Yuanhao Wu, Faruk V. Mutlu, Yuezhou Liu, E. Yeh, Ran Liu, C. Iordache, J. Balcas, Harvey Newman, Raimondas Sirvinskas, Michael Lo, Sichen Song, Jason Cong, Lixia Zhang, Sankalpa Timilsina, Susmit Shannigrahi, Chengyu Fan, Davide Pesavento, Junxiao Shi, L. Benmohamed
{"title":"N-DISE:基于ndn的大规模数据密集型科学数据分布","authors":"Yuanhao Wu, Faruk V. Mutlu, Yuezhou Liu, E. Yeh, Ran Liu, C. Iordache, J. Balcas, Harvey Newman, Raimondas Sirvinskas, Michael Lo, Sichen Song, Jason Cong, Lixia Zhang, Sankalpa Timilsina, Susmit Shannigrahi, Chengyu Fan, Davide Pesavento, Junxiao Shi, L. Benmohamed","doi":"10.1145/3517212.3558087","DOIUrl":null,"url":null,"abstract":"To meet unprecedented challenges faced by the world's largest data- and network-intensive science programs, we design and implement a new, highly efficient and field-tested data distribution, caching, access and analysis system for the Large Hadron Collider (LHC) high energy physics (HEP) network and other major science programs. We develop a hierarchical Named Data Networking (NDN) naming scheme for HEP data, implement new consumer and producer applications to interface with the high-performance NDN-DPDK forwarder, and build on recently developed high-throughput NDN caching and forwarding methods. We integrate NDN systems concepts and algorithms with the mainstream data distribution, processing, and management system of the Compact Muon Solenoid (CMS) experiment. We design and prototype stable, high-performance virtual LANs (VLANs) over a continental-scale wide area network testbed. In extensive experiments, our proposed integrated system, named NDN for Data-Intensive Science Experiments (N-DISE), is shown to deliver LHC data over the wide area network (WAN) testbed at throughputs exceeding 31 Gbps between Caltech and StarLight, with dramatically reduced download time.","PeriodicalId":165903,"journal":{"name":"Proceedings of the 9th ACM Conference on Information-Centric Networking","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"N-DISE: NDN-based data distribution for large-scale data-intensive science\",\"authors\":\"Yuanhao Wu, Faruk V. Mutlu, Yuezhou Liu, E. Yeh, Ran Liu, C. Iordache, J. Balcas, Harvey Newman, Raimondas Sirvinskas, Michael Lo, Sichen Song, Jason Cong, Lixia Zhang, Sankalpa Timilsina, Susmit Shannigrahi, Chengyu Fan, Davide Pesavento, Junxiao Shi, L. Benmohamed\",\"doi\":\"10.1145/3517212.3558087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To meet unprecedented challenges faced by the world's largest data- and network-intensive science programs, we design and implement a new, highly efficient and field-tested data distribution, caching, access and analysis system for the Large Hadron Collider (LHC) high energy physics (HEP) network and other major science programs. We develop a hierarchical Named Data Networking (NDN) naming scheme for HEP data, implement new consumer and producer applications to interface with the high-performance NDN-DPDK forwarder, and build on recently developed high-throughput NDN caching and forwarding methods. We integrate NDN systems concepts and algorithms with the mainstream data distribution, processing, and management system of the Compact Muon Solenoid (CMS) experiment. We design and prototype stable, high-performance virtual LANs (VLANs) over a continental-scale wide area network testbed. In extensive experiments, our proposed integrated system, named NDN for Data-Intensive Science Experiments (N-DISE), is shown to deliver LHC data over the wide area network (WAN) testbed at throughputs exceeding 31 Gbps between Caltech and StarLight, with dramatically reduced download time.\",\"PeriodicalId\":165903,\"journal\":{\"name\":\"Proceedings of the 9th ACM Conference on Information-Centric Networking\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 9th ACM Conference on Information-Centric Networking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3517212.3558087\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 9th ACM Conference on Information-Centric Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3517212.3558087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
N-DISE: NDN-based data distribution for large-scale data-intensive science
To meet unprecedented challenges faced by the world's largest data- and network-intensive science programs, we design and implement a new, highly efficient and field-tested data distribution, caching, access and analysis system for the Large Hadron Collider (LHC) high energy physics (HEP) network and other major science programs. We develop a hierarchical Named Data Networking (NDN) naming scheme for HEP data, implement new consumer and producer applications to interface with the high-performance NDN-DPDK forwarder, and build on recently developed high-throughput NDN caching and forwarding methods. We integrate NDN systems concepts and algorithms with the mainstream data distribution, processing, and management system of the Compact Muon Solenoid (CMS) experiment. We design and prototype stable, high-performance virtual LANs (VLANs) over a continental-scale wide area network testbed. In extensive experiments, our proposed integrated system, named NDN for Data-Intensive Science Experiments (N-DISE), is shown to deliver LHC data over the wide area network (WAN) testbed at throughputs exceeding 31 Gbps between Caltech and StarLight, with dramatically reduced download time.