SFS: Smart OS Scheduling for Serverless Functions
Yuqi Fu, Li Liu, Haoliang Wang, Yue Cheng, Songqing Chen

TL;DR
This paper introduces SFS, a user-space scheduler for serverless functions that improves short function performance by approximating SRTF, addressing unpredictable execution times caused by default Linux scheduling policies.
Contribution
SFS is a novel user-space scheduling approach that combines FIFO and CFS to optimize serverless function performance, especially for short tasks.
Findings
SFS significantly reduces short function execution times.
SFS causes minimal impact on longer functions.
Implementation in Linux user space demonstrates practical benefits.
Abstract
Serverless computing enables a new way of building and scaling cloud applications by allowing developers to write fine-grained serverless or cloud functions. The execution duration of a cloud function is typically short-ranging from a few milliseconds to hundreds of seconds. However, due to resource contentions caused by public clouds' deep consolidation, the function execution duration may get significantly prolonged and fail to accurately account for the function's true resource usage. We observe that the function duration can be highly unpredictable with huge amplification of more than 50x for an open-source FaaS platform (OpenLambda). Our experiments show that the OS scheduling policy of cloud functions' host server can have a crucial impact on performance. The default Linux scheduler, CFS (Completely Fair Scheduler), being oblivious to workloads, frequently context-switches short…
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Taxonomy
TopicsCloud Computing and Resource Management · IoT and Edge/Fog Computing · Distributed and Parallel Computing Systems
