A Decentralized Framework for Serverless Edge Computing in the Internet of Things

TL;DR

This paper proposes a decentralized framework for serverless edge computing tailored for IoT environments, optimizing task dispatching to reduce response times and improve fairness in resource-constrained networks.

Contribution

It introduces a novel, simple dispatching framework that leverages network information and is suitable for deployment on limited IoT devices, addressing performance issues in decentralized settings.

Findings

Efficient task dispatching reduces response times in IoT edge environments.

Framework adapts to client mobility and request pattern variations.

System copes effectively with network congestion.

Abstract

Serverless computing is becoming widely adopted among cloud providers, thus making increasingly popular the Function-as-a-Service (FaaS) programming model, where the developers realize services by packaging sequences of stateless function calls. The current technologies are very well suited to data centers, but cannot provide equally good performance in decentralized environments, such as edge computing systems, which are expected to be typical for Internet of Things (IoT) applications. In this paper, we fill this gap by proposing a framework for efficient dispatching of stateless tasks to in-network executors so as to minimize the response times while exhibiting short- and long-term fairness, also leveraging information from a virtualized network infrastructure when available. Our solution is shown to be simple enough to be installed on devices with limited computational capabilities, such as IoT gateways, especially when using a hierarchical forwarding extension. We evaluate the proposed platform by means of extensive emulation experiments with a prototype implementation in realistic conditions. The results show that it is able to smoothly adapt to the mobility of clients and to the variations of their service request patterns, while coping promptly with network congestion.