Metis: Optimal Task Allocation Framework for the Edge/Hub/Cloud Paradigm

Abstract

Increased demands for real-time decision support and data analytics facilitate the need of performing significant computing away from the cloud and onto the IoT devices. In this paper, we propose Metis, a mathematical programming based framework, able to deliver an optimal task allocation when targeting a specific performance metric. Metis is currently suitable for systems which consist of an edge node, an intermediate node and the cloud infrastructure, but can be expanded to multi-Edge/Hub systems. Evaluation results using a real-life use-case scenario demonstrate that Metis provides the optimal task allocation by minimizing the overall latency of the system while taking into consideration the application's specific requirements and resource constraints of each computational unit.