Foggy: A Platform for Workload Orchestration in a Fog Computing Environment

TL;DR

Foggy is an open-source platform designed for workload orchestration in fog computing environments, supporting resource negotiation, scheduling, and workload placement for IoT and 5G applications.

Contribution

It introduces a comprehensive architectural framework and software platform tailored for fog computing, integrating traditional and non-traditional resource management and planning.

Findings

Demonstrated effective workload orchestration in video surveillance and vehicle tracking.

Supported diverse resource constraints including networking and location.

Showcased potential for economic and pricing models in resource management.

Abstract

In this paper we present Foggy, an architectural framework and software platform based on Open Source technologies. Foggy orchestrates application workload, negotiates resources and supports IoT operations for multi-tier, distributed, heterogeneous and decentralized Cloud Computing systems. Foggy is tailored for emerging domains such as 5G Networks and IoT, which demand resources and services to be distributed and located close to data sources and users following the Fog Computing paradigm. Foggy provides a platform for infrastructure owners and tenants (i.e., application providers) offering functionality of negotiation, scheduling and workload placement taking into account traditional requirements (e.g. based on RAM, CPU, disk) and non-traditional ones (e.g. based on networking) as well as diversified constraints on location and access rights. Economics and pricing of resources can also be considered by the Foggy model in a near future. The ability of Foggy to find a trade-off between infrastructure owners' and tenants' needs, in terms of efficient and optimized use of the infrastructure while satisfying the application requirements, is demonstrated through three use cases in the video surveillance and vehicle tracking contexts.