AuctionWhisk: Using an Auction-Inspired Approach for Function Placement in Serverless Fog Platforms

TL;DR

AuctionWhisk introduces an auction-inspired, decentralized method for function placement in fog computing, optimizing revenue and request handling in serverless environments across cloud and edge nodes.

Contribution

It presents a novel auction-based, online, decentralized approach for function placement in fog platforms, with a prototype implementation demonstrating its effectiveness.

Findings

Maximizes revenue for overloaded fog nodes.

Prevents request drops during high load.

Works effectively in real-time, decentralized settings.

Abstract

The Function-as-a-Service (FaaS) paradigm has a lot of potential as a computing model for fog environments comprising both cloud and edge nodes, as compute requests can be scheduled across the entire fog continuum in a fine-grained manner. When the request rate exceeds capacity limits at the resource-constrained edge, some functions need to be offloaded towards the cloud. In this paper, we present an auction-inspired approach in which application developers bid on resources while fog nodes decide locally which functions to execute and which to offload in order to maximize revenue. Unlike many current approaches to function placement in the fog, our approach can work in an online and decentralized manner. We also present our proof-of-concept prototype AuctionWhisk that illustrates how such an approach can be implemented in a real FaaS platform. Through a number of simulation runs and system experiments, we show that revenue for overloaded nodes can be maximized without dropping function requests.