CN107733797A - A kind of complex network method for routing based on gravitational field - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/122—Shortest path evaluation by minimising distances, e.g. by selecting a route with minimum of number of hops
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/29—Flow control; Congestion control using a combination of thresholds
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/50—Queue scheduling
- H04L47/62—Queue scheduling characterised by scheduling criteria
- H04L47/6245—Modifications to standard FIFO or LIFO
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Abstract
The gravitational field that the present invention is excited to network transmission process interior joint using gravics is described, and establish node equations of gravitational field and transmission path to the gravitation calculation formula of packet.On this basis, it is proposed a kind of complex network routing strategy based on node gravitational field, the strategy account for the length of transmission path, on path the factor such as the Congestion Level SPCC of node and node-node transmission ability influence, and during technical problem to facing node selection, propose a kind of optimal shortest path selection strategy.The application routing policy is by effectively balance network load, the handling capacity alleviated network congestion and improve network.
Description
Technical Field
The invention relates to the field of communication, in particular to a complex network routing method based on a gravitational field.
Background
The complexity science is the science for researching the complexity of a system and the complex behaviors, characteristics and rules emerging from the interaction among all components in the complex system. In recent years, complex network theory has been widely applied to the fields of computers, control, traffic, physics, biology, sociology and the like, and research focuses mainly on two aspects of network topology complexity and dynamics process thereof. With the increasing traffic flow on the network, the network congestion is more and more serious, and how to relieve the network congestion under the condition of limited resources, improve the network throughput and ensure the efficient transmission of information becomes an increasingly urgent problem.
In order to solve the above problems, the current research mainly focuses on optimizing a network topology structure, and improving the network structure aiming at the congestion situation on the network so as to achieve the purpose of shunting; the processing capability of the network node is improved, namely the larger the processing capability is, the larger the network throughput is; thirdly, designing an efficient routing strategy, improving the throughput of the network and relieving the congestion situation by changing the routing mode of the data packets on the network, and improving the transmission capability of the whole network to a certain extent by using an effective routing algorithm, a random walk algorithm, an adjacent load routing algorithm and the like.
However, after the method is operated for a period of time, a drift phenomenon of route congestion may be caused, so that data packets passing through the current congested road section and area are induced in a large number and flow to other unobstructed (or not easily congested) road sections and areas, and the data throughput of the originally unobstructed (not easily congested) road sections or areas is increased sharply and exceeds the capacity of the original unobstructed (not easily congested) road sections or areas, thereby forming new secondary congestion.
Therefore, the invention describes the gravitational field excited by the nodes in the network transmission process by using the gravitational field theory, and establishes the gravitational field equation of the nodes and the gravitational calculation formula of the transmission path to the data packet. On the basis, a complex network routing strategy based on a node gravity field is provided, the strategy takes the influence of factors such as the length of a transmission path, the congestion degree of nodes on the path, the transmission capacity of the nodes and the like into consideration, and a selection strategy is provided when the technical problem of node selection is faced. Compared with the shortest routing algorithm, the routing strategy can effectively balance network load, relieve network congestion and improve network throughput.
Disclosure of Invention
On the basis, the invention provides a complex network routing method based on a gravitational field, which comprises the following steps:
1) Acquiring neighbor node set N 'of node v where data packet is located currently' v ；
2) Acquisition instituteNeighbor node set N' v The neighbor node i which the data packet has not passed through in the transmission path forms a neighbor node set N v ，i∈N v ；
3) Obtaining the shortest path from any neighbor node i to the target node t, extracting the nodes forming the shortest path to form a shortest node set N it Calculating the attraction F of the shortest path from the neighbor node i to the target node t to the data packet it In which the attractive force F it Comprises the following steps:
wherein, F it The gravity of the shortest path from a neighbor node i to a target node t to a data packet is shown, N is the shortest node set N it Number of nodes of (F) j Is the shortest node set N it Any node j (j is epsilon N) it ) An attraction to the node v, wherein attraction F j Comprises the following steps:
wherein, F j Is the attraction of node j to node v; k is a constant; c. C j The transmission capacity of the node j is the maximum number of data packets that can be processed by the node j in unit time; q. q of j The number of data packets in the current cache queue of the node j is determined; c. C j /q j The degree of openness of the current node j can be regarded; d is a radical of jv The length of the shortest path from the node j to the node v; alpha and gamma are two adjustable parameters which are respectively used for adjusting the dependence degree of data transmission on the node unblocked degree, the node transmission capacity and the path length, and alpha>0；γ>0；
4) Computing the set of neighbor nodes N v The shortest path from all the neighbor nodes to the target node t is attracted to the data packet to obtain an attraction set { F } it }；
5) Acquiring the attractive force set{F it Maximum attraction value F in max ，F max ＝max{F it Determining the maximum attraction value F max And the corresponding neighbor node takes the node as the next routing node for transmitting the data packet in the node v.
Preferably, if the attractive force set { F } it There are a plurality of the most attractive forces F max Approximate attraction force values F of approximately equal nt Approximately equal to | F nt -F max |&Beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F is obtained nt And the maximum attractive force value F max And the corresponding neighbor node with the shortest path from the neighbor node to the target node t is used as the next routing node for transmitting the data packet in the node v.
Preferably, if the attractive force set { F } it There are a plurality of the maximum attractive forces F max Approximate attraction force values F that are approximately equal nt Approximately equal to | F nt -F max |&Beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F is obtained nt And the maximum force value F max Average number of neighbor nodes of all nodes in shortest path from corresponding neighbor node to target node tWherein u =1,2 \8230p, p +1; where p is the number of approximate attraction values, m is the number of nodes in the shortest path, a i The number of neighbor nodes of any node i in the shortest path is counted; obtaining the minimum average neighbor node numberThe minimum meanNumber of average neighbor nodesThe corresponding shortest path is the shortest path transmitted by the data packet, and the neighbor node corresponding to the shortest path is the next routing node transmitted by the data packet in the node v.
Preferably, if the attractive force set { F } it There are a plurality of the maximum attractive forces F max Approximate attraction force values F of approximately equal nt Approximately equal to | F nt -F max |&Beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F in the last time period T is obtained nt And the maximum force value F max Average betweenness center value of all nodes in shortest path from corresponding neighbor node to target node tObtaining the minimum average mean center valueThe minimum mean center valueThe corresponding shortest path is the shortest path transmitted by the data packet, the neighbor node corresponding to the shortest path is the next routing node transmitted by the data packet in the node v,
whereinIs composed of
Wherein u =1,2 \ 8230p, p +1, p is the number of approximate attraction force values, m is the number of nodes in the shortest path, B i A medium center value of any node i in the shortest path, wherein，
Wherein N is the number of nodes of the network; b is a mixture of i The number of all processed data packets passing through the node i in the time period T is specifically
Wherein, t 0 As a result of the current point in time,the number of data packets which pass through the node i in the transmission process and take the node v as a source node and the node t as a target node is used.
Preferably, α >0 in said step 3); gamma >0.
Detailed Description
The invention will now be further described with reference to examples. It should be noted that the description of the embodiments is provided to help understanding of the present invention, and is not intended to limit the present invention.
Example one
For a given complex network, assuming that all nodes on the network have the functions of routing, packet receiving and packet sending, and the network load in an initial state is 0, then generating R data packets in each time step and randomly selecting a source node and a target node, automatically adding the generated data packets to the tail of a cache queue of the source node, wherein each node can only send ci data packets at most in a unit time step, and the cache queue of the node has infinite length and adopts a first-in first-out mode. In the network transmission process, a data packet is always sent to a certain neighbor node by a current node, and if the neighbor node is a target node of the data packet, the data packet is deleted; otherwise, entering the buffer queue of the neighbor node according to a given routing strategy.
From the perspective of gravitational field theory, the greater the gravitational force Fit of a path to a packet, the greater the probability that the packet will be transmitted along the path. Accordingly, a method of gravity-field-based complex network routing, the method comprising:
1) Acquiring neighbor node set N 'of node v where data packet is located currently' v ；
2) Acquiring neighbor node set N' v The neighbor node i which the data packet has not passed through in the transmission path forms a neighbor node set N v ，i∈N v ；
3) Obtaining the shortest path from any neighbor node i to the target node t, extracting the nodes forming the shortest path to form a shortest node set N it Calculating the attraction F of the shortest path from the neighbor node i to the target node t to the data packet it In which the attractive force F it Comprises the following steps:
wherein, F it The gravity of the shortest path from a neighbor node i to a target node t to a data packet is obtained, and N is the shortest node set N it Number of nodes of, F j Is the shortest node set N it Any node j (j is epsilon N) it ) An attraction force to the node v, wherein attraction force F j Comprises the following steps:
wherein, F j Is the attraction of node j to node v; k is a constant; c. C j The transmission capacity of the node j is the maximum number of data packets that can be processed by the node j in unit time; q. q.s j The number of data packets in the current cache queue of the node j is determined; c. C j /q j Can be regarded as the current sectionThe degree of openness of point j; d is a radical of jv The length of the shortest path from the node j to the node v; alpha and gamma are two adjustable parameters which are respectively used for adjusting the dependence degree of data transmission on the node unblocked degree, the node transmission capacity and the path length, and alpha>0；γ>, 0; as can be seen from the gravitational field equation, the gravitational effect of a node on a data packet is proportional to the alpha power of the product of the transmission capability of the node and the degree of openness of the node, and inversely proportional to the gamma power of the shortest path length from the node to the data packet. It can be seen that the physical meaning similar to the gravitational field theory is expressed
4) Calculating the neighbor node set N v The shortest path from all the neighbor nodes to the target node t is attracted to the data packet to obtain an attraction set { F } it }；
5) Obtaining the attractive force set { F it Maximum attraction value F in max ，F max ＝max{F it -determining said maximum force value F max And the corresponding neighbor node takes the node as the next routing node for transmitting the data packet in the node v.
Example two
The network is a huge topological network, and the calculation method in the first embodiment may have the maximum stress value F max The difference between the gravity values and the rest shortest paths is small, even the difference value is close to neglect, at this time, the shortest path with the largest gravity value is still selected and is not necessarily the best selection.
To solve the above-mentioned drawback, it is assumed that there is a set approximate threshold β, β>, 0 if attraction sets { F it There are a plurality of the maximum attractive forces F max Approximate attraction force values F that are approximately equal nt Approximately equal to | F nt -F max |&Beta, then the maximum attractive force value F is indicated max The corresponding shortest path is not necessarily the optimal path, and in this case, the approximate attraction force value F needs to be adjusted nt And maximum gravitational force F max And selecting the corresponding shortest path to ensure that the data packet enters the optimal channel. SelectingThe selection strategy mainly comprises three schemes.
First, if the attractive force set { F } it There are a plurality of the maximum attractive forces F max Approximate attraction force values F that are approximately equal nt Approximately equal to | F nt -F max |&Beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F is obtained nt And the maximum force value F max And the corresponding neighbor node with the shortest path from the neighbor node to the target node t is used as the next routing node for transmitting the data packet in the node v.
Or, if the attractive force set { F } it There are a plurality of the most attractive forces F max Approximate attraction force values F that are approximately equal nt Approximately equal to | F nt -F max |&Beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F is obtained nt And the maximum attractive force value F max Average number of neighbor nodes of all nodes in shortest path from corresponding neighbor node to target node tWherein u =1,2 \ 8230p, p +1; where p is the number of approximate attraction values, m is the number of nodes in the shortest path, a i The number of neighbor nodes of any node i in the shortest path is counted; obtaining the minimum average neighbor node number thereinThe minimum number of average neighbor nodesThe corresponding shortest path is transmitted by the data packetAnd a neighbor node corresponding to the shortest path is the next routing node transmitted by the data packet in the node v.
Again, if attraction sets { F it There are a plurality of the most attractive forces F max Approximate attraction force values F of approximately equal nt Approximately equal to | F nt -F max |&l is beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F in the last time period T is obtained nt And the maximum attractive force value F max Average betweenness center value of all nodes in shortest path from corresponding neighbor node to target node tObtaining the minimum average mean center valueThe minimum mean valueThe corresponding shortest path is the shortest path transferred by the data packet, the neighbor node corresponding to the shortest path is the next routing node transferred by the data packet in the node v,
whereinIs composed of
Wherein u =1,2 \ 8230p, p +1, p is the number of approximate attraction values, m is the number of nodes in the shortest path, B i Is the betweenness value of any node i in the shortest path, wherein,
wherein N is the number of nodes of the network; b i The number of all processed data packets passing through the node i in the time period T is specifically
Wherein, t 0 As a result of the current point in time,the number of data packets which pass through the node i in the transmission process and take the node v as a source node and the node t as a target node is used.
As described above, the present invention can be preferably implemented. Variations, modifications, substitutions, integrations and changes of these embodiments may be made without departing from the principle and spirit of the invention, and still fall within the scope of the invention.
Claims (5)
1. A gravity field-based complex network routing method is characterized by comprising the following steps:
1) Acquiring neighbor node set N 'of node v where data packet is located currently' v ；
2) Acquiring neighbor node set N' v The neighbor node i which the data packet has not passed through in the transmission path forms a neighbor node set N v ，i∈N v ；
3) Obtaining the shortest path from any neighbor node i to the target node t, extracting the nodes forming the shortest path to form a shortest node set N it Calculating the attraction F of the shortest path from the neighbor node i to the target node t to the data packet it In which the attractive force F it Comprises the following steps:
wherein, F it For neighbor node i to targetThe gravitation of the shortest path of the node t to the data packet, N is the shortest node set N it Number of nodes of, F j Is the shortest node set N it Any node j (j is epsilon N) it ) An attraction to the node v, wherein attraction F j Comprises the following steps:
wherein, F j Is the attraction of node j to node v; k is a constant; c. C j The transmission capacity of the node j is the maximum number of data packets that the node j can process in unit time; q. q.s j The number of data packets in the current cache queue of the node j is determined; c. C j /q j Can be regarded as the degree of openness of the current node j; d jv The length of the shortest path from the node j to the node v; alpha and gamma are two adjustable parameters which are respectively used for adjusting the dependence degree of data transmission on the node unblocked degree, the node transmission capacity and the path length;
4) Calculating the neighbor node set N v The shortest path from all the neighbor nodes to the target node t is attracted to the data packet to obtain an attraction set { F } it }；
5) Obtaining the attractive force set { F it Maximum attraction value F in } max ，F max ＝max{F it Determining the maximum attraction value F max And the corresponding neighbor node takes the node as the next routing node for transmitting the data packet in the node v.
2. The gravity field-based complex network routing method according to claim 1, wherein if the attractive force set { F } it There are a plurality of the maximum attractive forces F max Approximate attraction force values F of approximately equal nt Approximately equal to | F nt -F max |&l is beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F is obtained nt And the maximum force value F max Corresponding neighbor node to targetAnd the neighbor node with the shortest path of the node t is used as the next routing node for transmitting the data packet in the node v.
3. The gravity field-based complex network routing method according to claim 1, wherein if the attractive force set { F } it There are a plurality of the most attractive forces F max Approximate attraction force values F of approximately equal nt Approximately equal to | F nt -F max |&Beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F is obtained nt And the maximum force value F max Average number of neighbor nodes of all nodes in shortest path from corresponding neighbor node to target node tWherein u =1,2 \ 8230p, p +1;where p is the number of approximate attraction values, m is the number of nodes in the shortest path, a i Counting the number of neighbor nodes of any node i in the shortest path; obtaining the minimum average neighbor node number thereinThe minimum number of average neighbor nodesThe corresponding shortest path is the shortest path transmitted by the data packet, and the neighbor node corresponding to the shortest path is the next routing node transmitted by the data packet in the node v.
4. The gravity field-based complex network routing method according to claim 1, wherein if the attractive force set { F } it There are a plurality of the most attractive forces F max Approximate attraction force values F that are approximately equal nt Approximately equal to | F nt -F max |&l is beta, wherein, F nt ∈{F it Is an approximate threshold and beta>, 0, the approximate attraction force value F in the last time period T is obtained nt And the maximum force value F max Average betweenness center value of all nodes in shortest path from corresponding neighbor node to target node tObtaining the minimum average mean center valueThe minimum mean center valueThe corresponding shortest path is the shortest path transmitted by the data packet, the neighbor node corresponding to the shortest path is the next routing node transmitted by the data packet in the node v,
whereinIs composed of
Wherein u =1,2 \ 8230p, p +1, p is the number of approximate attraction force values, m is the number of nodes in the shortest path, B i Is the betweenness center value of any node i in the shortest path, wherein,
wherein N is the number of nodes of the network; b i The number of all processed data packets passing through the node i in the time period T is specifically
Wherein, t 0 Is the current point in time and is,the number of data packets which pass through the node i in the transmission process and take the node v as a source node and the node t as a target node is used.
5. The gravity field-based complex network routing method according to claim 1, wherein α >0 in the step 3); gamma >0.
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Application publication date: 20180223 |