{"title":"基于DNA计算的GN算法优化","authors":"Cheng Zihang, Huang Zhen","doi":"10.1109/COMPCOMM.2016.7924915","DOIUrl":null,"url":null,"abstract":"DNA computation is a new computing model with high performance in storage of DNA molecules and parallelism of biochemical reactions, but it needs complex conditions of biochemical operation, likely astable and uncontrollable. The main work of this paper is optimizing GN algorithm to solve a graph clustering question on social networks, which simulated on computer using the DNA computation model to improve the computational efficiency. Simulation results of the Karate Club interpersonal relationship network indicate that the proposed algorithm has a better performance than traditional GN algorithm.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of GN algorithm based on DNA computation\",\"authors\":\"Cheng Zihang, Huang Zhen\",\"doi\":\"10.1109/COMPCOMM.2016.7924915\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"DNA computation is a new computing model with high performance in storage of DNA molecules and parallelism of biochemical reactions, but it needs complex conditions of biochemical operation, likely astable and uncontrollable. The main work of this paper is optimizing GN algorithm to solve a graph clustering question on social networks, which simulated on computer using the DNA computation model to improve the computational efficiency. Simulation results of the Karate Club interpersonal relationship network indicate that the proposed algorithm has a better performance than traditional GN algorithm.\",\"PeriodicalId\":210833,\"journal\":{\"name\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPCOMM.2016.7924915\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPCOMM.2016.7924915","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of GN algorithm based on DNA computation
DNA computation is a new computing model with high performance in storage of DNA molecules and parallelism of biochemical reactions, but it needs complex conditions of biochemical operation, likely astable and uncontrollable. The main work of this paper is optimizing GN algorithm to solve a graph clustering question on social networks, which simulated on computer using the DNA computation model to improve the computational efficiency. Simulation results of the Karate Club interpersonal relationship network indicate that the proposed algorithm has a better performance than traditional GN algorithm.