Portable Energy-Aware Cluster-Based Edge Computers

Abstract

Computational resources distributed at the edge of the network are the fundamental infrastructural component of edge computing. The operational scale of edge computing introduces new challenges for building and operating suitable computation platforms. Many application scenarios require edge computing resources to provide reliable response times while operating in dynamic and resource-constrained environments. In this paper, we present a novel architecture for energy-aware, cluster-based edge computers that are designed to be portable and usable in fieldwork scenarios. We use compact general-purpose commodity hardware to build a high-density cluster prototype, and implement a power-management runtime to enable real-time energy-awareness. Furthermore, we present an experimental analysis of the energy and resource-consumption characteristics of our prototype in the context of a data analytics application. The results show the feasibility of our prototype for the presented scenarios, but also reveal the intricacies of power-management approaches already built into modern CPUs. We show that different load balancing policies and cluster configurations have a significant impact on energy consumption and system responsiveness. Our insights lay the groundwork for future research on energy-consumption optimization approaches for cluster-based edge computers.