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1. Novel Network Services for Supporting Big Data Science Research

   Chung, J.; Donovan, S.; Bezerra, J.; Morgan, H.; Ibarra, J.; Clark, R.; Owen, H (October 2017, Gateways 2017)

   To interconnect research facilities across wide geographic areas, network operators deploy science networks, also referred to as Research and Education (R&E) networks. These networks allow experimenters to establish dedicated network connections between research facilities for transferring large amounts of data. Recently, R&E networks have started using Software-Defined Networking (SDN) and Software Defined Exchanges (SDX) for deploying these connections. AtlanticWave/SDX is a response to the growing demand to support end-to-end network services spanning multiple SDN domains. However, requesting these services is a challenging task for domain-expert scientists, because the interfaces of the R&E networks have been developed by network operators for network operators. In this paper, we propose interfaces that allow domain expert scientists to reserve resources of the scientific network using abstractions that focus on their data transfer needs for scientific workflow management. Recent trends in the networking field pursue better interfaces for requesting network services (e.g., intent-based networking). Although intents are sufficient for the needs of network operations, they are not abstract enough in most cases to be used by domain-expert scientists. This is an issue we are addressing in the AtlanticWave/SDX design: network operators and domain-expert scientists will have their own interfaces focusing on their specific needs. 

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2. Novel Network Services for Supporting Big Data Science Research

   Chung, J.; Donovan, S.; Bezerra, J.; Morgan, H.; Ibarra, J.; Clark, R.; Owen, H (October 2017, Gateways 2017)

   Poster Abstract: To interconnect research facilities across wide geographic areas, network operators deploy science networks, also referred to as Research and Education (R&E) networks. These networks allow experimenters to establish dedicated network connections between research facilities for transferring large amounts of data. Recently, R&E networks have started using Software-Defined Networking (SDN) and Software Defined Exchanges (SDX) for deploying these connections. AtlanticWave/SDX is a response to the growing demand to support end-to-end network services spanning multiple SDN domains. However, requesting these services is a challenging task for domain-expert scientists, because the interfaces of the R&E networks have been developed by network operators for network operators. In this paper, we propose interfaces that allow domain expert scientists to reserve resources of the scientific network using abstractions that focus on their data transfer needs for scientific workflow management. Recent trends in the networking field pursue better interfaces for requesting network services (e.g., intent-based networking). Although intents are sufficient for the needs of network operations, they are not abstract enough in most cases to be used by domain-expert scientists. This is an issue we are addressing in the AtlanticWave/SDX design: network operators and domain expert scientists will have their own interfaces focusing on their specific needs. 

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3. Responding to the demands of big data scientific instruments through the development of an international software defined exchange point (SDX)

   Ibarra, J.; Bezerra, J.; Lopez, L.F.; Morgan, L; Cox, D. (April 2016, UbuntuNet Connect-Connect 2016)

   Science is being conducted in an era of information abundance. The rate at which science data is generated is increasing, both in volume and variety. This phenomenon is transforming how science is thought of and practiced. This transformation is being shaped by new scientific instruments that are being designed and deployed that will dramatically increase the need for large, real-time data transfers among scientists throughout the world. One such instrument is the Square Kilometer Array (SKA) being built in South Africa that will transmit approximately 160Gbps of data from each radio dish to a central processor. This paper describes a collaborative effort to respond to the demands of big data scientific instruments through the development of an international software defined exchange point (SDX) that will meet the network provisioning needs for science applications. This paper discusses the challenges of end-to-end path provisioning across multiple research and education networks using OpenFlow/SDN technologies. Furthermore, it refers to the AtlanticWave-SDX, a project at Florida International University and the Georgia Institute of Technology, funded by the US National Science Foundation (NSF), along with support from Brazil’s NREN, Rede Nacional de Ensino e Pesquisa (RNP, and the Academic Network of Sao Paulo (ANSP). Future work explores the feasibility of establishing an SDX in West Africa, in collaboration with regional African RENs, based on the planned availability of submarine cable spectrum for use by research and education communities. 

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4. Designing workflows for materials characterization

   https://doi.org/10.1063/5.0169961  

   Kalinin, Sergei V.; Ziatdinov, Maxim; Ahmadi, Mahshid; Ghosh, Ayana; Roccapriore, Kevin; Liu, Yongtao; Vasudevan, Rama K. (March 2024, Applied Physics Reviews)

   Experimental science is enabled by the combination of synthesis, imaging, and functional characterization organized into evolving discovery loop. Synthesis of new material is typically followed by a set of characterization steps aiming to provide feedback for optimization or discover fundamental mechanisms. However, the sequence of synthesis and characterization methods and their interpretation, or research workflow, has traditionally been driven by human intuition and is highly domain specific. Here, we explore concepts of scientific workflows that emerge at the interface between theory, characterization, and imaging. We discuss the criteria by which these workflows can be constructed for special cases of multiresolution structural imaging and functional characterization, as a part of more general material synthesis workflows. Some considerations for theory–experiment workflows are provided. We further pose that the emergence of user facilities and cloud labs disrupts the classical progression from ideation, orchestration, and execution stages of workflow development. To accelerate this transition, we propose the framework for workflow design, including universal hyperlanguages describing laboratory operation, ontological domain matching, reward functions and their integration between domains, and policy development for workflow optimization. These tools will enable knowledge-based workflow optimization; enable lateral instrumental networks, sequential and parallel orchestration of characterization between dissimilar facilities; and empower distributed research. 

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5. Automated Network Services for Exascale Data Movement

   https://doi.org/10.1051/epjconf/202429501009  

   Balcas, Justas; Newman, Harvey; Bhat, Preeti P; Würthwein, Frank; Guiang, Jonathan; Arora, Aashay; Davila, Diego; Graham, John; Hutton, Thomas; Lehman, Tom; et al (January 2024, EPJ Web of Conferences)

   De_Vita, R; Espinal, X; Laycock, P; Shadura, O (Ed.)

   The Large Hadron Collider (LHC) experiments distribute data by leveraging a diverse array of National Research and Education Networks (NRENs), where experiment data management systems treat networks as a “blackbox” resource. After the High Luminosity upgrade, the Compact Muon Solenoid (CMS) experiment alone will produce roughly 0.5 exabytes of data per year. NREN Networks are a critical part of the success of CMS and other LHC experiments. However, during data movement, NRENs are unaware of data priorities, importance, or need for quality of service, and this poses a challenge for operators to coordinate the movement of data and have predictable data flows across multi-domain networks. The overarching goal of SENSE (The Software-defined network for End-to-end Networked Science at Exascale) is to enable National Labs and universities to request and provision end-to-end intelligent network services for their application workflows leveraging SDN (Software-Defined Networking) capabilities. This work aims to allow LHC Experiments and Rucio, the data management software used by CMS Experiment, to allocate and prioritize certain data transfers over the wide area network. In this paper, we will present the current progress of the integration of SENSE, Multi-domain end-to-end SDN Orchestration with QoS (Quality of Service) capabilities, with Rucio, the data management software used by CMS Experiment. 

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