Hengjian Tang, F. Zhang, Xiaolu Zhang, Yu Zheng, Y. Wang, Junhua Qiu, Xiaohan Sun
{"title":"异步光分组交换网络中动态流量疏导的改进蚁群算法","authors":"Hengjian Tang, F. Zhang, Xiaolu Zhang, Yu Zheng, Y. Wang, Junhua Qiu, Xiaohan Sun","doi":"10.1109/ICOCN.2014.6987072","DOIUrl":null,"url":null,"abstract":"We propose an improved ant colony algorithm for dynamic traffic grooming (IACA-DTG) in asynchronous optical packets switching networks, by using of the ratio of available wavelengths and path chosen length each iteration and the dynamic information updated on the available instant wavelengths in full network, which can implement traffic grooming under shorter path and less iterations. The algorithm has been evaluated through simulation and the results show the packets blocking probability can be reduced as 0.1 and wavelength utilization ratio can be increased as 0.2, compared with original ant colony algorithm.","PeriodicalId":364683,"journal":{"name":"2014 13th International Conference on Optical Communications and Networks (ICOCN)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An improved ant colony algorithm for dynamic traffic grooming in asynchronous optical packets switching networks\",\"authors\":\"Hengjian Tang, F. Zhang, Xiaolu Zhang, Yu Zheng, Y. Wang, Junhua Qiu, Xiaohan Sun\",\"doi\":\"10.1109/ICOCN.2014.6987072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose an improved ant colony algorithm for dynamic traffic grooming (IACA-DTG) in asynchronous optical packets switching networks, by using of the ratio of available wavelengths and path chosen length each iteration and the dynamic information updated on the available instant wavelengths in full network, which can implement traffic grooming under shorter path and less iterations. The algorithm has been evaluated through simulation and the results show the packets blocking probability can be reduced as 0.1 and wavelength utilization ratio can be increased as 0.2, compared with original ant colony algorithm.\",\"PeriodicalId\":364683,\"journal\":{\"name\":\"2014 13th International Conference on Optical Communications and Networks (ICOCN)\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 13th International Conference on Optical Communications and Networks (ICOCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOCN.2014.6987072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 13th International Conference on Optical Communications and Networks (ICOCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOCN.2014.6987072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An improved ant colony algorithm for dynamic traffic grooming in asynchronous optical packets switching networks
We propose an improved ant colony algorithm for dynamic traffic grooming (IACA-DTG) in asynchronous optical packets switching networks, by using of the ratio of available wavelengths and path chosen length each iteration and the dynamic information updated on the available instant wavelengths in full network, which can implement traffic grooming under shorter path and less iterations. The algorithm has been evaluated through simulation and the results show the packets blocking probability can be reduced as 0.1 and wavelength utilization ratio can be increased as 0.2, compared with original ant colony algorithm.
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