CN110365585A - A kind of routing cutting optimization method based on more cost indexs - Google Patents
A kind of routing cutting optimization method based on more cost indexs Download PDFInfo
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Abstract
The invention proposes a kind of, and the routing based on more cost indexs cuts optimization method.The present invention constructs various dimensions space by cost indicator vector and carries out elongated segmentation to every dimension axis according to the stepped sequence that precision is established；It is routed across in node from source node to destination node and selects intermediate node, the cost indicator vector of the neighbor node of calculating source node to intermediate node；Any two cost indicator vector in all cost indicator vectors of the neighbor node of source node to intermediate node is compared the primary cutting of realization routing；Secondary cutting is carried out in various dimensions space according to the remaining cost indicator vector of the neighbor node of source node to intermediate node；It repeats primary cutting and secondary be cut to searches source node to the routing of destination node and be in optimized selection；Successive ignition, which repeats, to be searched source node to the routing of destination node and optimizes.Compared with prior art, the invention is simple and feasible, and higher-dimension cost index can be handled in polynomial time.
Description
Technical field
The present invention relates to wireless network communication technique field more particularly to a kind of routing cutting based on more cost indexs are excellent
Change method.
Background technique
In the calculating of shortest path, each of the links have a cost value, and routing decision module is by searching out purpose
There is the path of minimum total cost to complete to route on ground.In RIP agreement, use hop count as the foundation of routing, each of the links
Cost be 1.In the ospf protocol, default is the cost using reference bandwidth divided by interface bandwidth as each outbound
Index.
In recent years, software defined network (Software Defined Networking, SDN) has been greatly developed.
Software defined network realizes the centralized management of control logic by that will control plane and data planar separation.In software definition
In network, the forwarding of data is made decisions by SDN controller.Since SDN controller has global view, thus can be very smart
True is each stream planning path.When carrying out routing decision, for the path of point-to-point transmission, the cost in path is each link
The sum of cost.Controller selects the optimal path from source node to destination node according to the cost value in path each in network.
Current controller measures the cost of link using single index, but a real good road in actual use
Diameter tends not to simply be measured with a single index, needs to consider simultaneously many factors, including time delay, bandwidth, hop count
With rent etc., two kinds of even more cost indexs at this moment are considered as each of the links.It is selected most according to single cost
When shortest path, dijkstra's algorithm can be used to calculate.But for the path of multi objective, there is presently no good methods.
Main problem is that its search space is too big, the fully-connected network of a n node is considered, the path between any two points can be with
There is (n-1)！The calculating of item, optimal path cannots be completed in a short period of time.The problem is referred to as Multi-Object Optimal
Path, MOOP, correlative study show that this is a NP-complete problem, to obtain Pareto optimality disaggregation, need exponential form
Time.Thus, current SDN controller only supports the Route Selection of single cost index, there is no the routing under more cost indexs
Scheme.
Summary of the invention
To solve the above-mentioned problems, the present invention provides a kind of, and the routing based on more cost indexs cuts optimization method, this
Technical solution used by inventing is:
Step 1: various dimensions space being constructed by cost indicator vector, the stepped sequence established according to precision is to various dimensions sky
Between every dimension axis carry out elongated segmentation；
Step 2: selecting source node and destination node from network node, be routed across section from source node to destination node
Intermediate node is selected in point, the neighbours of source node to intermediate node are calculated according to the cost indicator vector of source node to intermediate node
The cost indicator vector of node；
Step 3: by all cost indicator vectors of the neighbor node of traversal source node to intermediate node, and by any two
A cost indicator vector, which is compared, realizes that primary cut of routing obtains the remaining cost of neighbor node of the node to intermediate node
Indicator vector and remaining route set；
Step 4: according to the remaining cost indicator vector of the neighbor node of source node to intermediate node in various dimensions space
Secondary cutting is carried out to the remaining routing of the neighbor node of source node to intermediate node；
Step 5: repeating step 3 to step 4 to searching source node to the routing of destination node and be in optimized selection；
Step 6: successive ignition repeats step 5.
Preferably, cost indicator vector described in step 1 are as follows:
Wxy,i=(wxy,i,1,wxy,i,2,...,wxy,i,K)x∈[1,N],y∈[1,N],i∈[1,|Pxy|],x≠y
Wherein, Wxy,iThe cost indicator vector routed for network node x to network node y i-th, PxyFor network node x
To the route set of network node y, | Pxy| it is routing quantity, that is, cost indicator vector number of network node x to network node y
Amount, N are the number of nodes in network, and K is the index quantity in network, wxy,i,kK ∈ [1, K] is network node x to network node
K-th of cost index of the cost indicator vector of y i-th routing；
Various dimensions space H is constructed according to network middle finger target quantity KK, dimension K；
If the lower bound of jth (1≤j≤K) dimension cost is LB in all pathsj, upper bound UBj, precision e, and there are one
Mj∈ Z+ (positive integer) makesThen
The stepped sequence that the precision e according to step 1 is established are as follows:
Wherein, m-th of element is (1+e) in stepped sequencem-1m∈[1,Mj]；
To various dimensions space H described in step 1KJth dimension axis be segmented are as follows:
Wherein, on jth dimension axis n-th section be [(1+e)n-1,(1+e)n]n∈[1,Mj], various dimensions space HKK axis it is equal
Elongated segmentation is carried out according to stepped sequence；
Preferably, selecting network node s (s ∈ [1, N]) to be used as source node, choosing from network node described in step 2
Network node t (t ∈ [1, N]) is selected as destination node, N is the quantity of nodes；
Selection network node u (u ∈ [1, N]) described in step 2 is used as intermediate node, and source node is into described in step 2
The cost indicator vector of intermediate node
Wsu,l=(wsu,l,1,wsu,l,2,...,wsu,l,K)s∈[1,N],u∈[1,N],l∈[1,|Psu|],s≠u
Wherein, Wsu,lFor the cost indicator vector that source node is routed to the l articles of intermediate node, PsuFor source node to middle node
The route set of point, | Pxy| for routing quantity, that is, cost indicator vector quantity of source node to intermediate node, N is in network
Number of nodes, K are network middle finger target quantity, wsu,l,kK ∈ [1, K] is source node in network to the l articles of intermediate node routing
Cost indicator vector k-th of cost index；
Intermediate node described in step 2 to intermediate node neighbor node cost indicator vector are as follows:
Wuv,o=(wuv,o,1,wuv,o,2,...,wuv,o,K)u∈[1,N],v∈[1,N],o∈[1,|Puv|],u≠v
Wherein, Wuv,oFor the cost indicator vector of the o articles of neighbor node routing of intermediate node to intermediate node, PsuFor in
Intermediate node to intermediate node neighbor node route set, | Pxy| for the routing of the neighbor node of intermediate node to intermediate node
Quantity, that is, cost indicator vector quantity, N are the quantity of nodes, and K is network middle finger target quantity, wuv,o,kk∈[1,
K] be intermediate node to the o articles of neighbor node of intermediate node routing cost indicator vector k-th of cost index；
Source node described in step 2 to intermediate node neighbor node cost indicator vector are as follows:
Wsv,q=Wsu,l+Wuv,o
Wherein, Wsv,q(q∈[1,|Psv|]) it is the neighbor node the q article cost index that routes of the source node to intermediate node
Vector, PsvFor the route set of the neighbor node of source node to intermediate node, | Psv| it is saved for the neighbours of source node to intermediate node
Routing quantity, that is, cost indicator vector quantity of point, and PsvIn arbitrarily route do not include intermediate node i.e. network node u (u
∈[1,N])；
Preferably, the cost indicator vector of neighbor node of source node described in step 3 to intermediate node is respectively as follows:
Wherein, Wsv,q(q∈[1,|Psv|]) it is the neighbor node the q article cost index that routes of the source node to intermediate node
Vector, PsvFor the route set of the neighbor node of source node to intermediate node, | Psv| it is saved for the neighbours of source node to intermediate node
Routing quantity, that is, cost indicator vector quantity of point, and PsvIn arbitrarily route do not include intermediate node i.e. network node u (u
∈[1,N])；
The indicator vector of any two cost described in step 3 is compared, and arbitrarily selects two cost indicator vector Wsv,g
(g∈[1,|Psv|]) and Wsv,h(h∈[1,|Psv|]) and g ≠ h, if Wsv,g(g∈[1,|Psv|]) in each element it is small
In equal to Wsv,h(h∈[1,|Psv|]) in corresponding each element, i.e., W is met to any k (k ∈ [1, K])sv,g(k)≤Wsv,h
(k) then by Wsv,hThe route set P of neighbor node of the corresponding the h articles routing from source node to intermediate nodesvMiddle deletion is cut out
It cuts；
Traverse source node to intermediate node neighbor node all cost indicator vectors, according to above-mentioned comparison method source node
Remaining routing quantity to the neighbor node of intermediate node is that the quantity of remaining cost indicator vector is For source node
To the remaining route set of the neighbor node of intermediate node；
Preferably, the remaining of neighbor node of source node described in step 4 to intermediate node routes quantity i.e. remaining generation
The quantity of valence indicator vector isFor the remaining route set of the neighbor node of source node to intermediate node, ifThen secondary cutting is completed；
IfIt is by the remaining cost indicator vector of the neighbor node of source node described in step 4 to intermediate nodeIn various dimensions space HKIn cut；
The stepped sequence that the precision according to step 1 is established carries out variable step point to every dimension axis in various dimensions space
Section, by various dimensions space HKMultiple subspaces are divided into, the residue of the neighbor node of source node described in step 4 to intermediate node
Cost indicator vector isCorresponding S sub-spaces are belonging respectively to, each continuous subspace is wrapped respectively
Containing M1,M2,...,MSA residue cost indicator vector；
For separately including M1,M2,...,MSEvery sub-spaces of a cost indicator vector, according to any one subspace
It is M it includes the quantity of remaining cost indicator vectorfMf∈[M1,MS], subspace includes that cost indicator vector isCalculate separately the weighted value of each cost indicator vector are as follows:
Wherein,For minimum value, the neighbours of corresponding source node to intermediate node
NodeIn corresponding FzItem routing retains, remaining Mf- 1 routing fromIn deleted and cut；
Preferably, selecting network node s (s ∈ [1, N]) to be used as source node, choosing from network node described in step 5
Network node t (t ∈ [1, N]) is selected as destination node, N is the quantity of nodes；
The cost indicator vector of source node described in step 5 to destination node is respectivelySource section
It puts to routing quantity, that is, cost indicator vector quantity of destination node and isFor the routing of source node to destination node
Set, calculates separately the weighted value of each cost indicator vector are as follows:
Wherein,For minimum value, corresponding source node to destination node exists
In n-thminItem routing retains, remainingItem routing fromIn deleted and cut；
Preferably, the number for being iteratively repeated execution step 5 described in step 6 is Mopt=N-1, N are nodes
Quantity.
Compared with prior art, remaining path is cut off, search space is greatly reduced；Operation is completed to target in iteration
When node, remaining path is approximate more cost optimal paths on destination node；And the method for the present invention is simple and easy, it can be more
Higher-dimension cost index is handled in the item formula time.
Detailed description of the invention
Fig. 1: for flow chart of the method for the present invention；
Fig. 2: for the network topological diagram of the embodiment of the present invention.
Specific embodiment
Understand for the ease of those of ordinary skill in the art and implement the present invention, with reference to the accompanying drawings and embodiments to this hair
It is bright to be described in further detail, it should be understood that implementation example described herein is merely to illustrate and explain the present invention, not
For limiting the present invention.
Fig. 1 is flow chart of the method for the present invention, and Fig. 2 is the network topological diagram of the embodiment of the present invention.The embodiment of the present invention
It is carried out on Mininet emulation platform and python Programming with Pascal Language, uses Floodlight as controller in Mininet,
And choosing 6 interchangers as network node, that is, network node quantity is 6, is two-way link, figure between every two network node
In each link include a two-dimensional cost indicator vector, on the link with a pair of of bracket mark, the of cost indicator vector
The time delay cost of one element representation link, the bandwidth cost of second element representation link of cost indicator vector, choosing
Selecting network node 1 is source node, selects network node 6 for destination node.
The specific steps that the embodiment of the present invention is introduced below with reference to Fig. 1 and Fig. 2, the present invention provides one kind based on mostly generation
The routing of valence index cuts optimization method, the specific steps are that:
Step 1: various dimensions space being constructed by cost indicator vector, the stepped sequence established according to precision is to various dimensions sky
Between every dimension axis carry out elongated segmentation；
Cost indicator vector described in step 1 are as follows:
Wxy,i=(wxy,i,1,wxy,i,2,...,wxy,i,K)x∈[1,N],y∈[1,N],i∈[1,|Pxy|],x≠y
Wherein, Wxy,iThe cost indicator vector routed for network node x to network node y i-th, PxyFor network node x
To the route set of network node y, | Pxy| it is routing quantity, that is, cost indicator vector number of network node x to network node y
Amount, N=6 are the number of nodes in network, and K=2 is the index quantity in network, wxy,i,kK ∈ [1, K] is network node x to net
K-th of cost index of the cost indicator vector of network node y i-th routing；
Various dimensions space H is constructed according to network middle finger target quantity K=2K, dimension K；
If the lower bound of jth (1≤j≤K) dimension cost is LB in all pathsj=1, upper bound UBj=10, precision e, and
There are a Mj∈ Z+ (positive integer) makesThen
The stepped sequence that the precision e according to step 1 is established are as follows:
Wherein, m-th of element is (1+e) in stepped sequencem-1m∈[1,Mj]；
To various dimensions space H described in step 1KJth dimension axis be segmented are as follows:
Wherein, on jth dimension axis n-th section be [(1+e)n-1,(1+e)n]n∈[1,Mj], various dimensions space HKK axis it is equal
Elongated segmentation is carried out according to stepped sequence；
Step 2: selecting source node and destination node from network node, be routed across section from source node to destination node
Intermediate node is selected in point, the neighbours of source node to intermediate node are calculated according to the cost indicator vector of source node to intermediate node
The cost indicator vector of node；
It selects network node s (s ∈ [1, N]) to be used as source node from network node described in step 2, selects network node
T (t ∈ [1, N]) is used as destination node, and N=6 is the quantity of nodes；
Selection network node u (u ∈ [1, N]) described in step 2 is used as intermediate node, and source node is into described in step 2
The cost indicator vector of intermediate node
Wsu,l=(wsu,l,1,wsu,l,2,...,wsu,l,K)s∈[1,N],u∈[1,N],l∈[1,|Psu|],s≠u
Wherein, Wsu,lFor the cost indicator vector that source node is routed to the l articles of intermediate node, PsuFor source node to middle node
The route set of point, | Pxy| it is source node to routing quantity, that is, cost indicator vector quantity of intermediate node, N=6 is network
In number of nodes, K=2 be network middle finger target quantity, wsu,l,kK ∈ [1, K] is source node in network to intermediate node l
K-th of cost index of the cost indicator vector of item routing；
Intermediate node described in step 2 to intermediate node neighbor node cost indicator vector are as follows:
Wuv,o=(wuv,o,1,wuv,o,2,...,wuv,o,K)u∈[1,N],v∈[1,N],o∈[1,|Puv|],u≠v
Wherein, Wuv,oFor the cost indicator vector of the o articles of neighbor node routing of intermediate node to intermediate node, PsuFor in
Intermediate node to intermediate node neighbor node route set, | Pxy| for the routing of the neighbor node of intermediate node to intermediate node
Quantity, that is, cost indicator vector quantity, N=6 are the quantity of nodes, and K=2 is network middle finger target quantity, wuv,o,kk
∈ [1, K] is k-th of cost index of the cost indicator vector of the o articles of neighbor node routing of intermediate node to intermediate node；
Source node described in step 2 to intermediate node neighbor node cost indicator vector are as follows:
Wsv,q=Wsu,l+Wuv,o
Wherein, Wsv,q(q∈[1,|Psv|]) it is the neighbor node the q article cost index that routes of the source node to intermediate node
Vector, PsvFor the route set of the neighbor node of source node to intermediate node, | Psv| it is saved for the neighbours of source node to intermediate node
Routing quantity, that is, cost indicator vector quantity of point, and PsvIn arbitrarily route do not include intermediate node i.e. network node u (u
∈[1,N])；
Step 3: by all cost indicator vectors of the neighbor node of traversal source node to intermediate node, and by any two
A cost indicator vector, which is compared, realizes that primary cut of routing obtains the remaining cost of neighbor node of the node to intermediate node
Indicator vector and remaining route set；
The cost indicator vector of neighbor node of source node described in step 3 to intermediate node is respectively as follows:
Wherein, Wsv,q(q∈[1,|Psv|]) it is the neighbor node the q article cost index that routes of the source node to intermediate node
Vector, PsvFor the route set of the neighbor node of source node to intermediate node, | Psv| it is saved for the neighbours of source node to intermediate node
Routing quantity, that is, cost indicator vector quantity of point, and PsvIn arbitrarily route do not include intermediate node i.e. network node u (u
∈[1,N])；
The indicator vector of any two cost described in step 3 is compared, and arbitrarily selects two cost indicator vector Wsv,g
(g∈[1,|Psv|]) and Wsv,h(h∈[1,|Psv|]) and g ≠ h, if Wsv,g(g∈[1,|Psv|]) in each element it is small
In equal to Wsv,h(h∈[1,|Psv|]) in corresponding each element, i.e., W is met to any k (k ∈ [1, K])sv,g(k)≤Wsv,h
(k) then by Wsv,hThe route set P of neighbor node of the corresponding the h articles routing from source node to intermediate nodesvMiddle deletion is cut out
It cuts；
Traverse source node to intermediate node neighbor node all cost indicator vectors, according to above-mentioned comparison method source node
Remaining routing quantity to the neighbor node of intermediate node is that the quantity of remaining cost indicator vector is For source node
To the remaining route set of the neighbor node of intermediate node；
Step 4: according to the remaining cost indicator vector of the neighbor node of source node to intermediate node in various dimensions space
Secondary cutting is carried out to the remaining routing of the neighbor node of source node to intermediate node；
The remaining of neighbor node of source node described in step 4 to intermediate node routes the i.e. remaining cost indicator vector of quantity
Quantity beFor the remaining route set of the neighbor node of source node to intermediate node, ifThen secondary sanction
Cut completion；
IfIt is by the remaining cost indicator vector of the neighbor node of source node described in step 4 to intermediate nodeIn various dimensions space HKIn cut；
The stepped sequence that the precision according to step 1 is established carries out variable step point to every dimension axis in various dimensions space
Section, by various dimensions space HKMultiple subspaces are divided into, the residue of the neighbor node of source node described in step 4 to intermediate node
Cost indicator vector isCorresponding S sub-spaces are belonging respectively to, each continuous subspace is wrapped respectively
Containing M1,M2,...,MSA residue cost indicator vector；
For separately including M1,M2,...,MSEvery sub-spaces of a cost indicator vector, according to any one subspace
It is M it includes the quantity of remaining cost indicator vectorf Mf∈[M1,MS], subspace includes that cost indicator vector isCalculate separately the weighted value of each cost indicator vector are as follows:
Wherein,For minimum value, the neighbours of corresponding source node to intermediate node
NodeIn corresponding FzItem routing retains, remaining Mf- 1 routing fromIn deleted and cut；
Step 5: repeating step 3 to step 4 to searching source node to the routing of destination node and be in optimized selection；
It selects network node s (s ∈ [1, N]) to be used as source node from network node described in step 5, selects network node
T (t ∈ [1, N]) is used as destination node, and N=6 is the quantity of nodes；
The cost indicator vector of source node described in step 5 to destination node is respectivelySource section
It puts to routing quantity, that is, cost indicator vector quantity of destination node and isFor the routing of source node to destination node
Set, calculates separately the weighted value of each cost indicator vector are as follows:
Wherein,For minimum value, corresponding source node to destination node exists
In n-thminItem routing retains, remainingItem routing fromIn deleted and cut；
Step 6: successive ignition repeats step 5；
Being iteratively repeated and executing the number of step 5 is Mopt=5, from source node, that is, network node 1 to destination node, that is, network section
The optimal path of point 6 is 1-2-4-6.
It should be understood that the above-mentioned description for preferred embodiment is more detailed, can not therefore be considered to this
The limitation of invention patent protection range, those skilled in the art under the inspiration of the present invention, are not departing from power of the present invention
Benefit requires to make replacement or deformation under protected ambit, fall within the scope of protection of the present invention, this hair
It is bright range is claimed to be determined by the appended claims.
Claims (7)
1. a kind of routing based on more cost indexs cuts optimization method, which comprises the following steps:
Step 1: various dimensions space being constructed by cost indicator vector, the stepped sequence established according to precision is to various dimensions space
Every dimension axis carries out elongated segmentation；
Step 2: selecting source node and destination node from network node, be routed across in node from source node to destination node
Intermediate node is selected, the neighbor node of source node to intermediate node is calculated according to the cost indicator vector of source node to intermediate node
Cost indicator vector；
Step 3: by all cost indicator vectors of the neighbor node of traversal source node to intermediate node, and by any two generation
Valence indicator vector, which is compared, realizes that primary cut of routing obtains the remaining cost index of neighbor node of the node to intermediate node
Vector and remaining route set；
Step 4: according to the remaining cost indicator vector of the neighbor node of source node to intermediate node to source in various dimensions space
The remaining of neighbor node of node to intermediate node routes the secondary cutting of progress；
Step 5: repeating step 3 to step 4 to searching source node to the routing of destination node and be in optimized selection；
Step 6: successive ignition repeats step 5.
2. the routing according to claim 1 based on more cost indexs cuts optimization method, which is characterized in that in step 1
The cost indicator vector are as follows:
Wxy,i=(wxy,i,1,wxy,i,2,...,wxy,i,K)x∈[1,N],y∈[1,N],i∈[1,|Pxy|],x≠y
Wherein, Wxy,iThe cost indicator vector routed for network node x to network node y i-th, PxyFor network node x to net
The route set of network node y, | Pxy| it is routing quantity, that is, cost indicator vector quantity of network node x to network node y, N
For the number of nodes in network, K is the index quantity in network, wxy,i,kK ∈ [1, K] is network node x to network node y the
K-th of cost index of the cost indicator vector of i item routing；
Various dimensions space H is constructed according to network middle finger target quantity KK, dimension K；
If the lower bound of jth (1≤j≤K) dimension cost is LB in all pathsj, upper bound UBj, precision e, and there are a Mj∈
Z+(positive integer) makesThen
The stepped sequence that the precision e according to step 1 is established are as follows:
Wherein, m-th of element is (1+e) in stepped sequencem-1m∈[1,Mj]；
To various dimensions space H described in step 1KJth dimension axis be segmented are as follows:
Wherein, on jth dimension axis n-th section be [(1+e)n-1,(1+e)n]n∈[1,Mj], various dimensions space HKK axis all in accordance with
Stepped sequence carries out elongated segmentation.
3. the routing according to claim 1 based on more cost indexs cuts optimization method, which is characterized in that in step 2
It is described to select network node s (s ∈ [1, N]) to be used as source node from network node, select network node t (t ∈ [1, N]) conduct
Destination node, N are the quantity of nodes；
Selection network node u (u ∈ [1, N]) described in step 2 is used as intermediate node, source node described in step 2 to middle node
The cost indicator vector of point
Wsu,l=(wsu,l,1,wsu,l,2,...,wsu,l,K)s∈[1,N],u∈[1,N],l∈[1,|Psu|],s≠u
Wherein, Wsu,lFor the cost indicator vector that source node is routed to the l articles of intermediate node, PsuFor source node to intermediate node
Route set, | Pxy| for routing quantity, that is, cost indicator vector quantity of source node to intermediate node, N is the node in network
Quantity, K are network middle finger target quantity, wsu,l,kK ∈ [1, K] is the generation that source node is routed to the l articles of intermediate node in network
K-th of cost index of valence indicator vector；
Intermediate node described in step 2 to intermediate node neighbor node cost indicator vector are as follows:
Wuv,o=(wuv,o,1,wuv,o,2,...,wuv,o,K)u∈[1,N],v∈[1,N],o∈[1,|Puv|],u≠v
Wherein, Wuv,oFor the cost indicator vector of the o articles of neighbor node routing of intermediate node to intermediate node, PsuFor middle node
It puts to the route set of the neighbor node of intermediate node, | Pxy| for the routing quantity of the neighbor node of intermediate node to intermediate node
That is the quantity of cost indicator vector, N are the quantity of nodes, and K is network middle finger target quantity, wuv,o,kK ∈ [1, K] is
Intermediate node to the o articles of neighbor node of intermediate node routing cost indicator vector k-th of cost index；
Source node described in step 2 to intermediate node neighbor node cost indicator vector are as follows:
Wsv,q=Wsu,l+Wuv,o
Wherein, Wsv,q(q∈[1,|Psv|]) it is the neighbor node the q article cost mark sense that routes of the source node to intermediate node
Amount, PsvFor the route set of the neighbor node of source node to intermediate node, | Psv| for the neighbor node of source node to intermediate node
Routing quantity, that is, cost indicator vector quantity, and PsvIn arbitrarily route do not include intermediate node i.e. network node u (u ∈
[1,N])。
4. the routing according to claim 1 based on more cost indexs cuts optimization method, which is characterized in that in step 3
The cost indicator vector of neighbor node of the source node to intermediate node is respectively as follows:
Wherein, Wsv,q(q∈[1,|Psv|]) it is the neighbor node the q article cost mark sense that routes of the source node to intermediate node
Amount, PsvFor the route set of the neighbor node of source node to intermediate node, | Psv| for the neighbor node of source node to intermediate node
Routing quantity, that is, cost indicator vector quantity, and PsvIn arbitrarily route do not include intermediate node i.e. network node u (u ∈
[1,N])；
The indicator vector of any two cost described in step 3 is compared, and arbitrarily selects two cost indicator vector Wsv,g(g∈
[1,|Psv|]) and Wsv,h(h∈[1,|Psv|]) and g ≠ h, if Wsv,g(g∈[1,|Psv|]) in each element be respectively less than etc.
In Wsv,h(h∈[1,|Psv|]) in corresponding each element, i.e., W is met to any k (k ∈ [1, K])sv,g(k)≤Wsv,h(k) then
By Wsv,hThe route set P of neighbor node of the corresponding the h articles routing from source node to intermediate nodesvMiddle deletion is cut；
Traverse source node to intermediate node neighbor node all cost indicator vectors, according to above-mentioned comparison method source node into
The remaining routing quantity of the neighbor node of intermediate node is that the quantity of remaining cost indicator vector is It is source node into
The remaining route set of the neighbor node of intermediate node.
5. the routing according to claim 1 based on more cost indexs cuts optimization method, which is characterized in that in step 4
The remaining routing quantity of neighbor node of the source node to intermediate node is that the quantity of remaining cost indicator vector is For the remaining route set of the neighbor node of source node to intermediate node, ifThen secondary cutting is completed；
IfIt is by the remaining cost indicator vector of the neighbor node of source node described in step 4 to intermediate nodeIn various dimensions space HKIn cut；
The stepped sequence that the precision according to step 1 is established carries out variable step segmentation to every dimension axis in various dimensions space, will
Various dimensions space HKMultiple subspaces are divided into, the remaining cost of the neighbor node of source node described in step 4 to intermediate node
Indicator vector isCorresponding S sub-spaces are belonging respectively to, each continuous subspace separately includes M1,
M2,...,MSA residue cost indicator vector；
For separately including M1,M2,...,MSEvery sub-spaces of a cost indicator vector, according to any one subspace Qi Bao
Quantity containing remaining cost indicator vector is Mf Mf∈[M1,MS], subspace includes that cost indicator vector isCalculate separately the weighted value of each cost indicator vector are as follows:
Wherein,For minimum value, the neighbor node of corresponding source node to intermediate node
?In corresponding FzItem routing retains, remaining Mf- 1 routing fromIn deleted and cut.
6. the routing according to claim 1 based on more cost indexs cuts optimization method, which is characterized in that in step 5
It is described to select network node s (s ∈ [1, N]) to be used as source node from network node, select network node t (t ∈ [1, N]) conduct
Destination node, N are the quantity of nodes；
The cost indicator vector of source node described in step 5 to destination node is respectively Wst,1,Wst,2,...,Source node
Routing quantity, that is, cost indicator vector quantity to destination node is For the set of routes of source node to destination node
It closes, calculates separately the weighted value of each cost indicator vector are as follows:
Wherein,For minimum value, corresponding source node to destination node existsIn
nminItem routing retains, remainingItem routing fromIn deleted and cut.
7. the routing according to claim 1 based on more cost indexs cuts optimization method, which is characterized in that in step 6
The number for being iteratively repeated execution step 5 is Mopt=N-1, N are the quantity of nodes.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113328950A (en) * | 2021-05-25 | 2021-08-31 | 桂林电子科技大学 | SDN routing system construction method based on tree structure |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003061194A2 (en) * | 2001-12-26 | 2003-07-24 | Tropic Networks Inc. | Multi-constraint routine system and method |
| CN101778041A (en) * | 2009-12-31 | 2010-07-14 | 福建星网锐捷网络有限公司 | Method, device and network equipment for path selection |
| CN102523360A (en) * | 2012-01-12 | 2012-06-27 | 江苏电力信息技术有限公司 | Call routing algorithm based on multi-dimensional queue model |
| CN103036787A (en) * | 2011-10-09 | 2013-04-10 | 华为技术有限公司 | Network route convergence processing method and network route convergence processing device |
| CN104038418A (en) * | 2014-05-19 | 2014-09-10 | 暨南大学 | Routing method for hybrid topologic structure data center, path detection mechanism and message processing mechanism |
| EP2940946A1 (en) * | 2014-04-30 | 2015-11-04 | Alcatel Lucent | Method for operating a communication network |
| CN105591915A (en) * | 2014-10-22 | 2016-05-18 | 中兴通讯股份有限公司 | Maintenance method and apparatus of routing table |
| CN105847151A (en) * | 2016-05-25 | 2016-08-10 | 安徽大学 | Multi-constrained QoS (Quality of Service) routing strategy designing method for software defined network |
-
2018
- 2018-03-26 CN CN201810254608.5A patent/CN110365585B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003061194A2 (en) * | 2001-12-26 | 2003-07-24 | Tropic Networks Inc. | Multi-constraint routine system and method |
| CN101778041A (en) * | 2009-12-31 | 2010-07-14 | 福建星网锐捷网络有限公司 | Method, device and network equipment for path selection |
| CN103036787A (en) * | 2011-10-09 | 2013-04-10 | 华为技术有限公司 | Network route convergence processing method and network route convergence processing device |
| CN102523360A (en) * | 2012-01-12 | 2012-06-27 | 江苏电力信息技术有限公司 | Call routing algorithm based on multi-dimensional queue model |
| EP2940946A1 (en) * | 2014-04-30 | 2015-11-04 | Alcatel Lucent | Method for operating a communication network |
| CN104038418A (en) * | 2014-05-19 | 2014-09-10 | 暨南大学 | Routing method for hybrid topologic structure data center, path detection mechanism and message processing mechanism |
| CN105591915A (en) * | 2014-10-22 | 2016-05-18 | 中兴通讯股份有限公司 | Maintenance method and apparatus of routing table |
| CN105847151A (en) * | 2016-05-25 | 2016-08-10 | 安徽大学 | Multi-constrained QoS (Quality of Service) routing strategy designing method for software defined network |
Non-Patent Citations (4)
| Title |
|---|
| HAIZHOUBAO ET AL.: "Minimal Road-side unit placement for delay-bounded applicaitons in bus ad-hoc networks", 《IPCCC》 * |
| HUANG CHUANHE ET AL.: "A tursted routing protocol for wireless mobile ad hoc networks", 《CCWMSN》 * |
| 汪胡青: "基于Dijistra算法的多约束多播路由算法的研究", 《计算机技术与发展》 * |
| 覃匡宇: "基于多路广播树的SDN多路径路由算法", 《计算机科学》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113328950A (en) * | 2021-05-25 | 2021-08-31 | 桂林电子科技大学 | SDN routing system construction method based on tree structure |
| CN113328950B (en) * | 2021-05-25 | 2022-06-17 | 桂林电子科技大学 | SDN routing system construction method based on tree structure |
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