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DTSTART;TZID=America/Chicago:20181111T090000
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UID:submissions.supercomputing.org_SC18_sess159@linklings.com
SUMMARY:Innovating the Network for Data Intensive Science (INDIS)
DESCRIPTION:Introduction - Innovating the Network for Data Intensive Scien
 ce (INDIS)\n\nWide area networks are now an integral and essential part of
  this data-driven supercomputing ecosystem connecting information sources,
  data stores, processing, simulation, visualization and user communities t
 ogether.  Networks for data-intensive science have more extreme requiremen
 ts than general-pu...\n\n\nPaola Grosso (University of Amsterdam), Mary He
 ster (SURFnet), Ilya Baldin (Renaissance Computing Institute (RenCI)), and
  Michelle Zhu (Montclair State University)\n---------------------\nBandwid
 th Scheduling for Big Data Transfer with Deadline Constraint between Data 
 Centers\n\nAn increasing number of applications in scientific and other do
 mains have moved or are in active transition to clouds, and the demand for
  the movement of big data between geographically distributed cloud-based d
 ata centers is rapidly growing. Many modern backbone networks leverage log
 ically centrali...\n\n\nAiqin Hou (Northwest University, China); Chase Q. 
 Wu (New Jersey Institute of Technology); Dingyi Fang (Northwest University
 , China); Liudong Zuo (California State University, Dominguez Hills); Mich
 elle M. Zhu (Montclair State University); and Xiaoyang Zhang, Ruimin Qiao,
  and Xiaoyan Yin (Northwest University, China)\n---------------------\nFlo
 wzilla: A Methodology for Detecting Data Transfer Anomalies in Research Ne
 tworks\n\nResearch networks are designed to support high volume scientific
  data transfers that span multiple network links. Like any other network, 
 research networks experience anomalies. Anomalies are deviations from prof
 iles of normality in a science network’s traffic levels. Diagnosing anomal
 ies is critica...\n\n\nAnna Giannakou, Dan Gunter, and Sean Peisert (Lawre
 nce Berkeley National Laboratory)\n---------------------\nAnalysis of CPU 
 Pinning and Storage Configuration in 100 Gbps Network Data Transfer\n\nA c
 ommon bottleneck for high-speed network data transfers is lack of CPU reso
 urces. A number of techniques and solutions have been proposed to reduce C
 PU load for data transfer. One can optimize the core affinity settings in 
 their Non-Uniform Memory Access (NUMA) system and use NVMe over Fabrics to
  ...\n\n\nSe-young Yu, Jim Chen, Joe Mambretti, and Fei Yeh (International
  Center for Advanced Internet Research (iCAIR), Northwestern University)\n
 ---------------------\nINDIS Showcases Panel: NRE and XNET and Architectur
 e\n---------------------\nINDIS Afternoon Keynote\n\nKate Keahey will give
  the second keynote on "Chameleon: New Capabilities for Experimental Compu
 ter Science". Chameleon is a large-scale, deeply reconfigurable testbed bu
 ilt specifically to explore a broad range of different state-of-the-art ha
 rdware options, assess scalability of systems, and provid...\n\n\nKate Kea
 hey (Argonne National Laboratory)\n---------------------\nSocial Computati
 onal Trust Model (SCTM): A Framework to Facilitate Selection of Partners\n
 \nCreating a cyber security alliance among network domain owners, as a mea
 ns to minimize security incidents, has gained the interest of practitioner
 s and academics in the last few years. A cyber security alliance, like any
  membership organization, requires the creation and maintenance of trust a
 mong i...\n\n\nAmeneh Deljoo and Tom van Engers (University of Amsterdam),
  Leon Gommans (Air France-KLM), and Cees de Laat (University of Amsterdam)
 \n---------------------\nINDIS Morning Keynote\n\nJosh Bailey will give a 
 keynote on FAUCET. FAUCET is an open source, production SDN controller, su
 pporting multiple network vendors, and is deployed as part of SC18's SCine
 t network among other networks. This talk will be an update on FAUCET's cu
 rrent status and features and an informal Q&A on the s...\n\n\nJosh Bailey
  (Google LLC)\n---------------------\nWorkshop Morning Break\n------------
 ---------\nFast Detection of Elephant Flows with Dirichlet-Categorical Inf
 erence\n\nThe problem of elephant flow detection is a longstanding researc
 h area with the goal of quickly identifying flows in a network that are la
 rge enough to affect the quality of service of smaller flows. Past work in
  this field has largely been either domain-specific, based on thresholds f
 or a specific ...\n\n\nAditya Gudibanda, Jordi Ros-Giralt, Alan Commike, a
 nd Richard Lethin (Reservoir Labs Inc)\n---------------------\nWorkshop Af
 ternoon Break\n---------------------\nBigData Express: Toward Schedulable,
  Predictable, and High-Performance Data Transfer\n\nBig Data has emerged a
 s a driving force for scientific discoveries. Large scientific instruments
  (e.g., colliders, and telescopes) generate exponentially increasing volum
 es of data. To enable scientific discovery, science data must be collected
 , indexed, archived, shared, and analyzed, typically in ...\n\n\nQiming Lu
 , Liang Zhang, Sajith Sasidharan, Wenji Wu, and Phil Demar (Fermi National
  Accelerator Laboratory); Chin Guok, John Macauley, and Inder Monga (Energ
 y Sciences Network (ESnet)); Se-young Yu, Jim-hao Chen, and Joe Mambretti 
 (Northwestern University); Jim Kim and Seo-young Noh (Korea Advanced Insti
 tute of Science and Technology); Xi Yang and Tom Lehman (University of Mar
 yland); and Gary Liu (New Jersey Institute of Technology)\n---------------
 ------\nTracking Network Flows with P4\n\nTracking flows within a single d
 evice, as well as tracking the full path a flow takes in a network, are co
 re components in securing networks. Malicious traffic can be easily identi
 fied and its source blocked. Traditional methods have performance and prec
 ision shortcomings, while new programmable dev...\n\n\nJoseph Hill, Mitche
 ll Aloserij, and Paola Grosso (University of Amsterdam)\n-----------------
 ----\nWorkshop Lunch (on your own)\n---------------------\nINDIS Invited T
 alk: Introduction to SCinet\n\nJason Zurawski (Energy Sciences Network (ES
 net))\n---------------------\nSDN for End-to-End Networked Science at the 
 Exascale (SENSE)\n\nThe Software-defined network for End-to-end Networked 
 Science at Exascale (SENSE) research project is building smart network ser
 vices to accelerate scientific discovery in the era of ‘big data’ driven b
 y Exascale, cloud computing, machine learning and AI. The project’s archit
 ecture, models, and demo...\n\n\nInder Monga, Chin Guok, John MacAuley, an
 d Alex Sim (Lawrence Berkeley National Laboratory, Energy Sciences Network
  (ESnet)); Harvey Newman and Justas Balcas (California Institute of Techno
 logy; Division of Physics, Mathematics and Astronomy); Phil DeMar (Fermi N
 ational Accelerator Laboratory, Computing Division); Linda Winkler (Argonn
 e National Laboratory; Computing, Environment and Life Science Division); 
 and Tom Lehman and Xi Yang (University of Maryland, Mid-Atlantic Crossroad
 s)\n\nTag: Architectures, Networks, Security\n\nRegistration Category: Wor
 kshop Reg Pass\n\nSession Chairs: Ilya Baldin (Thomas Jefferson National A
 ccelerator Facility); Paola Grosso (University of Amsterdam, Netherlands);
  Mary Hester (Dutch National Institute for Subatomic Physics); and Michell
 e Zhu (Montclair State University)
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