CN107733796A - A kind of preferentially path calculation method and system - Google Patents
A kind of preferentially path calculation method and system Download PDFInfo
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- CN107733796A CN107733796A CN201710066835.0A CN201710066835A CN107733796A CN 107733796 A CN107733796 A CN 107733796A CN 201710066835 A CN201710066835 A CN 201710066835A CN 107733796 A CN107733796 A CN 107733796A
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Abstract
The present invention provides a kind of preferentially path calculation method and system, belongs to route applied technical field.Preferentially path calculation method comprises the following steps the present invention：Acquisition approach calculates demand parameter, and selects corresponding weighted calculation model according to path computing demand parameter；Obtain the network state parameters between current each path node；According to the parameter of acquisition, weight and the sequence in current each path are calculated；Empirical model is called, the sequence to path is adjusted；Obtain optimal path.Present invention also offers a kind of system for realizing the above method.Beneficial effects of the present invention are：Matched according to the network parameter needed for practical application, obtain best suiting the path that application network transmission needs；And empirically factor pair path is calculated and adjusted with historical data, the path for making to calculate is more accurate and meets application demand.
Description
Technical field
The present invention relates to route applied technical field, more particularly to a kind of preferentially path calculation method, further relates to a kind of real
The system of existing above-mentioned preferentially path calculation method.
Background technology
Network route path calculation method in, most of path calculation methods are all critical path method (CPM)s, it is recognized that ratio
Preferable algorithm dijkstra's algorithm is relatively more suitable for signal source shortest path problem, and Floyd algorithms are suitable for solving full source most
Short path, OSPF Routing Protocols only calculate the path of fewest number of hops.
Above-mentioned path computing do not consider route between real-time network quality, so fewest number of hops path do not represent it is optimal
Path, path time shortest path do not represent optimal path yet.And due to Internet resources and Internet data transmission demand
Contradiction increasingly strengthen, cost corresponding to the quality characteristic of network transmission also has no small difference, the application of disparate networks transmission
Requirement to network is not quite similar, so current network route computing method technically goes to provide quality highest net merely
Network path, the acquisition of the optimal path of real network transmission requirement can not be met, be in particular in it is following some：
1) current computational methods ignore the different demands of network transmission.Internet development to today, infrastructure network
Build and the multistage trend broken up is presented in operation, be not unified constant：There is national core network, also there is Feeder Network, have
Multi-thread bgp network, also there is single carrier network, there is high network quality also to have low-cost network.The purpose of network transmission be for
Various data transmission applications services, and the purpose of the data transfer of various applications also differs, the requirement for network transmission is
Different：Such as, the application of real-time deal, it is that transmission time is most short for the requirement that data are transmitted in a network；Data calamity is standby, from
The cost transmitted in the application requirement network of line big data calculating etc is minimum；The application of online real-time video, exists for data
The requirement of network transmission is that network jitter is few；Requirement of the data transfer of various kinds of sensors to network is available in Internet of Things application
Property highest.Using most short or what is be evolved redirects based on the time given by traditional static routing, dynamic routing algorithm
Most short " optimal " routing algorithm is the network demand that can not meet that current and future is different.
2) current computational methods lack the foresight that can plan.The network equipment needs to safeguard, and safeguards and plan be present
Property, when planned maintenance causes network node following certain time network transmission stopping or hydraulic performance decline occurring,
Current network method for calculation considers these influences, without foresight, and simply node currently occur " problem " it
Laggard walking along the street footpath adjustment, this have impact on the overall stability of network, it may appear that a certain degree of fluctuation, be unsatisfactory for some applications
Data transportation requirements under environment.
3) current computational methods do not have historical data to analyze and support.Over a period to come, the situation of localized network is
There is certain regularity, showing as certain short network, either (certain net cast activity or double 11 networks promote for activity by some applications
Pin) influence cause periodic network change (e.g., congestion or delay increase), these influences can be specific in current and future
Had an impact in cycle.Current computational methods do not carry out the excavation and analysis of these historical datas, current to calculate based on this
Method can not provide optimal path.
The content of the invention
To solve the problems of the prior art, the present invention provides a kind of preferentially path calculation method, additionally provides a kind of real
The system of the existing preferentially path calculation method.
Preferentially path calculation method comprises the following steps the present invention：
A：Acquisition approach calculates demand parameter, and selects corresponding weighted calculation model according to path computing demand parameter；
B：Obtain the network state parameters between current each path node；
C：According to the parameter of acquisition, weight and the sequence in current each path are calculated；
D：Empirical model is called, the sequence to path is adjusted；
E：Obtain optimal path.
The present invention is further improved, and after step A execution, before step B is performed, in addition to acquisition approach is joined by demand
Number step, the path include the node having to pass through and/or the node that must be avoided by demand parameter.
The present invention is further improved, and the path computing demand parameter includes that the time is most fast, shortest path, path cost
It is minimum, path stability is best, time delay is most short.
The present invention is further improved, and in stepb, the network state parameters include current all nets that can be connected
Ping values, std deviations in network between each node, packet loss.
The present invention is further improved, and in stepb, the network state parameters also include current all can connect
Delay, stability, distance and cost in network between each node and adjacent node.
The present invention is further improved, and in step E, in addition to obtains sub-optimal path alternately path.
The present invention is further improved, and the quantity of the alternative path is two.
The present invention is further improved, in step D, the factor in empirical model include the network state of history, the time, should
With activity.
Present invention also offers the preferentially system of path calculation method, including the first acquisition module described in a kind of realize：With
Demand parameter is calculated in acquisition approach, and corresponding weighted calculation model is selected according to path computing demand parameter；Second obtains
Module：For obtaining the network state parameters between current each path node；Calculate order module：For the ginseng according to acquisition
Number, calculate weight and the sequence in current each path；Adjusting module：For calling empirical model, the sequence to path is adjusted
It is whole；Path acquisition module：For obtaining optimal path.
The present invention is further improved, in addition to demand parameter acquisition module is passed through in path：For acquisition approach by needing
Parameter is sought, the path includes the node having to pass through and/or the node that must be avoided by demand parameter.
Compared with prior art, the beneficial effects of the invention are as follows：Solve the deficiency of current network path computational methods, change
The calculation in current simple, single " most short " path, is matched according to the network parameter needed for practical application, is obtained
Best suit the path that application network transmission needs；And empirically factor pair path is calculated and adjusted with historical data,
The path for making to calculate is more accurate and meets application demand.
Brief description of the drawings
Fig. 1 is the inventive method flow chart；
Fig. 2 is one embodiment of the invention method flow diagram.
Embodiment
The present invention is described in further details with reference to the accompanying drawings and examples.
As shown in figure 1, preferentially path calculation method comprises the following steps the present invention：
Step A：Acquisition approach calculates demand parameter, the path computing demand parameter of this example include the time is most fast, path most
Short, path cost is minimum, path stability is best, time delay is most short etc..Then joined according to the path computing demand of input
The corresponding weighted calculation model of number Auto-matching.
Step B：The network state parameters between current each path node are obtained, the network state parameters include current institute
There are ping values in the network that can be connected between each node, std deviations, packet loss etc., wherein, Ping values refer to from PC to net
Network server sends data to the time for receiving server feedback data；Std deviations are standard deviation.In addition, the network
State parameter can also include delay in current all networks that can be connected between each node and adjacent node, stability,
Distance and cost etc..
Step C：According to path computing demand parameter and network state parameters, the weight in current each path is calculated side by side
Sequence, the available network routed path screened form a paths ordering collection.
Step D：The empirical model for calling historical data to be formed, the sequence to path are adjusted；In the empirical model
The network state of the factor including history, the time, application activity etc., such as double 11 networks promotion described in the prior art
Period, certain apply net cast during situations such as take into account.
Step E：Optimal path is obtained, one, two sub-optimal paths alternately path can be selected.
In addition, after step A execution, before step B is performed, in addition to acquisition approach passes through demand parameter step, for defeated
Enter the node being had to pass through in all-network and/or the node that must be avoided, now, in step C, according to the path computing of acquisition
Demand parameter is passed through in demand parameter, network state parameters and path, calculates weight and the sequence in current each path.
As shown in Fig. 2 as one embodiment of the present of invention, concrete methods of realizing of the present invention comprises the following steps：
S1：Start, the demand that input network path calculates, acquisition approach calculates demand parameter, such as minimum, the path that is delayed
Most short, stability highest, cost is minimum etc..
S2：According to the demand of user, corresponding weighted calculation model is automatically selected, match parameter weight, configures influence
Weights, definition configure the weighted value of corresponding time TimeR, path length ShortR, stability SlaR and cost according to demand
CostR；, then can be by counterweight weights value TimeR=100 for example demand is that cost is minimum；ShortR=100；SlaR=
100；CostR=1；Wherein 1 and 100 be empirical value, can be adjusted according to specific network.
S3—S5：Determine whether that demand is passed through in path, if not, directly performing step S6；Node is avoided if desired
NodeA, then it is empirical value that all path weight values linked with node A, which readjust such as w (A, n)=100,100, this value according to
Specific network condition adjustment.Node node B are had to pass through if desired, then all path weight values linked with node B are again
Adjustment such as w (B, n)=0,0 is empirical value, is adjusted according to specific network condition, then performs step S6.
S6 and S7：The network of all nodes composition be V, and parameter includes accordingly between network two adjacent sections point：Delay
NTimeDelay, length nDistance, stability nSTD and cost nCost；Path values between adjacent node node u, node v
Weighting obtain two hops weight calculation formula be：
W (u, v)=nTimeDelay*TimeR+nDistance*ShortR+nSTD*SlaR+nCost*CostR
Now, getting the network V, V of all node compositions includes the set node { a, b, c ... } and phase of all nodes
The weight w { w (a, b), w (a, c) ... } in the path of neighbors, and the weight between all adjacent nodes is updated according to demand,
Such as weight w (u, v) between node node u, node v.
Select the path that path weight value is most short in V：The specifically routing algorithm such as usable Kshort.Select optimal path
This path is excluded afterwards to select again, obtains sub-optimal path, obtains a paths ordering set by that analogy, p1, p2,
p3……}。
S8：Path P is the path weight value P.cost () after the weighted value addition of all hops.Pass through calling
Historical data, such as：Acquisition approach usage time (timeSpan), then draw the state weight in identical historical time path
Such as p1.History (timeSpan), then according to historical data, weight P.Cost ()=x* in all sequence paths is updated
P.Cost ()+y*P.History (timeSpan), wherein x, y are an empirical coefficient, are configured according to specific network condition.And
{ p ' 1, p ' 2, p ' 3 ... } is resequenced in paths ordering set to renewal.
S9：Export and most match the optimal path p ' 1 of demand after rule of thumb model adjustment, and provide two as needed
Sub-optimal path p ' 2 and p ' 3, terminate.
The present invention solves the deficiency of current network path computational methods, changes current simple, single " most short " path
Calculation, matched according to the network parameter needed for practical application, obtain best suiting what application network transmission needed
Path；And empirically factor pair path is calculated and adjusted with historical data, make the path calculated more accurate
With meet application demand.
Present invention also offers a kind of system for realizing above-mentioned preferentially path calculation method, including the first acquisition module：With
Demand parameter is calculated in acquisition approach, and corresponding weighted calculation model is selected according to path computing demand parameter；Second obtains
Module：For obtaining the network state parameters between current each path node；Calculate order module：For obtaining mould according to first
The parameter obtained in block and the second acquisition module, calculate weight and the sequence in current each path；Adjusting module：Passed through for calling
Model is tested, the sequence to path is adjusted；Path acquisition module：For obtaining optimal path.
The system also passes through demand parameter acquisition module including path：Pass through demand parameter, the road for acquisition approach
Footpath includes the node having to pass through and/or the node that must be avoided by demand parameter.
Embodiment described above is the better embodiment of the present invention, not limits the specific of the present invention with this
Practical range, the scope of the present invention includes being not limited to present embodiment, all equal according to the equivalence changes of the invention made
Within the scope of the present invention.
Claims (10)
1. a kind of preferentially path calculation method, it is characterised in that comprise the following steps：
A：Acquisition approach calculates demand parameter, and selects corresponding weighted calculation model according to path computing demand parameter；
B：Obtain the network state parameters between current each path node；
C：According to the parameter of acquisition, weight and the sequence in current each path are calculated；
D：Empirical model is called, the sequence to path is adjusted；
E：Obtain optimal path.
2. preferentially path calculation method according to claim 1, it is characterised in that：After step A execution, step B is performed
Before, in addition to acquisition approach passes through demand parameter step, the path by demand parameter include the node that has to pass through and/or
The node that must be avoided.
3. preferentially path calculation method according to claim 1, it is characterised in that：The path computing demand parameter includes
Time is most fast, shortest path, and path cost is minimum, path stability is best, time delay is most short.
4. preferentially path calculation method according to claim 1, it is characterised in that：In stepb, the network state ginseng
Number includes the ping values between each node in current all networks that can be connected, std deviations, packet loss.
5. preferentially path calculation method according to claim 4, it is characterised in that：In stepb, the network state ginseng
Number also includes delay, stability, distance and the cost between each node and adjacent node in current all networks that can be connected.
6. according to the preferentially path calculation method described in claim any one of 1-5, it is characterised in that：In step E, in addition to
Obtain sub-optimal path alternately path.
7. preferentially path calculation method according to claim 6, it is characterised in that：The quantity of the alternative path is two.
8. preferentially path calculation method according to claim 6, it is characterised in that：In step D, the factor in empirical model
Network state, time including history, application activity.
9. a kind of realize described in claim any one of 1-8 the preferentially system of path calculation method, it is characterised in that including：
First acquisition module：Demand parameter is calculated for acquisition approach, and is added according to the selection of path computing demand parameter is corresponding
Weigh computation model；
Second acquisition module：For obtaining the network state parameters between current each path node；
Calculate order module：For the parameter according to acquisition, weight and the sequence in current each path are calculated；
Adjusting module：For calling empirical model, the sequence to path is adjusted；
Path acquisition module：For obtaining optimal path.
10. system according to claim 9, it is characterised in that：Also pass through demand parameter acquisition module including path：For
Acquisition approach passes through demand parameter, and the path includes the node having to pass through and/or the section that must be avoided by demand parameter
Point.
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| CN117150271A (en) * | 2023-09-08 | 2023-12-01 | 南京栖西科技有限公司 | Communication path matching method and system |
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