CN103200096A - Heuristic routing method avoiding key nodes in complex network - Google Patents
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- CN103200096A CN103200096A CN2013100785680A CN201310078568A CN103200096A CN 103200096 A CN103200096 A CN 103200096A CN 2013100785680 A CN2013100785680 A CN 2013100785680A CN 201310078568 A CN201310078568 A CN 201310078568A CN 103200096 A CN103200096 A CN 103200096A
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Abstract
To solve the problem of routing optimization in a complex network, the invention discloses a heuristic routing method avoiding key nodes in the complex network. On the basis of maintaining original network connection unchanged and based on the routing of the shortest path, by changing weight of the edges connecting key nodes and reducing the maximum node in the network, the flow load is distributed again between the key nodes and non-key nodes, and flow of the key nodes is reduced. By adopting the heuristic routing method, larger network capacity, a routing length closer to the shortest path and higher transmission performance under load attack can be provided, network congestion can be relieved effectively, and good defense effect on cascade invalidation caused by congestion of the key nodes can be achieved.
Description
Technical field
The present invention relates to avoid in a kind of complex network route-optimization technique, particularly a kind of complex network the heuristic method for routing of key node.
Background technology
Complex network becomes the focus of a lot of field scientist researchs in recent years; huge potential using value is being contained in the research of complex network; yet the fragility that complex network shows; become its big defective in actual applications; especially facing under the multiple complex attacks such as attack at random, calculated attack, concerted attack, distributed attack; the fail safe of complex network more and more is subjected to serious threat, is one of the focus that faces now of people and difficult point problem to the defence of complex network and guard method research.
The large-scale communication network network can be considered complex network, and this complex communications networks that has dissimilar nodes, link and other resource tends to cause the flow load skewness, congested usually appearing on some key node in the network.Key node has more connection, has also therefore born more traffic transport task, has occurred the serious imbalance of load between node thus, and key node becomes the easiest network that makes and produces congested node.If a key node lost efficacy, the load that it is born will be re-assigned to other node in the network, and the cascade that may cause network that heavily distributes of so a large amount of loads was lost efficacy, and made whole internet cause catastrophic destruction.In order to improve the efficient of transfer of data, avoid or reduce the network congestion phenomenon, particularly avoid high load capacity congestion situation in the key node, a method is exactly to revise the bottom-layer network structure of network, and another kind of method is the method for routing of seeking more to optimize.Because change the higher and difficult realization of cost of network bottom layer structure, therefore, the researcher drops into more energy aspect the method for routing of seeking more to optimize.For example,
(Yang Junlong such as Yang Junlong, Yu HeWei.Optimizing Multi-Path Routing by Avoiding Key Nodes.[C] .Proceedings of IC-BNMT2009.2009.) propose by avoiding the multi-path routing method MRABKN of key node, they have provided a simple and effective detection key node and have avoided their method, analog result has shown that this method has good performance obtaining nonintersecting paths, can slow down the congested of key node effectively, improve the reliability of network.(Gang Yan such as the Gang Yan of Chinese University of Science and Technology, Tao Zhou, Bo Hu, Zhong-Qian Fu, Bing-Hong Wang.Efficient routing on complex networks[J] .Phys.Rev.E, 73:046108.2006.) the active path routing policy proposed, this active path routing policy is not to seek the shortest path as the shortest path routing algorithm, but seek " active path ", so-called " active path " is exactly to avoid those may produce congested key node in effective path.(Cun-Lai Pu such as Cun-Lai Pu, Si-Yuan Zhou, et al.Efficient and robust routing on scale-free networks[J] .Physica A392 (866-871) .2012.) improve on the basis of effective route, positive route (AR) strategy has been proposed, the AR stragetic innovation cost function of path P, and the parameters such as size that lost efficacy of the capacity by analog network and cascade, proved should strategy than effective routing policy more excellent a little aspect the cascade inefficacy of defending against network.Chen Hua very waits (Chen Hualiang, Liu Zhongxin, Deng. a kind of weighting routing policy research [J] of complex network. Acta Physica Sinica .2009.58 (9): 6068-6073.) proposed the long-pending weighting routing policy of degree, this strategy calculate arbitrary node between during route, realize the equilibrium that the load transmission distributes by the weight that changes the path, experimental result also shown the defence key node congested, improve and to be similar to the active path routing policy aspect the network capacity, occur at network having improved network transmission efficiency under the situation of high capacity.(Guo Lei such as Guo Lei, Wang Binqiang, Deng. a kind of multipath routing algorithm [J] towards key node. computer engineering and application .44 (26) 119-121.2008.) in order to solve the congestion problems of key node, on the basis of researching and analysing the multirouting agreement, a kind of multipath routing algorithm (KNMRA) towards the key node shunting has been proposed, KNMRA makes the load in the network be tending towards balanced effectively, has improved the congestion phenomenon on the key node greatly.
Yet effective method for routing of above-mentioned several complex networks has all thoroughly changed the method for routing of the SPF of using mostly in the reality, realizes comparatively complexity, and route length and the shortest path difference of trying to achieve are bigger.Therefore, how to seek a kind of simple, effectively method for routing becomes research difficult point and the focus in the complex network route-optimization technique field.
Summary of the invention
Technical problem solved by the invention is to provide the heuristic method for routing of avoiding key node in a kind of complex network.
The technical solution that realizes the object of the invention is: avoid the heuristic method for routing of key node in a kind of complex network, may further comprise the steps:
Step 1, use complex network node Jie number determine method determine complex network G=(V, E) in each node v
iJie count b
iWherein V represents node set, and E represents limit set, w (v
i, v
j) expression node v
iWith node v
jBetween limit (v
i, v
j) on weights, given network traffics delay constraint constant D arranges R
c=0, R wherein
cThe expression network capacity;
Step 2, arrange from big to small according to the value of node Jie number, as key node, wherein r is the parameter of determining according to whole complex network scale with the node of r% before coming, and 5≤r≤20 supposes that key node is that m is individual, then key node set V
k={ v
K1, v
K2, Kv
Km, v wherein
K1Expression Jie counts the node of maximum, by that analogy;
Step 3, increase the weights on all limits that link to each other with each key node according to corresponding step delta, wherein step delta is the parameter definite according to the weights of whole complex network, and (v is supposed in 1≤Δ≤10
Ki, v
j) be key node v
KiA limit that links to each other, that is, and w (v
Ki, v
j)=w (v
Ki, v
j)+Δ;
Step 4, use complex network node Jie number determine that method redefines each node v in the complex network
iJie count b
i
Step 5, utilize the Floyd shortest-path method determine all nodes between shortest path, namely form routing table;
Step 6, utilize formula
Determine R
C_now, wherein, R
C_nowRepresent current network capacity, n represents the node sum of complex network, b
MaxBe the maximum of current all node Jie numbers, that is, and b
Max=max{b
1, b
2... b
n;
Step 7, judgement current network capacity R
C_nowWith network capacity R
cValue, if R
C_nowR
c, and current network traffics time delay is less than given network traffics delay constraint constant D, then R
c=R
C_now, forward step 3 to and repeat; Otherwise whole process finishes, and the routing table of current preservation is as the route of the near-optimization of trying to achieve.
The present invention compared with prior art, its remarkable advantage is: the routing optimality problem that 1) the present invention is directed to complex network, on shortest path route basis, a kind of heuristic method for routing of avoiding key node is provided, flow load is heavily distributed between key node and non-key node, reduce the flow of key node, avoid key node to occur because load is overweight losing efficacy; Adopt method of the present invention on the basis of shortest path route, to reduce the flow of key node, defense reaction is preferably played in congested " the cascade inefficacy " that causes because of key node; 2) method of the present invention makes whole network reach the approximate maximum ability of handling flow as far as possible, and bigger network capacity can be provided; 3) method of the present invention is simply effective, has more the route length near shortest path; 4) method of the present invention has improved the transmission performance of network under load is attacked, and has alleviated the congestion condition of network.
Description of drawings
Fig. 1 is overview flow chart of the present invention.
Fig. 2 is complex network instance graph of the present invention.
Fig. 3 is the contrast of the network capacity under four kinds of different method for routing schematic diagram in the emulation experiment of the present invention.
Fig. 4 is the congested formation maximum average length contrast schematic diagram under different loads is attacked in the emulation experiment of the present invention.
Fig. 5 is the data transmission period contrast schematic diagram under different loads is attacked in the emulation experiment of the present invention.
Embodiment
Below in conjunction with accompanying drawing the present invention is described in further detail, for convenience of explanation, provide as giving a definition and describing.
Definition 1: complex network model
Complex network model with figure G represent, G=(V, E).V={v
1, v
2..., v
nBe node set, E={e
1, e
2..., e
mV * V is limit set.v
i∈ V, (i=1,2 ..., n), a node in the expression network, (v
i, v
j) ∈ E, expression is to node v
iTo node v
jA limit, w (v
i, v
j) expression limit (v
i, v
j) weights.
Definition 2: network traffics dynamic model: the Internet is modeled as complex network, each node is all regarded as main frame or router, a queue assignment that satisfies first-in first-out rule is to each node in the network, in each step network R data packet generation arranged, source node and the destination node of each packets of information are distributed randomly, in case a packet has arrived destination node, this packet removes from network; If the present node of a packet arrival is not destination node, this packet will be delivered to neighbor node according to the routing table that method for routing generates, and suppose that the quantity of the each maximum data packet of transmitting of a node is constant C.
Definition 3: network capacity: if network generation quantity of data packets is R in the time per unit, when R was less, the propagation delay time of packet was directly proportional with the jumping figure in the path of its process, the packet that network energy normal process produces.When the load of network was increased gradually, the load of some node significantly increased in the network, and network begins to take place congestion phenomenon, network generation quantity of data packets R in the time per unit when congested flow occurring at first in the define grid
cBe network capacity.
Network capacity R
cThe maximum capacity that has directly reflected the network processes load is as R＜R
cThe time, the packet that produces in the network and the packet of delivery are balances; As R＞R
cThe time, this balance is broken, and occurs flow congestion in the network, so it has also reflected the phase transition of flow dynamics.
Network capacity R
cBy
Calculate, wherein n represents the node sum of complex network, b
MaxBe the maximum of current all node Jie numbers, that is, and b
Max=max{b
1, b
2... b
n.Obviously, in order to obtain maximum network capacity, defending against network is congested to greatest extent, and Jie maximum in the network counts b
MaxShould be reduced as far as possible.
Based on above-mentioned definition, starting point of the present invention is when computing node Jie counts, can be by increasing the weight calculation route that links around the key node again, change the flow that some passed through this key node originally, make flow flow to unused relatively node processing from initial busy node, thereby defending against network is congested to greatest extent.
Therefore, in order to find a kind of simple and effective complex network method for routing, the present invention is on the basis of shortest path route, by changing the weight on the limit that connects key node, reduce maximum node Jie number in the network, flow load is heavily distributed between key node and non-key node, reduce the flow of key node, make whole network reach the approximate maximum ability of handling flow as far as possible, thereby defense reaction is preferably played in congested " the cascade inefficacy " that causes because of key node.
To achieve these goals, in conjunction with Fig. 1, the invention discloses a kind of heuristic method for routing of avoiding key node in the complex network, its detailed process is:
Step 1: given complex network G=(V, E), wherein V represents node set, E represents limit set, w (v
i, v
j) expression limit (v
i, v
j) weights, given network traffics delay constraint D, for example, D=50ms arranges R
c=0, R wherein
cThe expression network capacity;
Step 2: use complex network node Jie number to determine that method determines each node v in the complex network
iJie count b
i
Step 3: the value according to node Jie number is arranged from big to small, and as key node, wherein r is a parameter according to whole complex network adjustable scale with the node of r% before coming, and 5≤r≤20 supposes that key node is that m is individual, then key node set V
k={ v
K1, v
K2... v
Km, v wherein
K1Expression Jie counts the node of maximum, by that analogy;
In conjunction with Fig. 2, Fig. 2 is that a node number is 60 complex network example, and the number on limit is 116.The value of determining all node Jie numbers in this definite complex network of method with complex network node Jie number is as shown in table 1:
The value of all node Jie numbers in the table 1 complex network example
| Node ID | Node Jie number | Node ID | Node Jie |
| 0 | 349.686 | 30 | 1.461 |
| 1 | 29.923 | 31 | 1.333 |
| 2 | 582.062 | 32 | 23.598 |
| 3 | 47.192 | 33 | 23.684 |
| 4 | 241.576 | 34 | 48.266 |
| 5 | 526.193 | 35 | 5.623 |
| 6 | 208.873 | 36 | 0.000 |
| 7 | 100.210 | 37 | 1.461 |
| 8 | 5.131 | 38 | 2.811 |
| 9 | 65.012 | 39 | 21.969 |
| 10 | 20.794 | 40 | 0.000 |
| 11 | 54.223 | 41 | 6.000 |
| 12 | 22.038 | 42 | 7.208 |
| 13 | 100.375 | 43 | 5.295 |
| 14 | 18.733 | 44 | 1.250 |
| 15 | 10.840 | 45 | 5.615 |
| 16 | 40.790 | 46 | 8.345 |
| 17 | 0.000 | 47 | 5.552 |
| 18 | 17.697 | 48 | 4.398 |
| 19 | 23.731 | 49 | 0.000 |
| 20 | 6.726 | 50 | 0.750 |
| 21 | 44.084 | 51 | 3.932 |
| 22 | 5.623 | 52 | 2.117 |
| 23 | 4.104 | 53 | 0.000 |
| 24 | 14.577 | 54 | 4.734 |
| 25 | 8.768 | 55 | 1.390 |
| 26 | 0.000 | 56 | 4.029 |
| 27 | 0.000 | 57 | 4.398 |
| 28 | 141.470 | 58 | 4.104 |
| 29 | 0.500 | 59 | 7.744 |
In conjunction with the complex network example of Fig. 2, the value of node Jie number is arranged from big to small, suppose r=10, our node (60*10%=6) of preceding 10% is as key node, and is as shown in table 2.
Jie's number of preceding 6 key nodes of table 2
| Sequence number | Node ID | Node Jie number |
| 1 | 2 | 582.062 |
| 2 | 5 | 526.193 |
| 3 | 0 | 349.686 |
| 4 | 4 | 241.576 |
| 5 | 6 | 208.873 |
| 6 | 28 | 141.470 |
Then, key node set V
k={ v
K1, v
K2... v
K6}={ v
2, v
5, v
0, v
4, v
6, v
28.
Step 4: increase the weights on all limits that link to each other with each key node according to corresponding step delta, wherein step delta can arrange according to the weights of whole complex network, supposes (v
Ki, v
j) be key node v
KiA limit that links to each other, that is, and w (v
Ki, v
j)=w (v
Ki, v
j)+Δ; Δ=3;
Step 5: use complex network node Jie number to determine that method redefines each node v in the complex network
iJie count b
i
Step 6: utilize the Floyd shortest-path method calculate all nodes between shortest path, and upgrade routing table;
Step 7: utilize formula
Determine R
C_now, wherein, R
C_nowRepresent current network capacity, n represents the node sum of complex network, b
MaxBe the maximum of current all node Jie numbers, that is, and b
Max=max{b
1, b
2... b
n;
Step 8: if R
C_now＞R
c, and current network traffics time delay is less than given network traffics delay constraint D, then R
c=R
C_now, forward step 4 to and repeat; Otherwise whole process finishes, and the routing table of current preservation is as the route of the near-optimization of trying to achieve.
In order to verify validity of the present invention, chosen shortest path route (SP) method, classical long-pending weight path (DM) method for routing of degree and active path (ER) method for routing three kinds of different method for routing and the inventive method (being called AKNHR) and do not had the scale network model at BA and carried out the emulation experiment contrast.
(1) experiment 1: four kinds of network capacitys that method for routing is tried to achieve under the heterogeneous networks node, as shown in Figure 3.
Find out easily that from Fig. 3 method of the present invention has improved network capacity to a great extent, such as when the BA number of network node n=1200, the network capacity of using SPF routing algorithm (SP) to try to achieve is 18, and the network capacity of utilizing the inventive method to try to achieve is 162.8, be under the shortest path more than 9 times, and be higher than active path (ER) classical in the complex network and spend long-pending weight path (DM) method for routing, clearly, method of the present invention trends towards optimum in network capacity optimization.
(2) experiment 2: different routing policies and congested formation maximum average length under different high capacities are attacked, as shown in Figure 4.
We simulate and have generated a node number is that 1500 BA does not have a scale network, simulated the average length of the congested formation of network node under above-mentioned four kinds of methods in this topology, simulate by test of many times, recorded the average length of the congested formation of network node in the different moment, getting wherein, maximum is the maximum average length of network congestion formation, Fig. 4 has portrayed the maximum average length of the network congestion formation under the heterogeneous networks load is attacked, therefrom attack at different loads as can be seen, method of the present invention has been alleviated the congestion condition of network preferably.
(3) experiment 3: the data transmission period under different routing policies and different loads are attacked, as shown in Figure 5.
We are that 1500 BA does not have the network latency of having simulated in the scale network under the heterogeneous networks load at same node number; attack packets rate and the relation between the data route transmission time under four kinds of methods have been recorded; analog result such as Fig. 5; as can be seen from the figure the inventive method is relatively low on total data transmission period; because it based on the key node equilibrium load Distribution of complex network node; improved the transmission performance of network under load is attacked preferably, finally the defending against network generation that cascade was lost efficacy under high capacity is attacked effectively; the normal operation of protecting network.
This shows, the present invention heavily distributes between key node and non-key node by flow load, reduce the flow of key node, make whole network reach the approximate maximum ability of handling flow as far as possible, thereby defense reaction is preferably played in congested " the cascade inefficacy " that causes because of key node, reached intended purposes.
Claims (1)
1. avoid the heuristic method for routing of key node in the complex network, it is characterized in that, may further comprise the steps:
Step 1, use complex network node Jie number determine method determine complex network G=(V, E) in each node v
iJie count b
iWherein V represents node set, and E represents limit set, w (v
i, v
j) expression node v
iWith node v
jBetween limit (v
i, v
j) on weights, given network traffics delay constraint constant D arranges R
c=0, R wherein
cThe expression network capacity;
Step 2, arrange from big to small according to the value of node Jie number, as key node, wherein r is the parameter of determining according to whole complex network scale with the node of r% before coming, and 5≤r≤20 supposes that key node is that m is individual, then key node set V
k={ v
K1, v
K2... v
Km, v wherein
K1Expression Jie counts the node of maximum, by that analogy;
Step 3, increase the weights on all limits that link to each other with each key node according to corresponding step delta, wherein step delta is the parameter definite according to the weights of whole complex network, and (v is supposed in 1≤Δ≤10
Ki, v
j) be key node v
KiA limit that links to each other, that is, and w (v
Ki, v
j)=w (v
Ki, v
j)+Δ;
Step 4, use complex network node Jie number determine that method redefines each node v in the complex network
iJie count b
i
Step 5, utilize the Floyd shortest-path method determine all nodes between shortest path, namely form routing table;
Step 6, utilize formula
Determine R
C_now, wherein, R
C_nowRepresent current network capacity, n represents the node sum of complex network, b
MaxBe the maximum of current all node Jie numbers, that is, and b
Max=max{b
1, b
2... b
n;
Step 7, judgement current network capacity R
C_nowWith network capacity R
cValue, if R
C_nowR
c, and current network traffics time delay is less than given network traffics delay constraint constant D, then R
c=R
C_now, forward step 3 to and repeat; Otherwise whole process finishes, and the routing table of current preservation is as the route of the near-optimization of trying to achieve.
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| CN112187658A (en) * | 2020-09-24 | 2021-01-05 | 南京工业职业技术大学 | Congestion control method under complex network environment |
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100322244A1 (en) * | 2009-06-23 | 2010-12-23 | Nortel Networks Limited | Utilizing Betweenness to Determine Forwarding State in a Routed Network |
| CN102684981A (en) * | 2011-03-15 | 2012-09-19 | 江苏镇安电力设备有限公司 | Routing method for generalizing shortest information path |
-
2013
- 2013-03-13 CN CN201310078568.0A patent/CN103200096B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100322244A1 (en) * | 2009-06-23 | 2010-12-23 | Nortel Networks Limited | Utilizing Betweenness to Determine Forwarding State in a Routed Network |
| CN102684981A (en) * | 2011-03-15 | 2012-09-19 | 江苏镇安电力设备有限公司 | Routing method for generalizing shortest information path |
Non-Patent Citations (3)
| Title |
|---|
| 冯颜: ""复杂网络抗毁性优化策略及关键技术研究"", 《中国优秀硕士学位论文全文数据库(电子期刊)》, 31 December 2011 (2011-12-31) * |
| 张煜 等: ""复杂网络抗毁性优化研究综述"", 《信息与电脑》, 30 June 2011 (2011-06-30) * |
| 朱涛 等: ""改进的加权复杂网络节点重要度评估的收缩方法"", 《系统工程与电子技术》, 31 August 2009 (2009-08-31) * |
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