Applying OSiRIS NMAL to Network Slices on SLATE

Musser, Jeremy; Kissel, Ezra; Swany, Martin; Breen, Joe; Stidd, Jason; Kee, S. P. Mc; Meekhof, Benjeman

doi:10.1051/epjconf/202024507055

Cited by 1 publication

(1 citation statement)

References 15 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%

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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