{"title":"数据中心网络的哈密顿特性 DPCell","authors":"Hui Dong;Huaqun Wang;Mengjie Lv;Weibei Fan","doi":"10.1109/TNSE.2025.3537698","DOIUrl":null,"url":null,"abstract":"Data center networks (DCNs) play an irreplaceable role in digital transformation by enabling data storage, processing, and complex computing. DPCell is a DCN built on a novel fabric of switches structure, outperforming other DCNs based on dual-port servers in scalability and bisection width. Ensuring reliable communication performance in DCNs is critical for continuous service delivery. In this paper, we investigate the reliable communication performance of DPCell from the perspective of Hamiltonian properties. We first prove that DPCell is Hamiltonian-connected. Considering the inevitability of network failures, we further prove that DPCell is a super fault-tolerant Hamiltonian network under a fault model, achieving an optimal result. The superior Hamiltonian properties of DPCell confirm its reliable communication performance, laying the foundation for deadlock-free reliable communication and fast adaptive diagnosis. We verify the theoretical results through simulation experiments and further evaluate DPCell's Hamiltonian properties under conditions exceeding the fault model limit, including structure faults caused by network attacks.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 3","pages":"1660-1676"},"PeriodicalIF":6.7000,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Hamiltonian Property of the Data Center Network DPCell\",\"authors\":\"Hui Dong;Huaqun Wang;Mengjie Lv;Weibei Fan\",\"doi\":\"10.1109/TNSE.2025.3537698\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data center networks (DCNs) play an irreplaceable role in digital transformation by enabling data storage, processing, and complex computing. DPCell is a DCN built on a novel fabric of switches structure, outperforming other DCNs based on dual-port servers in scalability and bisection width. Ensuring reliable communication performance in DCNs is critical for continuous service delivery. In this paper, we investigate the reliable communication performance of DPCell from the perspective of Hamiltonian properties. We first prove that DPCell is Hamiltonian-connected. Considering the inevitability of network failures, we further prove that DPCell is a super fault-tolerant Hamiltonian network under a fault model, achieving an optimal result. The superior Hamiltonian properties of DPCell confirm its reliable communication performance, laying the foundation for deadlock-free reliable communication and fast adaptive diagnosis. We verify the theoretical results through simulation experiments and further evaluate DPCell's Hamiltonian properties under conditions exceeding the fault model limit, including structure faults caused by network attacks.\",\"PeriodicalId\":54229,\"journal\":{\"name\":\"IEEE Transactions on Network Science and Engineering\",\"volume\":\"12 3\",\"pages\":\"1660-1676\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Network Science and Engineering\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10887023/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10887023/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
The Hamiltonian Property of the Data Center Network DPCell
Data center networks (DCNs) play an irreplaceable role in digital transformation by enabling data storage, processing, and complex computing. DPCell is a DCN built on a novel fabric of switches structure, outperforming other DCNs based on dual-port servers in scalability and bisection width. Ensuring reliable communication performance in DCNs is critical for continuous service delivery. In this paper, we investigate the reliable communication performance of DPCell from the perspective of Hamiltonian properties. We first prove that DPCell is Hamiltonian-connected. Considering the inevitability of network failures, we further prove that DPCell is a super fault-tolerant Hamiltonian network under a fault model, achieving an optimal result. The superior Hamiltonian properties of DPCell confirm its reliable communication performance, laying the foundation for deadlock-free reliable communication and fast adaptive diagnosis. We verify the theoretical results through simulation experiments and further evaluate DPCell's Hamiltonian properties under conditions exceeding the fault model limit, including structure faults caused by network attacks.
期刊介绍:
The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.