Instantiating a Global Network Measurement Framework

Tierney, Brian; Boote, Jeff; Boyd, Eric L.; Brown, Alexander L.; Grigoriev, Maxim; Metzger, Joe; Swany, Martin; Zekauskas, Matt; Zurawski, Jason

doi:10.2172/946807

Cited by 27 publications

(22 citation statements)

References 15 publications

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“…Finally, we discuss network management protocols and frameworks to investigate appropriate implementation mechanisms to deploy the description of the network environment on the testbed. [7,11] and PerfSONAR [29] are not capable of continuously monitoring the network and detect changes. OpenVAS [23] is used to identify vulnerabilities within an infrastructure but has limited scanning capabilities.…”

Section: Related Workmentioning

confidence: 99%

Achieving Reproducible Network Environments with INSALATA

Herold

Wachs

Dorfhuber

et al. 2017

Lecture Notes in Computer Science

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Abstract. Analyzing network environments for security flaws and assessing new service and infrastructure configurations in general are dangerous and error-prone when done in operational networks. Therefore, cloning such networks into a dedicated test environment is beneficial for comprehensive testing and analysis without impacting the operational network. To automate this reproduction of a network environment in a physical or virtualized testbed, several key features are required: (a) a suitable network model to describe network environments, (b) an automated acquisition process to instantiate this model for the respective network environment, and (c) an automated setup process to deploy the instance to the testbed.With this work, we present INSALATA, an automated and extensible framework to reproduce physical or virtualized network environments in network testbeds. INSALATA employs a modular approach for data acquisition and deployment, resolves interdependencies in the setup process, and supports just-in-time reproduction of network environments. INSALATA is open source and available on Github. To highlight its applicability, we present a real world case study utilizing INSALATA.

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Section: Related Workmentioning

confidence: 99%

Achieving Reproducible Network Environments with INSALATA

Herold

Wachs

Dorfhuber

et al. 2017

Lecture Notes in Computer Science

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“…At even larger scales, large clusters of DTNs provide data service to the Large Hadron Collider (LHC) 15 collaborations. The Tier-1 16 centers deploy large numbers of DTNs to support thousands of scientists. These are systems dedicated to the task of data transfers so that they provide reliable, high-performance service to science applications.…”

Section: Dedicated Systems: the Data Transfer Node (Dtn)mentioning

confidence: 99%

“…A perfSONAR host [16] helps with fault diagnosis on the Science DMZ. It offers end-to-end testing with collaborating sites that have perfSONAR tools installed, which allows for multi-domain troubleshooting.…”

Section: Performance Monitoringmentioning

confidence: 99%

The Science DMZ: A Network Design Pattern for Data-Intensive Science

Dart

Rotman

Tierney

et al. 2014

Scientific Programming

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Abstract. The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of highcapacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The Science DMZ paradigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.

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“…perfSONAR [13,15,4] offers a web-services based infrastructure for collecting and publishing network performance monitoring. It consists of a protocol, architecture and set of tools developed specifically to work in a multi-domain environment with the goal of solving endto-end performance problems on network paths crossing multiple domains.…”

Section: Related Workmentioning

confidence: 99%

Enabling persistent queries for cross-aggregate performance monitoring

et al. 2014

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It is essential for distributed data-intensive applications to monitor the performance of the underlying network, storage and computational resources. Increasingly, distributed applications need performance information from multiple aggregates, and tools need to take real-time steering decisions based on the performance feedback. With increasing scale and complexity, the volume and velocity of monitoring data is increasing, posing scalability challenges. In this work, we have developed a Persistent Query Agent (PQA) that provides realtime application and network performance feedback to clients/applications, thereby enabling dynamic adaptations. PQA enables federated performance monitoring by interacting with multiple aggregates and performance monitoring sources. Using a publish-subscribe framework, it sends triggers asynchronously to applications/clients when relevant performance events occur. The applications/clients register their events of interest using declarative queries and get notified by the PQA. PQA leverages a complex event processing (CEP) framework for managing and executing the queries expressed in a standard SQL-like query language. Instead of saving all monitoring data for future analysis, PQA observes performance event streams in real-time, and runs continuous queries over streams of monitoring events. In this work, we present the design and architecture of the persistent query agent, and describe some relevant use cases.

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Instantiating a Global Network Measurement Framework

Cited by 27 publications

References 15 publications

Achieving Reproducible Network Environments with INSALATA

Achieving Reproducible Network Environments with INSALATA

The Science DMZ: A Network Design Pattern for Data-Intensive Science

Enabling persistent queries for cross-aggregate performance monitoring

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