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Complex network quotient space model based path search method

A path search and complex network technology, applied in the direction of network interconnection, data exchange through path configuration, etc.

Inactive Publication Date: 2009-09-16
ANHUI UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The object of the invention is to propose a path search method based on the complex network quotient space model to solve the problem of fast search for "best path" in the undirected weighted network. A route composed of roads and roads with good road conditions; in the power system, it is a transmission route with high voltage and low loss in the process of power transportation; in a computer network, it is a route composed of high-traffic network paths

Method used

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  • Complex network quotient space model based path search method
  • Complex network quotient space model based path search method
  • Complex network quotient space model based path search method

Examples

Experimental program
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Effect test

Embodiment 1

[0042] Embodiment 1: Path search method based on complex network quotient space model of road traffic network

[0043] According to China's "Technical Standards for Highway Engineering", roads are divided into five grades, and urban roads are divided into four categories: express roads, trunk roads, secondary trunk roads and branch roads. Specific urban road segments usually include highways, streets, roads, alleys, roads and other types. In cities, urban and rural areas, and between towns, road sections include expressways, national roads, provincial roads, and township roads, and roads include 4-lane, 3-lane, 2-lane, and single-lane roads. In the road traffic network diagram to be established, its network G(X, E), node z can correspond to specific locations such as cities, towns, and various intersections, and the weight t(e) on the network edge e is based on the road section , road and speed conditions to decide. When constructing a road traffic network diagram for a cert...

Embodiment 2

[0088] Embodiment 2: Path search method based on complex network quotient space model of electric power transmission network

[0089] In the power system, it is the process of power transmission. According to the voltage of long-distance transmission in my country, there are 110 kV, 220 kV, and 330 kV. According to the specific actual situation of the experimental ultra-high voltage transmission line of volts, the network G(X, E) is established, the node z is each distribution transformer, step-up and step-down, and the weight t(e) on the edge e is according to the transmission line The transmission voltage, the total length of the line, the transmission power, etc. are determined. The corresponding weight of the high transmission voltage, short total line length and large transmission power is large, and vice versa.

[0090] Now select the power system in a certain area, and label the 12 distribution transformers, step-ups and step-downs in the area in a certain order as 1, 2, ...

Embodiment 3

[0110] Embodiment 3: Path search method based on complex network quotient space model for routing in computer network

[0111] In the process of computer network routing selection, establish a network G(X, E), node z is a user or a router, and the weight t(e) on edge e is due to the path length, delay, bandwidth, load and communication between nodes cost to decide. Inside an area, node z is a user; outside the area, node z is a router. When searching for a path, first determine whether the source and destination users are in the same area. If they are in the same area, use the method that node z is the user; otherwise, determine the home router of the source and destination users, and then use node z to be the user. Router method search. For the determination of the weight t(e) on the edge e, the weight of small load, low communication cost, large bandwidth, low delay and short path is large, otherwise the weight is small.

[0112] Now select a computer network system in a ...

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Abstract

Based on the path search method of a complex network quotient space model, the invention is characterized in that equivalence relation is used for gradually classifying the coarsening of a network, so as to form a hierarchical quotient space chain, and obtain the quotient space model of the hierarchical number of each node. Then, the hierarchical numbers of the starting node and the end node to be searched for can be found in the quotient space model; according to the quotient spaces from fine to coarse in the corresponding hierarchical quotient space chain, comparison is made from the last number, the communication path between two nodes begins to be searched for from the coarsest quotient space, and then fine quotient spaces are searched for in the relatively coarse quotient spaces, until the finest quotient space. According to the hierarchical numbers of any two nodes, the distribution of 'the optimal path' between the two nodes can be found visually; further 'the optimal path' between any two nodes in the network can be found according to the hierarchical quotient space chain; then based on the model, the communication path between two nodes begins to be searched for from the coarsest quotient space to the finest quotient space after gradual refinement, until 'the optimal path' is found.

Description

Technical field: [0001] The invention belongs to the technical field of complex networks (Complex Networks) application, in particular to an undirected weighted network quotient space model and a method for path search using quotient space granularity calculation and classification. Background technique: [0002] In recent years, the qualitative analysis of complex networks has become a research hotspot. From the perspective of granular computing, these analyzes only give some macroscopic properties of complex networks at the coarsest granularity, but for solving problems under a given goal , there is only direction but no method, and there is still no substantial progress. [0003] According to the introduction of "Complex Network" (Shanghai Science and Technology Education Press, edited by Guo Lei and Xu Xiaoming, first edition in November 2006, pages 271-275), when solving the shortest path problem of complex networks, Dijkstra algorithm and Floyd's algorithm and Dijkstr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/28H04L12/46
Inventor 张燕平张铃何富贵
Owner ANHUI UNIVERSITY
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