Multi-Layer Stream Orchestration with Flange

Musser, Jeremy; Kissel, Ezra; Skipper, Grant; Swany, Martin

doi:10.1109/icfc.2019.00023

Cited by 2 publications

(3 citation statements)

References 11 publications

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“…In addition to previous work performed in this project for in-network function placement (Brasilino et al, 2018, 2020; Ossen et al, 2022) and network orchestration (Musser et al, 2019; 2020), we took inspiration from several similar approaches described herein.…”

Section: Related Workmentioning

confidence: 99%

“…The INDIANA framework requires two core components, (1) a stream operator deployment architecture built using RISC-V soft cores, and (2) a flow-oriented network operating system built around a declarative language for expressing network behavior through broad policies. In the implementation provided herein, we leverage components from our prior work, NetFaaS (Ossen et al, 2022) and Flange (Musser et al, 2019), expanding on each and integrating them into a single unified whole. NetFaaS provides the NIC-CPU infrastructure to deploy network functions.…”

Section: Introductionmentioning

confidence: 99%

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INDIANA—In-Network Distributed Infrastructure for Advanced Network Applications

Ossen

Musser

Dalessandro

et al. 2023

The International Journal of High Performance Computing Applica

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Data volumes are exploding as sensors proliferate and become more capable. Edge computing is envisioned as a path to distribute processing and reduce latency. Many models of Edge computing consider small devices running conventional software. Our model includes a more lightweight execution engine for network microservices and a network scheduling framework to configure network processing elements to process streams and direct the appropriate traffic to them. In this article, we describe INDIANA, a complete framework for in-network microservices. We will describe how the two components-the INDIANA network Processing Element (InPE) and the Flange Network Operating System (NOS)-work together to achieve effective in-network processing to improve performance in edge to cloud environments. Our processing elements provide lightweight compute units optimized for efficient stream processing. These elements are customizable and vary in sophistication and resource consumption. The Flange NOS provides first-class flow based reasoning to drive function placement, network configuration, and load balancing that can respond dynamically to network conditions. We describe design considerations and discuss our approach and implementations. We evaluate the performance of stream processing and examine the performance of several exemplar applications on networks of increasing scale and complexity.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

INDIANA—In-Network Distributed Infrastructure for Advanced Network Applications

Ossen

Musser

Dalessandro

et al. 2023

The International Journal of High Performance Computing Applica

Self Cite

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“…With this model, our distributed system can optimize the network for performance and resiliency through SDN (Software Defined Networking). As shown in Figure 1, some key components include the Unified Network Information Service (UNIS) [6] that combines the capabilities of resource lookup and network topology services within a general data model and reference implementation, the Flange network orchestrator and domain specific language (DSL) [7] that drives network configuration and management, and a topology discovery and SDN component. The controller is informed by information collected in UNIS and managed by Flange, which allows for dynamically modified network behavior.…”

Section: Nmalmentioning

confidence: 99%

Applying OSiRIS NMAL to Network Slices on SLATE

et al. 2020

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The Network Management Abstraction Layer (NMAL) extends perfSONAR capabilities to include automated network topology discovery and tracking in the Unified Network Information Service (UNIS), and incorporate Software Defined Networking (SDN) into overall operations of the OSiRIS distributed Ceph infrastructure. We deploy perfSONAR components both within OSiRIS and at our “client” locations to allow monitoring and measuring the networks interconnecting science domain users and OSiRIS components. Topology discovery (using an SDN controller application) and Flange Network Orchestration (NOS) rules are used to dynamically manage network pathing in our testbed environments. NMAL components have been containerized to operate within the Services Layer at the Edge (SLATE) infrastructure, and we describe our experiences in packaging and deploying our services.

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Multi-Layer Stream Orchestration with Flange

Cited by 2 publications

References 11 publications

INDIANA—In-Network Distributed Infrastructure for Advanced Network Applications

INDIANA—In-Network Distributed Infrastructure for Advanced Network Applications

Applying OSiRIS NMAL to Network Slices on SLATE

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