[ { "id": "authors:qsngw-k3537", "collection": "authors", "collection_id": "qsngw-k3537", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20190109-091547583", "type": "book_section", "title": "Compositional structures for streaming applications", "book_title": "Proceedings of the 20th International Conference on Distributed Computing and Networking (ICDCN '19)", "author": [ { "family_name": "Chandy", "given_name": "K. Mani", "clpid": "Chandy-K-M" }, { "family_name": "Bunn", "given_name": "Julian", "orcid": "0000-0002-3798-298X", "clpid": "Bunn-J" } ], "abstract": "This paper describes an ongoing project to develop a Python software package, IoTPy, that helps beginning programmers build modular applications that process streams of data collected from sensors, social media and other sources, and to reason about the correctness of their applications in a compositional fashion. IoTPy helps build streaming applications in four ways: (1) enables the construction of non-terminating applications that continuously process endless streams of data by encapsulating terminating programs; (2) supports computation throughout a network of nodes from sensors at the edges of the network to the cloud and back to actuators at the edge; (3) allows users to separate concerns of the logic of an application from the parallel hardware on which the application runs, and (4) supports proofs and testing of the correct behavior of a composition from the specifications of its components.", "doi": "10.1145/3288599.3288642", "isbn": "978-1-4503-6094-4", "publisher": "Association for Computing Machinery (ACM)", "place_of_publication": "New York, NY", "publication_date": "2019-01", "pages": "352-361" }, { "id": "authors:3ss1s-xjh02", "collection": "authors", "collection_id": "3ss1s-xjh02", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20161208-082631422", "type": "book_section", "title": "Networking for high energy physics", "book_title": "Grid and cloud computing: concepts and practical applications", "author": [ { "family_name": "Newman", "given_name": "H. B.", "orcid": "0000-0003-0964-1480", "clpid": "Newman-H-B" }, { "family_name": "Mughal", "given_name": "A.", "clpid": "Mughal-A" }, { "family_name": "Kassymkhanova", "given_name": "I.", "clpid": "Kassymkhanova-I" }, { "family_name": "Bunn", "given_name": "J.", "orcid": "0000-0002-3798-298X", "clpid": "Bunn-J" }, { "family_name": "Voicu", "given_name": "R.", "clpid": "Voicu-R" }, { "family_name": "L\u00e1p\u00e1d\u00e1tescu", "given_name": "V.", "clpid": "L\u00e1p\u00e1d\u00e1tescu-V" }, { "family_name": "Kcira", "given_name": "D.", "orcid": "0000-0002-8190-2414", "clpid": "Kcira-D" } ], "contributor": [ { "family_name": "Carminati", "given_name": "F.", "clpid": "Carminati-F" }, { "family_name": "Betev", "given_name": "L.", "clpid": "Betev-L" }, { "family_name": "Grigoras", "given_name": "A.", "clpid": "Grigoras-A" } ], "abstract": "This report, and the accompanying reports of the Standing Committee on Inter-regional Connectivity (SCIC), a technical panel of the International Committee on Future Accelerators (ICFA), serve as comprehensive lecture notes, updated to February 2015, for the lectures on Global Networking delivered at the Varenna Summer School in July 2014. The full set of reports including the accompanying Annexes, Monitoring Working Group report and presentation slide deck may be found at http://cern.ch.icfa-scic.", "doi": "10.3254/978-1-61499-643-9-205", "isbn": "978-88-7438-100-5", "publisher": "IOS Press", "place_of_publication": "Amsterdam", "publication_date": "2016", "pages": "205-260" }, { "id": "authors:xhx1b-wp555", "collection": "authors", "collection_id": "xhx1b-wp555", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20151123-151838304", "type": "book_section", "title": "High speed scientific data transfers using software defined networking", "book_title": "Proceedings of the Second Workshop on Innovating the Network for Data-Intensive Science", "author": [ { "family_name": "Newman", "given_name": "Harvey", "orcid": "0000-0003-0964-1480", "clpid": "Newman-H-B" }, { "family_name": "Mughal", "given_name": "Azher", "clpid": "Mughal-A" }, { "family_name": "Kcira", "given_name": "Dorian", "orcid": "0000-0002-8190-2414", "clpid": "Kcira-D" }, { "family_name": "Legrand", "given_name": "Iosif", "clpid": "Legrand-I" }, { "family_name": "Voicu", "given_name": "Ramiro", "clpid": "Voicu-R" }, { "family_name": "Bunn", "given_name": "Julian", "orcid": "0000-0002-3798-298X", "clpid": "Bunn-J" } ], "abstract": "The massive data volumes acquired, simulated, processed and analyzed by globally distributed scientific collaborations continue to grow exponentially. One leading example is the LHC program, now at the start of its second three year data taking cycle, searching for new particles and interactions in a previously inaccessible range of energies, which has experienced a 70% growth in peak data transfer rates over the last 12 months alone. Other major science programs such as LSST and SKA, and other disciplines ranging from earth observation to genomics, are expected to have similar or great needs than the LHC program within the next decade. The development of new methods for fast, efficient and reliable data transfers over national and global distances, and a new generation of intelligent, software-driven networks capable of supporting multiple science programs with diverse needs for high volume and/or real-time data delivery, are essential if these programs are to continue to progress, and meet their goals. In this paper we describe activities of the Caltech High Energy Physics team and collaborators, related to the use Software Defined Networking to help achieve fast and efficient data distribution and access. Results from Supercomputing 2014 are presented together with our work on the Advanced Network Services for the Experiments project, and a new project developing a Next Generation Integrated SDN Architecture, as well as our plans for Supercomputing 2015.", "doi": "10.1145/2830318.2830320", "isbn": "978-1-4503-4002-1", "publisher": "Association for Computing Machinery", "place_of_publication": "New York, NY", "publication_date": "2015-11", "pages": "Art. No. 2" }, { "id": "authors:6ffg6-fxq56", "collection": "authors", "collection_id": "6ffg6-fxq56", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20120816-143912724", "type": "book_section", "title": "Towards a Discipline of Geospatial Distributed Event Based Systems", "book_title": "Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems", "author": [ { "family_name": "Liu", "given_name": "Annie", "clpid": "Liu-A" }, { "family_name": "Olson", "given_name": "Michael", "clpid": "Olson-M" }, { "family_name": "Bunn", "given_name": "Julian", "orcid": "0000-0002-3798-298X", "clpid": "Bunn-J" }, { "family_name": "Chandy", "given_name": "K. Mani", "clpid": "Chandy-K-M" } ], "abstract": "A geospatial system is one in which the state space includes one, two or three-dimensional space and time. A geospatial event is one in which an event impacts points in space over time. Examples of geospatial events include floods, tsunamis, earthquakes, and emission of toxic plumes. This paper discusses aspects of the theory of geospatial distributed event based systems (GDEBS). The paper describes algorithms for rapid detection of geospatial events which can be used on Cloud computing architectures, in which many servers collaborate to detect events by analyzing data streams from large numbers of sensors. Sensor noise and timing errors may result in false detection or missed detection as well as incorrect identification of event attributes such as the location of the event source. The paper presents mathematical analyses and simulations dealing with rapid event detection for geospatial events of varying speeds in the presence of substantial sensor noise and timing error. The paper also describes some of the algorithmic and machine-learning techniques for improving event detection in the Cloud with large numbers of noisy sensors. Experience with GDEBS using a seismic network is described.", "doi": "10.1145/2335484.2335495", "isbn": "978-1-4503-1315-5", "publisher": "ACM", "place_of_publication": "New York", "publication_date": "2012", "pages": "95-106" }, { "id": "authors:9b6za-ap442", "collection": "authors", "collection_id": "9b6za-ap442", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170208-175923694", "type": "book_section", "title": "Sensor networks for the detection and tracking of radiation and other threats in cities", "book_title": "Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks", "author": [ { "family_name": "Liu", "given_name": "Annie H.", "clpid": "Liu-Annie-H" }, { "family_name": "Bunn", "given_name": "Julian J.", "orcid": "0000-0002-3798-298X", "clpid": "Bunn-J" }, { "family_name": "Chandy", "given_name": "K. Mani", "clpid": "Chandy-K-M" } ], "abstract": "This paper presents results from experiments, mathematical analysis, and simulations of a network of static and mobile sensors for detecting threats on city streets and in open areas such as parks. The paper focuses on the detection of nuclear radiation threats and shows how the analysis can be extended to other classes of threat. The paper evaluates algorithms that integrate methods of parametric and Bayesian statistics. A pure Bayesian approach is difficult because obtaining prior distributions on the large number of parameters is challenging. The results of analyses and simulations are compared against measurements made on a reduced scale testbed. A survey of background radiation in the city of Sacramento is used to quantify the efficacy of police patrols to detect threats. The paper also presents algorithms that optimize network parameters such as sensor placement.", "isbn": "978-1-61284-854-9", "publisher": "ACM", "place_of_publication": "New York, NY", "publication_date": "2011-04" }, { "id": "authors:4v3dp-ydw97", "collection": "authors", "collection_id": "4v3dp-ydw97", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20181212-101334585", "type": "book_section", "title": "High speed data gathering, distribution and analysis for physics discoveries at the large Hadron collider", "book_title": "Proceedings of the 2006 ACM/IEEE conference on Supercomputing (SC '06)", "author": [ { "family_name": "Bunn", "given_name": "Julian J.", "orcid": "0000-0002-3798-298X", "clpid": "Bunn-J" }, { "family_name": "Newman", "given_name": "Harvey", "orcid": "0000-0003-0964-1480", "clpid": "Newman-H-B" }, { "family_name": "McKee", "given_name": "Shawn", "clpid": "McKee-Shawn" }, { "family_name": "Foster", "given_name": "David G.", "clpid": "Foster-D-G" }, { "family_name": "Cavanaugh", "given_name": "Richard", "clpid": "Cavanaugh-R" }, { "family_name": "Hughes-Jones", "given_name": "Richard", "clpid": "Hughes-Jones-R" } ], "abstract": "The latest WAN infrastructure and Grid-based Web Services will be used to demonstrate movement and analysis of TeraByte-scale event datasets for particle physics. Optimized transfers of data over 10Gbit/sec networks linking servers and disk systems will be shown using the latest processors, PCI-Express NICs, RAID arrays and firmware. All available lambdas arriving at the SC06 show floor will be saturated, in full duplex mode. The WAN performance will be monitored using the MonALISA distributed agent-based system. A suite of Grid-enabled Analysis tools developed at Caltech, University of Florida and Michigan will be used, as will. EGEE, OSG, ATLAS and CMS data management software such as SRM, dCache, FTS, and PhEdEx. Prototypes of the latest version of parallel NFS will demonstrate excellent utilization of 10Gbit/sec connections during execution of the analysis tasks.We intend to exceed the aggregate rate of 150Gbits/sec we achieved in our SC2005 Bandwidth Challenge winning entry.", "doi": "10.1145/1188455.1188708", "isbn": "0-7695-2700-0", "publisher": "Association for Computing Machinery", "place_of_publication": "New York, NY", "publication_date": "2007-01-17", "pages": "Art. No. 241" } ]