FaaS Execution Models for Edge Applications

TL;DR

This paper explores different FaaS execution models for edge applications, focusing on reducing data transfer bottlenecks and improving performance through state management schemes and data locality principles.

Contribution

It introduces and evaluates three FaaS execution schemes for edge networks, extending them to DAG-based applications and validating with a prototype implementation.

Findings

Data locality reduces network traffic significantly.

Local caching improves end-to-end delay performance.

StateProp and StateLocal schemes outperform pure FaaS in edge scenarios.

Abstract

In this paper, we address the problem of supporting stateful workflows following a Function-as-a-Service (FaaS) model in edge networks. In particular we focus on the problem of data transfer, which can be a performance bottleneck due to the limited speed of communication links in some edge scenarios and we propose three different schemes: a pure FaaS implementation, StateProp, i.e., propagation of the application state throughout the entire chain of functions, and StateLocal, i.e., a solution where the state is kept local to the workers that run functions and retrieved only as needed. We then extend the proposed schemes to the more general case of applications modeled as Directed Acyclic Graphs (DAGs), which cover a broad range of practical applications, e.g., in the Internet of Things (IoT) area. Our contribution is validated via a prototype implementation. Experiments in emulated conditions show that applying the data locality principle reduces significantly the volume of network traffic required and improves the end-to-end delay performance, especially with local caching on edge nodes and low link speeds.