Chinese Journal of Network and Information Security ›› 2018, Vol. 4 ›› Issue (6): 52-61.doi: 10.11959/j.issn.2096-109x.2018054

• Papers • Previous Articles     Next Articles

Rapid IO routing strategy based on improved glowworm swarm optimization algorithm

Congyue YIN,Xingming ZHANG,Quan REN,Shuai WEI   

  1. National Digital Switching System Engineering &Technological Research Center,Zhengzhou 450002,China
  • Revised:2018-05-08 Online:2018-06-01 Published:2018-08-08
  • Supported by:
    The National Science Technology Major Project(2016ZX01012101);The National Natural Science Foundation of China(61572520);The National Natural Science Foundation of China(61521003)

Abstract:

Aiming at the problem of Qo S routing in Rapid IO network,a Rapid IO routing strategy based on improved glowworm swarm optimization algorithm was proposed.Firstly,gaussian mutation and storage mechanism were used to optimize the traditional firefly algorithm.Gaussian mutation can effectively control the scattering degree of the solution in the search space of the algorithm,so that the algorithm avoids falling into a local optimum.The storage mechanism is conducive to evaluating and storing the historical state of each glowworm,preventing information loss.Then combine the improved glowworm swarm optimization algorithm with the actual Rapid IO network Qo S problem and select the final best routing strategy.The experimental results show that in the simulated Rapid IO test network,the improved glowworm swarm optimization algorithm has a delay of 42 ms,delayed jitter of 8 ms,a minimum cost of 64 ms,and a total of 8 iterations,which is more stable than other algorithm curves.It can find the optimal solution more quickly and show the best performance,effectively solving the Qo S routing problem of Rapid IO network.

Key words: RapidIO, glowworm swarm optimization algorithm, gaussian mutation, storage mechanism, quality of service

CLC Number: 

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