Rapid IO routing strategy based on improved glowworm swarm optimization algorithm
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...
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2018-06-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2018054 |
| _version_ | 1828730996637302784 |
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| author | Congyue YIN,Xingming ZHANG,Quan REN,Shuai WEI |
| author_facet | Congyue YIN,Xingming ZHANG,Quan REN,Shuai WEI |
| author_sort | Congyue YIN,Xingming ZHANG,Quan REN,Shuai WEI |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T17:39:31Z |
| format | Article |
| id | doaj.art-4c7aa846730c474f84d07ebb93692a91 |
| institution | Directory Open Access Journal |
| issn | 2096-109X |
| language | English |
| last_indexed | 2024-04-12T17:39:31Z |
| publishDate | 2018-06-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj.art-4c7aa846730c474f84d07ebb93692a912022-12-22T03:22:51ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2018-06-0146526110.11959/j.issn.2096-109x.2018054Rapid IO routing strategy based on improved glowworm swarm optimization algorithmCongyue YIN,Xingming ZHANG,Quan REN,Shuai WEI 0National Digital Switching System Engineering ＆Technological Research Center,Zhengzhou 450002,ChinaAiming 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.http://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2018054rapidioglowworm swarm optimization algorithmgaussian mutationstorage mechanismquality of service |
| spellingShingle | Congyue YIN,Xingming ZHANG,Quan REN,Shuai WEI Rapid IO routing strategy based on improved glowworm swarm optimization algorithm 网络与信息安全学报 rapidio glowworm swarm optimization algorithm gaussian mutation storage mechanism quality of service |
| title | Rapid IO routing strategy based on improved glowworm swarm optimization algorithm |
| title_full | Rapid IO routing strategy based on improved glowworm swarm optimization algorithm |
| title_fullStr | Rapid IO routing strategy based on improved glowworm swarm optimization algorithm |
| title_full_unstemmed | Rapid IO routing strategy based on improved glowworm swarm optimization algorithm |
| title_short | Rapid IO routing strategy based on improved glowworm swarm optimization algorithm |
| title_sort | rapid io routing strategy based on improved glowworm swarm optimization algorithm |
| topic | rapidio glowworm swarm optimization algorithm gaussian mutation storage mechanism quality of service |
| url | http://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2018054 |
| work_keys_str_mv | AT congyueyinxingmingzhangquanrenshuaiwei rapidioroutingstrategybasedonimprovedglowwormswarmoptimizationalgorithm |