |-1}，i∈{1，2，...，|F * |}；
F in i size The size of the time-triggered stream i is indicated,
Figure FDA0003794452870000028
representing a switch node n a The time spent in transmitting the time triggered stream in mus, f i frag Representing the number of segments of the time triggered stream i.
3. The power service oriented time sensitive network traffic scheduling method of claim 1, wherein the method comprises the steps of: the objective function specific setting of S200 includes two parts:
1) All time trigger flows complete transmission within a specified transmission delay, namely, in each period, the sum of the processing delay of a switch node and the propagation delay of a link, through which the time trigger flows pass, is smaller than the transmission delay of the flow:
Figure FDA0003794452870000031
Figure FDA0003794452870000032
Figure FDA0003794452870000033
Figure FDA0003794452870000034
f i trans ≤f i delay (12)
in the middle of
Figure FDA0003794452870000035
Representing the superseriod of a time-triggered stream set, f i cycle Representing the period of the time-triggered stream, f i trans Representing the actual transmission delay +.>
Figure FDA0003794452870000036
Representing a switch node n a The time it takes to process the time-triggered stream, in mus,
Figure FDA0003794452870000037
representing a switch node n a Time spent transmitting time-triggered streamsThe unit is mu s, lcm is a function for solving the least common multiple;
2) And (3) the total transmission delay of all time trigger streams in the primary delay-sensitive network traffic scheduling is reduced:
Figure FDA0003794452870000038
Figure FDA0003794452870000039
Figure FDA0003794452870000041
in the middle of
Figure FDA0003794452870000044
Represents the sum of the actual transmission delays, in mus,
Figure FDA0003794452870000042
representing the total transmission delay of the time triggered stream set.
4. The power service oriented time sensitive network traffic scheduling method of claim 1, wherein the method comprises the steps of: the K-path algorithm based on the Yen in the scheduling algorithm of S300 is as follows:
s311, input network topology (N * ，L * ) Link start point n i Link endpoint n j ；
S312, traversing the sending node S and the receiving node d, setting the generating node S as a source point, setting the receiving node d as a destination point, and solving a K short path from the source point to the destination point:
a) Solving the shortest path from the source point s to the end point d;
b) Traversing all the deviation points choice;
c) Adding the alternative path into a list alter_route according to the rule;
d) Completing traversal, searching an alternative list, and finding out a K short path K_path;
s313, returning a K short path from the source point S to the destination point d;
s314, completing K short-path solving of the whole network;
s315, propagation delay matrix between output nodes
Figure FDA0003794452870000043
Or (n) i ，n j ) cost 。
5. The power service oriented time sensitive network traffic scheduling method of claim 1, wherein the method comprises the steps of: the preferred algorithm based on tabu search in the scheduling algorithm of S300 is:
s321, input network topology (N * ，L * ) Link start point n i Link endpoint n j ；
S322, solving an alternative path by using a K-short path algorithm based on Yen;
s323, acquiring flow information triggered at all times in a flow scheduling task;
s324, constructing an initial path by using a shortest path algorithm
S325, for i≡0 generates a new routing plan according to the provided policy:
a) i++1, adding the new route plan to the candidate_list list in the tabu table;
b) The if current path is then continuous in the routing table;
C)else；
a) The if new route planning cannot guarantee deterministic transmission of the succession;
b)else；
c) Calculating the current route planning cost, and adding the cost into a candidate_cost list;
d) if the current route plan is not the optimal route plan then continuous;
e)else break；
D)if i＞iterations_num then break
s326, selecting an existing optimal routing scheme, and determining a control list of each switch port door;
s327, outputting a GCL gate control list.
CN202210964931.8A 2022-08-12 2022-08-12 Time-sensitive network traffic scheduling method for power service Pending CN116055377A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210964931.8A CN116055377A (en) 2022-08-12 2022-08-12 Time-sensitive network traffic scheduling method for power service

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210964931.8A CN116055377A (en) 2022-08-12 2022-08-12 Time-sensitive network traffic scheduling method for power service

Publications (1)

Publication Number Publication Date
CN116055377A true CN116055377A (en) 2023-05-02

Family

ID=86131814

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210964931.8A Pending CN116055377A (en) 2022-08-12 2022-08-12 Time-sensitive network traffic scheduling method for power service

Country Status (1)

Country Link
CN (1) CN116055377A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117857423A (en) * 2023-11-29 2024-04-09 慧之安信息技术股份有限公司 Low-delay communication routing method and system based on electric power

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117857423A (en) * 2023-11-29 2024-04-09 慧之安信息技术股份有限公司 Low-delay communication routing method and system based on electric power

Similar Documents

Publication Publication Date Title
Sun et al. TIDE: Time-relevant deep reinforcement learning for routing optimization
WO2023004898A1 (en) Delay deterministic transmission method based on route scheduling and joint optimization
CN113285872B (en) Time-sensitive network communication flow scheduling method based on deep reinforcement learning
EP3297211A1 (en) Method and apparatus for generating network control policy, and network controller
Huang et al. Intelligent traffic control for QoS optimization in hybrid SDNs
Liu et al. DRL-PLink: Deep reinforcement learning with private link approach for mix-flow scheduling in software-defined data-center networks
Dai et al. Routing optimization meets Machine Intelligence: A perspective for the future network
US11526787B1 (en) Knowledge inference engine system and method of implementation
CN116055377A (en) Time-sensitive network traffic scheduling method for power service
Liu et al. Job scheduling for distributed machine learning in optical WAN
Haeri et al. A reinforcement learning-based algorithm for deflection routing in optical burst-switched networks
Gong et al. An efficient scheduling approach for multi-level industrial chain flows in time-sensitive networking
Chen et al. Traffic engineering based on deep reinforcement learning in hybrid IP/SR network
Zhang et al. Dynamic rapid scheduling algorithm for vehicle time sensitive communication based on CILP and AGA
Xu et al. A Graph reinforcement learning based SDN routing path selection for optimizing long-term revenue
Yao et al. A unified flow scheduling method for time sensitive networks
Yang et al. Reuse-based online joint routing and scheduling optimization mechanism in deterministic networks
CN114938374A (en) Cross-protocol load balancing method and system
EP4040732A1 (en) Graph neural network for time sensitive networking in industrial networks
Li et al. Online coordinated NFV resource allocation via novel machine learning techniques
Liu et al. Research on flow scheduling of train communication based on time-sensitive network
Pan et al. A hybrid neural network and genetic algorithm approach for multicast QoS routing
Zang et al. Intra-domain heuristic traffic scheduling algorithm for time-sensitive networks
Kouvatsos et al. Multicast communication in grid computing networks with background traffic
Yang et al. A Multi-Policy Deep Reinforcement Learning Approach for Multi-Objective Joint Routing and Scheduling in Deterministic Networks

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20240206

Address after: 750002 No. 663, Huanghe East Road, Jinfeng District, Yinchuan City, Ningxia Hui Autonomous Region

Applicant after: State Grid Ningxia Electric Power Co., Ltd. Information and Communication Co.

Country or region after: China

Applicant after: STATE GRID NINGXIA ELECTRIC POWER Co.,Ltd.

Address before: No. 663, Huanghe East Road, Jinfeng District, Yinchuan City, 750000 Ningxia Hui Autonomous Region

Applicant before: State Grid Ningxia Electric Power Co., Ltd. Information and Communication Co.

Country or region before: China