Stateful Function-as-a-Service at the Edge

TL;DR

This paper proposes a generalized FaaS model for edge computing that enables functions to switch between remote and local state phases, reducing latency and resource usage for IoT applications.

Contribution

It introduces a new pattern allowing functions to alternate between remote and local state, with persistent memory containers, improving resource utilization and latency in edge environments.

Findings

Reduced tail latencies in edge FaaS scenarios

Improved resource utilization on edge nodes

Potential for real-time ML applications in IoT

Abstract

In FaaS, users invoke remote functions, which encapsulate service(s). These functions typically need to remotely access a persistent state via external services: this makes the paradigm less attractive in edge systems, especially for IoT applications, due to the increased delay and outbound traffic. We propose to generalize the FaaS paradigm by allowing functions to alternate between remote-state and local-state phases, depending on internal and external conditions, and dedicating a container with persistent memory to functions when in a local-state phase. We present initial results showing that this simple yet powerful pattern allows to better utilize the available resources, which are scarce on edge nodes, while significantly reducing tail latencies, which is key to enable many new applications based on real-time ML, e.g., in smart vehicles and smart factory scenarios