Method for selecting multi-objective immune optimization multicast router path

Abstract

The invention discloses a method for selecting a multi-objective immune optimization multicast router path, which mainly solves the problem of the optimization of multicast routers. The method has the following steps of: (1) determining an optimized target to generate a network model, and setting running parameters to generate an initial population; (2) eliminating an individual path loop; (3) calculating the individual target value to generate a current non-dominant population; (4) judging finishing conditions, if the finishing conditions are met, the current non-dominant population is output, or else, carrying out step (5); (5) calculating the individual crowding distance of the current non-dominant distance to generate an active population; (6) carrying out cloning and local searching operation on the active population; (7) carrying out recombination, variation and local search operation on the cloned population; (8) combining the current non-dominant population with the populations obtained in the steps (6) and (7) to eliminate the individual path loop; (9) calculating the individual value to refresh the current non-dominant population, and carrying out the step (4). The invention has the advantage of providing a flexible optimization scheme and is suitable for selecting the multicast router path.

Description

technical field [0001] The invention belongs to the technical field of network communication, and relates to the selection of multicast routing paths, in particular to a multi-object immune optimization multicast routing path selection method. The method can be used for multicast routing path selection under the condition of satisfying multiple service requirements. Background technique [0002] With the maturity of commercial applications under the Internet and the rapid development of high-speed broadband networks, the communication capacity of packet-switching computer networks has increased from a few Mbps to hundreds or even thousands of Mbps, network functions have become increasingly powerful, and network services have also changed from simple information transmission such as E-mall and FTP have developed into comprehensive services such as distance education, video conferencing, computer collaborative computing, data distribution and online games. These emerging com...

AI Technical Summary

Problems solved by technology

When these methods deal with multiple objectives, they usually model all QoS parameters as constrained single-objective optimization problems during modeling, or use weighted methods to convert multiple objectives into single-objective optimization, although through these The method can sometimes get a good solution, that is, find a better path scheme, but the selection scheme it provides is unique, and it cannot find a better path stably when dealing with multiple targets

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