Fine-Grained Isolation for Scalable, Dynamic, Multi-tenant Edge Clouds


Yuxin Ren, The George Washington University; Guyue Liu, Carnegie Mellon University; Vlad Nitu, INSA Lyon France; Wenyuan Shao, Riley Kennedy, Gabriel Parmer, and Timothy Wood, The George Washington University; Alain Tchana, ENS Lyon France


5G edge clouds promise a pervasive computational infrastructure a short network hop away, enabling a new breed of smart devices that respond in real-time to their physical surroundings. Unfortunately, today’s operating system designs fail to meet the goals of scalable isolation, dense multi-tenancy, and high performance needed for such applications. In this paper we introduce EdgeOS that emphasizes system-wide isolation as fine-grained as per-client. We propose a novel memory movement accelerator architecture that employs data copying to enforce strong isolation without performance penalties. To support scalable isolation, we introduce a new protection domain implementation that offers lightweight isolation, fast startup and low latency even under high churn. We implement EdgeOS in a microkernel based OS and demonstrate running high scale network middleboxes using the Click software router and endpoint applications such as memcached, a TLS proxy, and neural network inference. We reduce startup latency by 170X compared to Linux processes, and improve latency by three orders of magnitude when running 300 to 1000 edge-cloud memcached instances on one server.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

@inproceedings {254426,
author = {Yuxin Ren and Guyue Liu and Vlad Nitu and Wenyuan Shao and Riley Kennedy and Gabriel Parmer and Timothy Wood and Alain Tchana},
title = {{Fine-Grained} Isolation for Scalable, Dynamic, Multi-tenant Edge Clouds},
booktitle = {2020 USENIX Annual Technical Conference (USENIX ATC 20)},
year = {2020},
isbn = {978-1-939133-14-4},
pages = {927--942},
url = {},
publisher = {USENIX Association},
month = jul

Presentation Video