Checkpointing and Migration of IoT Edge Functions

TL;DR

This paper presents a method using Docker and CRIU to checkpoint and migrate IoT edge functions, enabling more efficient resource use and improved system reliability despite IoT devices' resource constraints.

Contribution

It introduces a checkpointing approach for long-running functions on IoT devices using Docker and CRIU, enhancing migration and fault tolerance capabilities.

Findings

Checkpointing is slightly slower than Docker pause but more memory-efficient.

Checkpoint files are small, suitable for live migration and backup.

Method improves availability and reliability of IoT edge functions.

Abstract

The serverless and functions as a service (FaaS) paradigms are currently trending among cloud providers and are now increasingly being applied to the network edge, and to the Internet of Things (IoT) devices. The benefits include reduced latency for communication, less network traffic and increased privacy for data processing. However, there are challenges as IoT devices have limited resources for running multiple simultaneous containerized functions, and also FaaS does not typically support long-running functions. Our implementation utilizes Docker and CRIU for checkpointing and suspending long-running blocking functions. The results show that checkpointing is slightly slower than regular Docker pause, but it saves memory and allows for more long-running functions to be run on an IoT device. Furthermore, the resulting checkpoint files are small, hence they are suitable for live migration and backing up stateful functions, therefore improving availability and reliability of the system.