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Method, route device and business network for establishing the business connection

A routing and business technology, applied in the field of communication, can solve problems such as large consumption of control bandwidth, congestion of control channels, and a large amount of maintenance overhead, and achieve reasonable routing and establishment effects

Inactive Publication Date: 2007-07-11
HUAWEI TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] However, in this method, in the process of establishing a connection for the business, the interaction between the MPLS / GMPLS control protocol and the routing part is complicated, and the consumption of the control bandwidth is relatively large, especially when some emergencies occur, the demand for the control bandwidth will not be met. cause control channel congestion
In addition, MPLS / GMPLS uses labels to distinguish information such as routing and service levels. Different service levels correspond to different label resources. For each level of service, a global label database in the region is required to query. For large Under the constraints of multiple Qos parameters for a large-scale network, this method requires a large tag database and hardware devices with high-efficiency processing capabilities, and also requires a lot of maintenance overhead
Moreover, since the tag resource database is generally fixed, it is difficult to dynamically divide and control service connections and resource allocation
Each node cannot save the routing structure of the entire network in real time, and it is difficult to implement a distributed hop-by-hop routing mode

Method used

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  • Method, route device and business network for establishing the business connection
  • Method, route device and business network for establishing the business connection
  • Method, route device and business network for establishing the business connection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] FIG. 2 is a schematic flow diagram of a method for establishing a connection for a service in this embodiment. As shown in the figure, the method of this embodiment includes:

[0047] Step 201: The service requests to establish a connection.

[0048] Take any service request as an example to illustrate this implementation method.

[0049] Step 202: Select ants.

[0050] For a network that does not distinguish service levels, randomly select an ant (here, the ant is a fictitious ant) ​​for a service request as an ant that selects a route for the service.

[0051] For a general network, given the topology and resource constraints of the network, it is also necessary to consider the needs of users, that is, users need a network with multiple service levels, and each user can consider it according to their own needs and costs. Select the corresponding service level, and the network will provide multi-level services for different service requirements according to different...

Embodiment 2

[0123] FIG. 11 is a schematic structural diagram of a routing device in Embodiment 2. The routing device is a node in the network. As shown in the figure, the routing device includes:

[0124] The transition probability determination unit 110 is used for the Qos of the network and the biological information concentration  of the link from this node to each neighbor node ij , to determine the transition probability p from this node to the neighbor nodes ij k , wherein each of the neighbor nodes is a neighbor node of the current node, and each of the neighbor nodes belongs to a set of nodes that have not been searched.

[0125] The route selection unit 111 is configured to select the route with the highest transition probability according to the transition probabilities determined by the transition probability determination unit 110 as the route from the current node to the next hop node searched for the service.

[0126] The service routing unit 112 is configured to establis...

Embodiment 3

[0139] FIG. 12 is a schematic diagram of the service network structure in this embodiment. As shown in the figure, the network of this embodiment includes at least one node served by a routing device. The network of this embodiment specifically includes:

[0140] The network information storage unit 121 is used to store the current Qos parameters of the network, and the Qos parameters may include: time delay, delay t delay , link length t len , jitter, hop count, packet loss rate P loss , link resource utilization P util , blocking rate P block Etc., not to list them one by one.

[0141] The biological information storage unit 122 is configured to store the biological information concentrations of links from each node in the current network to its neighbor nodes. The biological information storage unit 122 can be set on a device in the network in a centralized manner, or can be distributed on each node of the network, and each node can store the biological information conc...

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Abstract

This invention relates to communication field and discloses one method, router device, business network to establish business connection, which comprises the following steps: determining this point to neighbor point transfer probability according to the linkage biological information concentration of each points and selecting router with maximum probability as this operation to next point router with its neighbor points as this point neighbor points.

Description

technical field [0001] The invention relates to the communication field, in particular to a method for establishing a service connection in network planning, a routing device and a service network. Background technique [0002] The core of network planning is to plan the transport network according to the characteristics of the service network. The transport network planning includes network topology planning, routing planning, and survivability planning. [0003] Among modern theoretical optimization algorithms, the ant colony algorithm is commonly used, and it can be used to solve the optimal path and so on. Ant colony algorithm is a population-based simulated evolutionary algorithm inspired by the group behavior of real ants in nature, which is a kind of random search algorithm. It was first proposed by Italian scholar M.Dorigo and others. He made full use of the similarity between the process of ant colony searching for food and the famous Traveling Salesman Problem (TS...

Claims

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Application Information

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IPC IPC(8): H04L12/28
Inventor 汪广泽李彬顾畹仪
Owner HUAWEI TECH CO LTD
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