{"title":"基于热力学的鲁棒自组织网络控制熵调整","authors":"Takuya Iwai, D. Kominami, M. Murata, T. Yomo","doi":"10.1109/COMPSAC.2014.48","DOIUrl":null,"url":null,"abstract":"As key technologies for future information networks, many researchers have focused on self-organized network controls. In the process of their ordering, their robustness against environmental changes decreases while their performance increases. Therefore, their behavior in dynamic environment should retain appropriate amount of disorder. In this paper, we conduct simulation experiments and show that higher entropy leads to higher robustness against node failures.","PeriodicalId":106871,"journal":{"name":"2014 IEEE 38th Annual Computer Software and Applications Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Thermodynamics-Based Entropy Adjustment for Robust Self-Organized Network Controls\",\"authors\":\"Takuya Iwai, D. Kominami, M. Murata, T. Yomo\",\"doi\":\"10.1109/COMPSAC.2014.48\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As key technologies for future information networks, many researchers have focused on self-organized network controls. In the process of their ordering, their robustness against environmental changes decreases while their performance increases. Therefore, their behavior in dynamic environment should retain appropriate amount of disorder. In this paper, we conduct simulation experiments and show that higher entropy leads to higher robustness against node failures.\",\"PeriodicalId\":106871,\"journal\":{\"name\":\"2014 IEEE 38th Annual Computer Software and Applications Conference\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 38th Annual Computer Software and Applications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPSAC.2014.48\",\"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 IEEE 38th Annual Computer Software and Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSAC.2014.48","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thermodynamics-Based Entropy Adjustment for Robust Self-Organized Network Controls
As key technologies for future information networks, many researchers have focused on self-organized network controls. In the process of their ordering, their robustness against environmental changes decreases while their performance increases. Therefore, their behavior in dynamic environment should retain appropriate amount of disorder. In this paper, we conduct simulation experiments and show that higher entropy leads to higher robustness against node failures.