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SUMMARY:INDIS'21: 8th Workshop on Innovating the Network for Data-Intensiv
 e Science
DESCRIPTION:Workshop\n\nMany fields of science continue to experience a la
 rge influx of data. Managing and transporting data, architecting systems a
 nd building tools to deal with the delivery of these data have become incr
 easingly important. Additionally, the ecosystem of information and communi
 cations frameworks supporting data management and transport is becoming mo
 re and more complex.\n\nNetworks for data-intensive science have more extr
 eme requirements than general-purpose networks. These requirements not onl
 y closely impact the design of processor interconnects in supercomputers a
 nd cluster computers, they also impact campus networks, regional networks 
 and national backbone networks.\n\nThis workshop brings together network e
 ngineers and researchers to share challenges and potential solutions. We i
 nvite papers that propose new and novel techniques that increase the capac
 ity and functionality of scientific computing and wide-area networks.\n\nS
 Cinet:  Future Research Perspectives\n\nKissel\n\n---------------------\nN
 etGraf: An End-to-End Learning Network Monitoring Service\n\nMohammed, Kir
 an, Enders\n\nNetwork monitoring services are of enormous importance to en
 sure optimal performance is being delivered and help determine any failing
  services. Particularly for large data transfers, checking key performance
  indicators like throughput, packet loss, and latency can make or break ex
 periment results. ...\n\n---------------------\nINDIS'21:  Afternoon Break
  (3-3:30)\n\n\n\n---------------------\nLearning Transfers via Transfer Le
 arning\n\nArifuzzaman, Arslan\n\nDetecting performance anomalies is key to
  efficiently utilize network resources and improve the quality of service.
  Researchers proposed various approaches to identify the presence of anoma
 lies by analyzing performance statistics using heuristic (e.g., change poi
 nt detection) and Machine Learning (M...\n\n---------------------\nPoster 
 Talk: Measuring Internet Latency from Gaming Footage\n\nAlvarez\n\nWith th
 e increase of available bandwidth, the performance of most Internet applic
 ations is now mostly dependant on Internet latency. However, characterizin
 g latency is challenging due to the Internet's scale and distributed natur
 e. Most state-of-the-art systems rely on probes, which have many drawba...
 \n\n---------------------\nPanel:  Experimental Networks (XNet) Planning a
 nd SCinet Integration\n\nCalyam, Ruth, Wiedlea, Zink, Fligor\n\n----------
 -----------\nINDIS 2021:  8th Workshop on Innovating the Network for Data-
 Intensive Science\n\nNeuwirth, Kiran\n\nMany fields of science continue to
  experience a large influx of data. Managing and transporting data, archit
 ecting systems and building tools to deal with the delivery of these data 
 have become increasingly important. Additionally, the ecosystem of informa
 tion and communications frameworks supportin...\n\n---------------------\n
 Expert Talk 2:  Mosaic5G – Agile 4G/5G Service Delivery Platforms and Use-
 Cases\n\nNikaein\n\nMosaic5G is an ecosystem of open source 4G/5G service 
 platforms, reusable components and use-cases, whose objective is to transf
 orm 4G/5G radio access network (RAN) and core network (CN) into agile and 
 open network services that can be tailored to divers use-cases. For this p
 urpose, Mosaic5G deliver...\n\n---------------------\nExpert Talk 1: Towar
 d a Quantum Internet\n\nReiserer\n\nA future quantum network will consist 
 of quantum processors that are connected by quantum channels, just like co
 nventional computers are wired up to form the Internet. In contrast to cla
 ssical devices, however, the entanglement and non-local correlations avail
 able in a quantum-controlled system faci...\n\n---------------------\nIntr
 oduction to SCinet\n\nHutchinson\n\n---------------------\nExploring the B
 BRv2 Congestion Control Algorithm for Use on Data Transfer Nodes\n\nTierne
 y, Dart, Kissel, Adhikarla\n\nIt is well known that loss-based TCP congest
 ion control algorithms are problematic for high-speed high-latency flows t
 hat are common in Big Science. In 2016 Google released a new congestion co
 ntrol algorithm called ’BBR’ (Bottleneck Bandwidth and Round-trip time) th
 at uses a model-based approach, an...\n\n---------------------\nBridging N
 etwork and Parallel I/O Research for Improving Data-Intensive Distributed 
 Applications\n\nBiswas, Neuwirth, Paul, Butt\n\nThe rapidly evolving scene
  of emerging workloads poses a challenge to the High Performance Computing
  community in terms of communication and I/O. Significant improvements are
  required to keep up with the demand of high rate of data transfers, strea
 ming services, and scientific research that deal wit...\n\n---------------
 ------\nDeploying Per-Packet Telemetry in a Long-Haul Network: the AmLight
  Use Case\n\nBezerra, Brito, Quintana, Ibarra, Chergarova...\n\nLong-haul 
 networks are growing in complexity to address the constant need for more b
 andwidth, lower latency and jitter, customized traffic prioritization, and
  SLA-grade network resilience. A more complex infrastructure requires a de
 eper visibility of the assets to optimize the resource utilization a...\n\
 n---------------------\nINDIS'21:  Awards Ceremony and Closing Remarks\n\n
 Neuwirth, Kiran\n\n---------------------\nINDIS'21:  Morning Break (10-10:
 30)\n\n\n\n---------------------\nThe Service Analysis and Network Diagnos
 is Data Pipeline\n\nWeitzel, McKee, Bockelman, Thiltges, Babik...\n\nModer
 n network performance monitoring toolkits, such as perfSONAR, take a remar
 kable number of measurements about the local network environment.  To gain
  a complete picture of network performance, however, one needs to aggregat
 e data across a large number of endpoints.  The Service Analysis and Netw.
 ..\n\n---------------------\nLightning Talk: DynamicDeepFlow - Classificat
 ion of Network Traffic Flow Changes Using Unsupervised Learning\n\nShen\n\
 nUnderstanding flows in network traffic has great importance in designing 
 and building robust networking infrastructure. Recent efforts via industry
  and research are developing monitoring tools to capture real-time flow da
 ta, predict future traffic and mirror packet headers. However, all of thes
 e req...\n\n---------------------\nINDIS'21:  Welcome Message\n\nNeuwirth,
  Kiran\n\nMany fields of science continue to experience a large influx of 
 data. Managing and transporting data, architecting systems and building to
 ols to deal with the delivery of these data have become increasingly impor
 tant. Additionally, the ecosystem of information and communications framew
 orks supportin...\n\n---------------------\nINDIS'21:  Lunch Break (12:30-
 2)\n\n\n\n---------------------\nPoster Talk:  Impact of Multi-Connectivit
 y on Channel Capacity and Outage Probability in Wireless Networks\n\nWeeda
 ge\n\nMulti-connectivity facilitates higher throughput, shorter delay, and
  lower outage probability for a user in a wireless network. Considering th
 ese promises, a rationale policy for a network operator would be to implem
 ent multi-connectivity for all of its users. In this research, we investig
 ate whethe...\n\n---------------------\nLightning Talk: Performance Profil
 e Estimation for Emulated Multi-Site Federations\n\nImam\n\nEmulations tha
 t replicate the software environments of multi-site federations of computi
 ng systems and instruments have been developed to reduce the cost and disr
 uptions to physical, production infrastructures. These emulation environme
 nts have been effectively used to develop and test software modu...\n\n\nT
 ag: Big Data, Cloud and Distributed Computing, Data Analytics, Data Manage
 ment, Datacenter, Networks, Performance, Quantum Computing\n\nRegistration
  Category: Workshop Reg Pass
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