CN104967566A - Automatically switched optical network (ASON) granule business path planning method and ASON granule business path planning device - Google Patents
Automatically switched optical network (ASON) granule business path planning method and ASON granule business path planning device Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L45/00—Routing or path finding of packets in data switching networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L47/00—Traffic control in data switching networks
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- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0005—Switch and router aspects
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Abstract
The present invention relates to an ASON granule business path planning method and an ASON granule business path planning device. By dividing the gathering modes of the granule businesses into an end-to-end gathering mode and a node gathering mode, then carrying out the path planning on the granule businesses of the end-to-end gathering and the granule businesses of the node gathering, the different time slot distribution requirements of the end-to-end gathering and the node gathering of the granule businesses are realized. According to the present invention, and by applying the two time slot gathering methods, the time slot utilization rate of an ASON is improved effectively, the business time slot distribution complexity is reduced, the subsequent novel businesses are conducive to being disposed rapidly, and the maintenance cost is reduced at the same time.
Description
Technical field
The present invention relates to optical transport network technical field, particularly relate to a kind of ASON granule service path planing method, a kind of ASON granule service path device for planning.
Background technology
At general ASON (Automatically Switched Optical Network, ASON) in network, STM-N (Synchronous Transport Module level N, synchronous transfer mode n level) link can transmit data with specific speed, such as STM-16 (third level synchronous transfer mode), STM-64 (fourth stage synchronous transfer mode) etc.Miscellaneous service signal is all through in the multiplexing STM-N of entering frame and carries out transmitting.STM-1 frame rate is 155MBit/s (MBPS), if the service rate of transmission is lower than STM-1, be then called 2M granule business, other business is called high-order business.
In ASON network, the path configurations of business comprises link sequences and the time slot allocation of business on link of business process in network topology.So for a service path configuration, the topology that namely will choose business distributes the chain time gap of business again.
The Sychronized optical networks technical system of China defines PDH (the Plesiochronous Digital Hierarchy based on 2Mbit/s signal, PDH (Pseudo-synchronous Digital Hierarchy)) as the Payload of ASON, and select the multiplexing route of AU-4 (administrative unit-4).High-order business is potted directly into one or more VC4, then directly transmits in the multiplexing STM-N of entering.And low-order service needs first to be encapsulated into VC12, be then multiplexed in VC4, be finally multiplexed in a STM-N and transmit.VC4 is the virtual container corresponding with the PDH signal of 140Mbit/s, VC12 is the virtual container corresponding with the PDH signal of 2Mbit/s, VC3 is the virtual container corresponding with the PDH signal of 34Mbit/s, a VC4 comprises 63 VC12 or 3 VC3, and the 2M granule business that the application relates to is the low-order service of VC12 rank.Here we are called time slot allocation business packed to the process of VC12/VC3, VC4.
In current optical transmission network, be that the transmission network of core exists in a large number with ASON.Current ASON topology of networks is from original Chain Network, and ring-like net progressively develops into multi-ring network, grid type network etc.Business granule degree gets more and more, and there is a large amount of low-order services, and the path planning of these business needs to run by planning software.But there is being miscellaneous service, in the network of particularly a large amount of low-order service, there will be service path plans successfully, but carrying out business configuration according to program results can cause the reduction of network slot utilance and business time-slot to distribute complexity, be unfavorable for follow-up rapid deployment new business, increase O&M cost simultaneously.
Summary of the invention
Based on this, be necessary for the problems referred to above, a kind of ASON paths planning method and device are provided, effectively can improve ASON network slot utilance.
A kind of ASON granule service path planing method, comprises step:
Gather the initial data of ASON, according to described Raw Data Generation network model data, wherein network model data comprises the data of network topology data and each granule business to be planned;
According to the data of each granule business, the granule business with identical sources equipment and host device is incorporated to each subservice list;
Be each virtual service by the end-to-end convergence of granule business can filling up high-order business in each subservice list, remaining granule business setting is each node convergence service;
According to network topology data, determining the path weight value of source device to host device of each virtual service, is that each virtual service distributes shortest route and time slot according to path weight value;
According to network topology data, determining the path weight value of source device to host device of each node convergence service, is that each node convergence service distributes shortest route and time slot according to path weight value.
A kind of ASON granule service path device for planning, comprising:
Network model data generation module, for gathering the initial data of ASON, according to described Raw Data Generation network model data, wherein network model data comprises the data of network topology data and each granule business to be planned;
Subservice List Generating Module, for the data according to each granule business, is incorporated to each subservice list by the granule business with identical sources equipment and host device;
Service convergence module, be each virtual service for the end-to-end convergence of granule business can filling up high-order business in each subservice list, remaining granule business setting is each node convergence service;
Virtual service path planning module, for according to network topology data, determines the path weight value of source device to host device of each virtual service, is that each virtual service distributes shortest route and time slot according to path weight value;
Node traffic path planning module, for according to network topology data, determines the path weight value of source device to host device of each node convergence service, is that each node convergence service distributes shortest route and time slot according to path weight value.
ASON granule service path planing method of the present invention and device, by being divided into end-to-end convergence and node to converge two kinds of modes the ethod of remittance of each granule business, then carry out path planning to the granule business that granule business and the node of end-to-end convergence converge respectively, the different time-gap achieving the end-to-end convergence of granule business and node convergence distributes requirement.By the application of these two kinds of time slot assemblage methods, effectively improve ASON network slot utilance, reduce business time-slot and distribute complexity, be conducive to follow-up rapid deployment new business, reduce O&M cost simultaneously.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the inventive method embodiment;
Fig. 2 is the schematic flow sheet of virtual service path planning step embodiment of the present invention;
Fig. 3 is the schematic flow sheet of node convergence service path planning step embodiment of the present invention;
Fig. 4 is the schematic diagram of ASON network topology specific embodiment;
Fig. 5 is the structural representation of apparatus of the present invention embodiment;
Fig. 6 is the structural representation of virtual service path planning module embodiment of the present invention;
Fig. 7 is the structural representation of node traffic path planning module embodiment of the present invention.
Embodiment
Be described in detail below in conjunction with the embodiment of accompanying drawing to ASON granule service path planing method of the present invention.
As shown in Figure 1, a kind of ASON granule service path planing method, comprises step:
The initial data of S110, collection ASON, according to described Raw Data Generation network model data, wherein network model data comprises the data of network topology data and each granule business to be planned;
S120, data according to each granule business, be incorporated to each subservice list by the granule business with identical sources equipment and host device;
S130, be each virtual service by the end-to-end convergence of granule business that can fill up high-order business in each subservice list, remaining granule business setting is each node convergence service;
S140, according to network topology data, determining the path weight value of source device to host device of each virtual service, is that each virtual service distributes shortest route and time slot according to path weight value;
S150, according to network topology data, determining the path weight value of source device to host device of each node convergence service, is that each node convergence service distributes shortest route and time slot according to path weight value.
Granule business refers to 2M granule business.The initial data of ASON network is the basis of network low-order service path planning, therefore needs first to gather.Can gather the initial data of ASON network from topological data source, topological data source comprises NMS and to unify network planning system.Network management system is used for open ASON network topology data, and network planning system is used for manual input device parameter, the parameter etc. of the such as network equipment and cable resource, supports graphical Interface.When gathering initial data by network planning system, there is manual New-deployed Network, open existing planning network, import webmaster network data three kinds of modes.To import webmaster network data, the step gathering initial data comprises: open webmaster network data exchange interface, prepare data buffer zone, start exchanges data, then generate the ASON network equipment and device data list, optical cable data list, business datum list etc.The ASON network raw data collected comprises Internet resources and service resources type and parameter thereof, and instantiation is as shown in table 1.
The initial data list that table 1 gathers
After collecting initial data, need the network model data initial data of the ASON network in different topology data source being adapted for system, thus carry out service convergence and path planning according to this network model data.Network model data comprises the data etc. of network topology data and each 2M granule business to be planned, network topology data are for determining the equipment in ASON network, the length that equipment room cable link connects and speed etc., the data of each 2M granule business to be planned are used for determining 2M granule business, also be source device and the host device of low-order service, the speed etc. of business.
End-to-end convergence refers to and is gathered together by the low-order service of identical sources equipment and host device, pools the business of the STM-1 of a high-order, and these low-order services use identical route and VC4 time slot in transmitting procedure.Node converges and refers to source device and the inconsistent low-order service of host device, on the identical path of business process, converges in a VC4 as far as possible.In order to improve ASON network slot utilance, needing first to carry out convergence operation to each 2M granule business, is that end-to-end convergence or node converge by each 2M granule business configuration.
When convergence operation is carried out to each 2M granule business, first according to the data of each 2M granule business, also namely sourcesink device id (identify label number) processes service lists, the 2M granule business with identical sources equipment and host device is incorporated to each subservice list, namely the 2M granule service source equipment inside each subservice list and host device are identical, and each subservice list forms subservice list collection.Then travel through subservice list collection, from subservice list collection, obtain a sub-service lists.Principle according to 2M granule service convergence is high-order business: such as 63 VC12 level traffic pool a high-order VC4 business, the 2M granule service combining that can complete a high-order business in this subservice list is completely become a virtual service, obtain many virtual services, and the ethod of remittance of these 2M granule business is set to end-to-end convergence; The 2M granule business that remaining bandwidth deficiency fills up single high-order business does not carry out merging treatment, and its ethod of remittance is set to node convergence, be so just the low-order service of multiple end-to-end convergence and the low-order service of node convergence by the 2M granule delineation of activities in this subservice list.Then above-mentioned ethod of remittance setting is carried out in the subservice list choosing other, until obtain the ethod of remittance of all subservice lists.
According to the convergence result of each subservice list, respectively path planning is carried out to the 2M granule business that 2M granule business and the node of end-to-end convergence converge.It should be noted that, when the 2M granule business that the 2M granule business and node that to there is end-to-end convergence converge simultaneously, first path planning is carried out to the 2M granule business of end-to-end convergence, when only there is a kind of 2M granule business of the ethod of remittance, then just can directly only plan the 2M granule business of this ethod of remittance.Certainly, the present invention does not limit the processing priority that there are two kinds of ethods of remittance simultaneously.
As shown in Figure 2, step S140 can comprise:
S1401, analysis network topology data, undirected lax figure Graph is adopted to describe topology of networks, and build the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, each link is abstract is the undirected corresponding limit of lax figure, enters step S1402;
S1402, travel through each virtual service form list, obtain select virtual service, enter step S1403;
S1403, weight equation according to end-to-end convergence service, upgrade the weight on each limit in undirected lax figure, enter step S1404;
S1404, weight according to undirected lax figure and each limit, call shortest path first and determine that described virtual service source device is to the shortest weight path of host device, enters step S1405;
S1405, according to the shortest described weight path, distribute VC4 time slot for described virtual service takies principle in order on each bar link of route process, enter step S1406;
S1406, be described virtual service distribution VC12 time slot under the VC4 time slot distributed, enter step S1407;
S1407, judge whether each virtual service time slot allocation completes, and as no, returns step S1402, in this way, then enter the step of node convergence service path planning, if without node convergence service, then terminate.
Shown in the structure of undirected lax figure is described below:
After obtaining undirected lax figure Graph, choose the virtual service that will carry out path planning.According to the weight equation of end-to-end convergence service, upgrade the weight on each limit in undirected lax figure Graph.End-to-end convergence service working load homeostatic principle, weight equation is as follows:
Weight＝TotalVC4TimeSlot/IdleVC4TimeSlot；
Weight＝NA(IdleVC4TimeSlot＝0)；
Wherein, TotalVC4TimeSlot describes the total VC4 timeslot number of link, and IdleVC4TimeSlot describes the free timeslot number of link, and VC4 timeslot number-business that the free timeslot number=link of link is total takies timeslot number, IdleVC4TimeSlot>0, NA represent infinitely great.In example network, the initializes weights on the undirected lax each limit of figure Graph can be set to 1.
According to the weight on each limit determined in the undirected lax figure Graph and step S1402 created in step S1401, call critical path method (CPM) and determine the shortest weight path of this virtual service source device to host device.Critical path method (CPM) can adopt Dijkstra (Dijkstra algorithm), Dijkstra is typical shortest path first, outwards expand layer by layer centered by starting point, until expand to terminal, thus calculate a point to other the shortest weight path a little.Use above-mentioned weight equation, during according to dijkstra's algorithm computing service shortest path, meet balancing link load principle.The shortest weight path determined can use Path (DOS path setting command) to describe.
After determining shortest path, distribute time slot namely can to this virtual service.First distribute VC4 time slot in principle for this virtual service takies in order on each bar link of shortest route process, because teleservice in virtual service is for take completely, so be VC12 time slot that the 2M granule traffic assignments of end-to-end convergence is corresponding under the VC4 time slot taken at virtual service.The time slot allocation of this virtual service completes, and then chooses new virtual service and carries out time slot allocation, until all virtual service time slot allocation complete.
When there is node convergence service, when all virtual service time slot allocation complete, namely start to carry out time slot allocation to each node convergence service.If there is not virtual service list, then directly carry out node convergence service time slot allocation.As shown in Figure 3, step S150 comprises step:
S1501, analysis network topology data, undirected lax figure is adopted to describe topology of networks, and build the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, the VC4 of each link is abstract is the undirected corresponding limit of lax figure, enters step S1502;
S1502, travel through each node convergence service form list, obtain select node convergence service, enter step S1503;
S1503, according to node convergence service limit weight equation, upgrade the weight of undirected lax Tu Gebian, enter step S1504;
S1504, weight according to undirected lax figure and each limit, call shortest path first and determine that described node convergence service source device is to the shortest weight path of host device, enters step S1505;
S1505, according to the shortest described weight path, for described node convergence service distributes VC4 time slot on each bar link of route process, enter step S1506;
S1506, be described node convergence service distribution VC12 time slot on the VC4 time slot distributed, enter step S1507;
S1507, judge whether each node convergence service time slot allocation completes, and as no, returns step S1502, if so, terminates.
When being transferred to node by virtual service time slot allocation and converging time slot coupling, only need to converge principle according to node and reconfigure undirected lax figure Graph limit and summit, by the summit that the device abstract in network topology is in undirected lax figure, by abstract for the VC4 of a link be the limit of undirected lax figure.Then according to the list that node convergence service is formed, the node convergence service needing time slot allocation is chosen.
After having chosen node convergence service, according to node convergence service limit weight equation, upgrade the weight on each limit in undirected lax figure Graph.Described node convergence service limit weight equation is:
Weight＝100(IdleTimeSlot>TotalLowerSlot)
Weight＝100*Slack(LowTimeSlot<＝IdleTimeSlot<＝TotalLowerSlot)
Weight＝NA(IdleTimeSlot<LowTimeSlot)
Wherein, IdleTime1Slot describes the free timeslot number in VC4, because 2M granule business is VC12 rank, so IdleTime1Slot description is VC12 timeslot number idle in VC4.TotalLowerSlot describes the timeslot number of all VC12 in a link.LowTimeSlot describes the total granule number of timeslots in VC4, because 2M granule business is VC12 rank, so LowTime1Slot refers to all VC12 timeslot numbers in VC4, numerical value is 63.Slack describes the convergence coefficient on VC4 limit, requires Slack<1, and convergence coefficient is larger, and during shortest path pathfinding, the path that preferential searching node convergence degree is high, is traditionally arranged to be 0.3 ~ 0.5.NA represents infinitely great.
According to the weight on each limit in undirected lax figure Graph and figure that S1501 creates, call shortest path first and determine the shortest weight path of this node convergence service source device to host device, wherein shortest path first can adopt dijkstra's algorithm.Use node convergence service limit weight equation, during according to dijkstra's algorithm determination business shortest path, meet the requirement that node convergence service preferentially uses the VC4 time slot that there is idle VC12.The shortest weight path determined can describe with Path.
After getting the shortest weight path of this node convergence service, for this node convergence service distributes high-order VC4 time slot in each section of route.Business route now uses VC4 to describe, and this VC4 label is the VC4 numbering that business takies.Then being node convergence service distribution VC12 time slot on the VC4 distributed, namely according to the quantity of VC12 idle on VC4, is the VC12 time slot that 2M granule service selection is corresponding.The time slot allocation of this node convergence service completes, and then chooses new node convergence service and carries out time slot allocation, until all node convergence service time slot allocation complete, the planning of 2M granule service path terminates.
In order to more clearly understand embodiments of the present invention, below in conjunction with a specific embodiment, technical solution of the present invention is described in detail.
As shown in Figure 4, be a concrete ASON network topology schematic diagram.As follows from the network model data of this ASON Network Capture:
, between each connection device, there are 4 STM-64 links in network topology data: ASON network has 4 equipment, and device name is respectively A, B, C, D, and in topology, equipment connection situation is: A-B, B-C, C-F, F-D, D-E, E-A;
2M granule business datum to be planned: first group be A point to C point, a business having 200 PDH2M, second group be C point to D point, a business having 100 PDH2M, the 3rd group be A point to D point, a business having 100 PDH2M.
Carry out convergence operation according to step S120 and step S130 to 2M granule business, the convergence result obtained is as follows:
200 2M granule business in first group of business, the end-to-end convergence of 189 2M granule business is wherein 3 virtual VC4 business, is set to T1 respectively, T2, T3; Remaining 11 2M granule business are that node converges, and are set to C1 respectively, C2...C11.
100 2M granule business in second group of business, the end-to-end convergence of 63 2M granule business is wherein 1 virtual VC4 business, is set to T4; Remaining 37 2M granule business are that node converges, and are set to C12 respectively, C13...C48.
100 articles of 2M granule business in 3rd group of business, the end-to-end convergence of 63 2M granule business is wherein 1 virtual VC4 business, is set to T5; Remaining 37 2M granule business are that node converges, and are set to C49 respectively, C50...C85.
First according to step S140, path planning is carried out, namely first to T1, T2, T3 to the 2M granule business of end-to-end convergence ... T5 carries out path planning, there are 4 summits, A-B, B-C, C-D in the undirected lax figure Graph wherein created,, between connection device, there are 4 limits in D-A, D-B.For A equipment to C equipment virtual service T1, through this operation, obtaining route is Path.T1={A-B, B-C}.Link idle time slot between A-B, B-C is all 63, takies time slot for virtual service T1 distributes time slot 1 respectively on A-B, B-C as the VC4 of virtual service T1.63 2M granule business in T1, are followed successively by the time slot 1 internal distribution VC12 time slot of every bar 2M granule business at A-B, B-C link.Final first group of A point takies A-B to the 60th article of business of B point, and the time slot of B-C link is all 1-60, and wherein 1 expression business takies the VC4 timeslot number of link, and 60 identification services take the timeslot number of VC12 under link VC4.So far, virtual service T1 time slot allocation completes, and carries out time slot allocation according to the method described above, then enter C1, C2 to other each virtual service ..., the step of C85 path planning.
To C1, C2 ..., before C85 path planning, need first to upgrade undirected lax figure Graph limit and summit according to step S1501, there are 4 summits in the undirected lax figure Graph now created, between connection device, there is 4*63 bar limit.For A point to C point node convergence service C1, through step S1504 operation, obtaining shortest route is Path.C1={A-B-4, B-C-4}.At link A-B, in B-C, select available VC4 time slot 4, C1 at link A-B, select in B-C on available VC4 time slot 4 for 2M granule service selection can VC12 time slot 1, then 2M granule business C1 distribute time slot be 4-1.So far, C1 time slot allocation completes, and carries out time slot allocation according to the method described above to other each node convergence service, until all node convergence service time slot allocation complete, then all 2M granule service path planning terminates.
Based on same inventive concept, the present invention also provides a kind of ASON granule service path device for planning, is described in detail below in conjunction with the embodiment of accompanying drawing to apparatus of the present invention.
As shown in Figure 5, a kind of ASON granule service path device for planning, comprising:
Network model data generation module 510, for gathering the initial data of ASON, according to described Raw Data Generation network model data, wherein network model data comprises the data of network topology data and each granule business to be planned;
Subservice List Generating Module 520, for the data according to each granule business, is incorporated to each subservice list by the granule business with identical sources equipment and host device;
Service convergence module 530, be each virtual service for the end-to-end convergence of granule business can filling up high-order business in each subservice list, remaining granule business setting is each node convergence service;
Virtual service path planning module 540, for according to network topology data, determines the path weight value of source device to host device of each virtual service, is that each virtual service distributes shortest route and time slot according to path weight value;
Node traffic path planning module 550, for according to network topology data, determines the path weight value of source device to host device of each node convergence service, is that each node convergence service distributes shortest route and time slot according to path weight value.
The network model data that network model data generation module 510 obtains comprises the data etc. of network topology data and each 2M granule business to be planned, network topology data are for determining the equipment in ASON network, the length that equipment room cable link connects and speed etc., the data of each 2M granule business to be planned are used for determining 2M granule business, also be source device and the host device of low-order service, the speed etc. of business.
In order to improve ASON network slot utilance, each 2M granule business configuration is that end-to-end convergence or node converge by subservice List Generating Module 520 and service convergence module 530.Then the 2M granule business of virtual service path planning module 540 to end-to-end convergence carries out path planning, and the 2M granule business that node traffic path planning module 550 pairs of nodes converge carries out path planning.It should be noted that, when the 2M granule business that the 2M granule business and node that to there is end-to-end convergence converge simultaneously, virtual service path planning module 540 first carries out path planning to the 2M granule business of end-to-end convergence, when only there is the 2M granule business that node converges, then node traffic path planning module 550 just can directly only be planned the 2M granule business of this ethod of remittance.
As shown in Figure 6, described virtual service path planning module 540 comprises:
Undirected lax figure construction unit 5401, for analyzing network topology data, undirected lax figure is adopted to describe topology of networks, and build the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, and each link is abstract is the undirected corresponding limit of lax figure;
Virtual service acquiring unit 5402, for traveling through the list that each virtual service is formed, obtains the virtual service selected;
Weight updating block 5403, for the weight equation according to end-to-end convergence service, upgrades the weight on each limit in undirected lax figure; The weight equation of end-to-end convergence service is as follows:
Weight＝TotalVC4TimeSlot/IdleVC4TimeSlot；
Weight＝NA(IdleVC4TimeSlot＝0)；
Wherein, TotalVC4TimeSlot describes the total VC4 timeslot number of link, and IdleVC4TimeSlot describes the free timeslot number of link, and VC4 timeslot number-business that the free timeslot number=link of link is total takies timeslot number, IdleVC4TimeSlot>0, NA represent infinitely great.In example network, the initializes weights on the undirected lax each limit of figure Graph can be set to 1.
The shortest weight path determining unit 5404, for the weight according to undirected lax figure and each limit, calls shortest path first and determines the shortest weight path of described virtual service source device to host device;
VC4 time slot allocating unit 5405, for according to the shortest described weight path, distributes VC4 time slot for described virtual service takies principle in order on each bar link of route process;
VC12 time slot allocating unit 5406, for being described virtual service distribution VC12 time slot under the VC4 time slot distributed;
Judging unit 5407, for judging whether each virtual service time slot allocation completes, in this way, node traffic path planning module 550 pairs of node convergence service carry out path planning, if without node convergence service, then terminate; Otherwise virtual service acquiring unit 5402 reselects virtual service and carries out time slot allocation, until all virtual service time slot allocation complete.
When there is node convergence service, when all virtual service time slot allocation complete, namely node traffic path planning module 550 starts to carry out time slot allocation to each node convergence service.If there is not virtual service list, then node traffic path planning module 550 directly carries out node convergence service time slot allocation.As shown in Figure 7, described node traffic path planning module 550 comprises:
Non-directed graph construction unit 5501, for analyzing network topology data, undirected lax figure is adopted to describe topology of networks, and build the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, and the VC4 of each link is abstract is the undirected corresponding limit of lax figure;
When being transferred to node by virtual service time slot allocation and converging time slot coupling, non-directed graph construction unit 5501 only needs to converge principle according to node and reconfigures undirected lax figure Graph limit and summit, by the summit that the device abstract in network topology is in undirected lax figure, by abstract for the VC4 of a link be the limit of undirected lax figure.
Node convergence service acquiring unit 5502, for traveling through the list that each node convergence service is formed, obtains the node convergence service selected;
Each limit weight updating block 5503, for according to node convergence service limit weight equation, upgrades the weight of undirected lax Tu Gebian;
Described node convergence service limit weight equation is:
Weight＝100(IdleTimeSlot>TotalLowerSlot)
Weight＝100*Slack(LowTimeSlot<＝IdleTimeSlot<＝TotalLowerSlot)
Weight＝NA(IdleTimeSlot<LowTimeSlot)
Wherein, IdleTime1Slot describes VC12 timeslot number idle in VC4.TotalLowerSlot describes the timeslot number of all VC12 in a link.LowTimeSlot describes all VC12 timeslot numbers in VC4, and numerical value is 63.Slack describes the convergence coefficient on VC4 limit, requires Slack<1, and convergence coefficient is larger, and during shortest path pathfinding, the path that preferential searching node convergence degree is high, is traditionally arranged to be 0.3 ~ 0.5.NA represents infinitely great.
Shortest path determining unit 5504, for the weight according to undirected lax figure and each limit, calls shortest path first and determines the shortest weight path of described node convergence service source device to host device;
High-order time slot allocating unit 5505, for according to the shortest described weight path, for described node convergence service distributes VC4 time slot on each bar link of route process;
Low order time slot allocating unit 5506, for being described node convergence service distribution VC12 time slot on the VC4 time slot distributed;
Detecting unit 5507, for judging whether each node convergence service time slot allocation completes, if not, node convergence service acquiring unit 5502 obtains node convergence service again, if complete, then the planning of 2M granule service path terminates.
Other technical characteristic of apparatus of the present invention is identical with the inventive method, does not repeat them here.
ASON granule service path planing method of the present invention and device, by being divided into end-to-end convergence and node to converge two kinds of modes the ethod of remittance of each 2M granule business, then carry out path planning to the 2M granule business that 2M granule business and the node of end-to-end convergence converge respectively, the different time-gap achieving the end-to-end convergence of 2M granule business and node convergence distributes requirement.When network topology and a large amount of 2M granule traffic carrying capacity of complexity, the granule time slot service efficiency in ASON network link can be reduced, thus promote network link utilization rate.
The above embodiment only have expressed several execution mode of the present invention, and it describes comparatively concrete and detailed, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection range of patent of the present invention should be as the criterion with claims.
Claims (10)
1. an ASON granule service path planing method, is characterized in that, comprise step:
Gather the initial data of ASON, according to described Raw Data Generation network model data, wherein network model data comprises the data of network topology data and each granule business to be planned;
According to the data of each granule business, the granule business with identical sources equipment and host device is incorporated to each subservice list;
Be each virtual service by the end-to-end convergence of granule business can filling up high-order business in each subservice list, remaining granule business setting is each node convergence service;
According to network topology data, determining the path weight value of source device to host device of each virtual service, is that each virtual service distributes shortest route and time slot according to path weight value;
According to network topology data, determining the path weight value of source device to host device of each node convergence service, is that each node convergence service distributes shortest route and time slot according to path weight value.
2. ASON granule service path planing method according to claim 1, it is characterized in that, according to network topology data, determine the path weight value of source device to host device of each virtual service, comprise according to the step that path weight value is each virtual service distribution shortest route and time slot:
Analyze network topology data, adopt undirected lax figure to describe topology of networks, and build the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, and each link is abstract is the undirected corresponding limit of lax figure;
Travel through the list that each virtual service is formed, obtain the virtual service selected;
According to the weight equation of end-to-end convergence service, upgrade the weight on each limit in undirected lax figure;
According to the weight on undirected lax figure and each limit, call shortest path first and determine the shortest weight path of described virtual service source device to host device;
According to the shortest described weight path, distribute VC4 time slot for described virtual service takies principle in order on each bar link of route process;
Be that described virtual service distributes VC12 time slot under the VC4 time slot distributed;
Judge whether each virtual service time slot allocation completes, as no, return the step of the list that each virtual service of traversal is formed.
3. ASON granule service path planing method according to claim 2, it is characterized in that, the weight equation of described end-to-end convergence service is:
Weight＝TotalVC4TimeSlot/IdleVC4TimeSlot；
Weight＝NA(IdleVC4TimeSlot＝0)；
Wherein, TotalVC4TimeSlot describes the total VC4 timeslot number of link, and IdleVC4TimeSlot describes the free timeslot number of link, and VC4 timeslot number-business that the free timeslot number=link of link is total takies timeslot number, IdleVC4TimeSlot>0, NA represent infinitely great.
4. ASON granule service path planing method according to claim 1, it is characterized in that, according to network topology data, determine the path weight value of source device to host device of each node convergence service, comprise according to the step that path weight value is each node convergence service distribution shortest route and time slot:
Analyze network topology data, undirected lax figure is adopted to describe topology of networks, and building the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, and the VC4 of each link is abstract is the undirected corresponding limit of lax figure;
Travel through the list that each node convergence service is formed, obtain the node convergence service selected;
According to node convergence service limit weight equation, upgrade the weight of undirected lax Tu Gebian;
According to the weight on undirected lax figure and each limit, call shortest path first and determine the shortest weight path of described node convergence service source device to host device;
According to the shortest described weight path, for described node convergence service distributes VC4 time slot on each bar link of route process;
The VC4 time slot distributed is described node convergence service distributes VC12 time slot;
Judge whether each node convergence service time slot allocation completes, as no, return the step of the list that each node convergence service of traversal is formed.
5. ASON granule service path planing method according to claim 4, is characterized in that, described node convergence service limit weight equation is:
Weight＝100(IdleTimeSlot>TotalLowerSlot)
Weight＝100*Slack(LowTimeSlot<＝IdleTimeSlot<＝TotalLowerSlot)
Weight＝NA(IdleTimeSlot<LowTimeSlot)
Wherein, IdleTime1Slot describes VC12 timeslot number idle in VC4, and TotalLowerSlot describes the timeslot number of all VC12 in a link, and LowTimeSlot describes all VC12 timeslot numbers in VC4, Slack describes the convergence coefficient on VC4 limit, and NA represents infinitely great.
6. an ASON granule service path device for planning, is characterized in that, comprising:
Network model data generation module, for gathering the initial data of ASON, according to described Raw Data Generation network model data, wherein network model data comprises the data of network topology data and each granule business to be planned;
Subservice List Generating Module, for the data according to each granule business, is incorporated to each subservice list by the granule business with identical sources equipment and host device;
Service convergence module, be each virtual service for the end-to-end convergence of granule business can filling up high-order business in each subservice list, remaining granule business setting is each node convergence service;
Virtual service path planning module, for according to network topology data, determines the path weight value of source device to host device of each virtual service, is that each virtual service distributes shortest route and time slot according to path weight value;
Node traffic path planning module, for according to network topology data, determines the path weight value of source device to host device of each node convergence service, is that each node convergence service distributes shortest route and time slot according to path weight value.
7. ASON granule service path device for planning according to claim 6, it is characterized in that, described virtual service path planning module comprises:
Undirected lax figure construction unit, for analyzing network topology data, adopting undirected lax figure to describe topology of networks, and building the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, and each link is abstract is the undirected corresponding limit of lax figure;
Virtual service acquiring unit, for traveling through the list that each virtual service is formed, obtains the virtual service selected;
Weight updating block, for the weight equation according to end-to-end convergence service, upgrades the weight on each limit in undirected lax figure;
The shortest weight path determining unit, for the weight according to undirected lax figure and each limit, calls shortest path first and determines the shortest weight path of described virtual service source device to host device;
VC4 time slot allocating unit, for according to the shortest described weight path, distributes VC4 time slot for described virtual service takies principle in order on each bar link of route process;
VC12 time slot allocating unit, for being described virtual service distribution VC12 time slot under the VC4 time slot distributed;
Judging unit, for judging whether each virtual service time slot allocation completes.
8. ASON granule service path device for planning according to claim 7, it is characterized in that, the weight equation of described end-to-end convergence service is:
Weight＝TotalVC4TimeSlot/IdleVC4TimeSlot；
Weight＝NA(IdleVC4TimeSlot＝0)；
Wherein, TotalVC4TimeSlot describes the total VC4 timeslot number of link, and IdleVC4TimeSlot describes the free timeslot number of link, and VC4 timeslot number-business that the free timeslot number=link of link is total takies timeslot number, IdleVC4TimeSlot>0, NA represent infinitely great.
9. ASON granule service path device for planning according to claim 6, it is characterized in that, described node traffic path planning module comprises:
Non-directed graph construction unit, for analyzing network topology data, undirected lax figure is adopted to describe topology of networks, and build the internal data of graph style, each device abstract wherein in network topology is the undirected corresponding summit of lax figure, and the VC4 of each link is abstract is the undirected corresponding limit of lax figure;
Node convergence service acquiring unit, for traveling through the list that each node convergence service is formed, obtains the node convergence service selected;
Each limit weight updating block, for according to node convergence service limit weight equation, upgrades the weight of undirected lax Tu Gebian;
Shortest path determining unit, for the weight according to undirected lax figure and each limit, calls shortest path first and determines the shortest weight path of described node convergence service source device to host device;
High-order time slot allocating unit, for according to the shortest described weight path, for described node convergence service distributes VC4 time slot on each bar link of route process;
Low order time slot allocating unit, for being described node convergence service distribution VC12 time slot on the VC4 time slot distributed;
Detecting unit, for judging whether each node convergence service time slot allocation completes.
10. ASON granule service path device for planning according to claim 9, is characterized in that, described node convergence service limit weight equation is:
Weight＝100(IdleTimeSlot>TotalLowerSlot)
Weight＝100*Slack(LowTimeSlot<＝IdleTimeSlot<＝TotalLowerSlot)
Weight＝NA(IdleTimeSlot<LowTimeSlot)
Wherein, IdleTime1Slot describes VC12 timeslot number idle in VC4, and TotalLowerSlot describes the timeslot number of all VC12 in a link, and LowTimeSlot describes all VC12 timeslot numbers in VC4, Slack describes the convergence coefficient on VC4 limit, and NA represents infinitely great.
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