Estimating Energy Consumption of Cloud, Fog and Edge Computing Infrastructures

Abstract

Abstract: To address the imperative need for enhanced locality considerations, innovative Cloud-related architectures, such as Edge Computing, have emerged. Despite the burgeoning popularity of these architectures, their energy consumption remains a relatively unexplored domain. To delve into this critical question, we present a comprehensive approach. Initially, we establish a taxonomy delineating diverse Cloud-related architectures. Subsequently, we introduce an intricate energy model designed to assess their consumption patterns. What sets our model apart is its inclusivity, encapsulating not only the energy usage of computing facilities but also factoring in cooling systems and the energy consumption of network devices connecting end users to Cloud resources. In contrast to prior proposals, our model provides a holistic view of energy consumption within the Cloud ecosystem. The instantiation of our model on various Cloud-related architectures, ranging from fully centralized to entirely distributed ones, facilitates a nuanced comparison of their energy consumption. Our findings reveal that a fully distributed architecture, by eschewing intra-data center networks and large-scale cooling systems, exhibits a notable energy efficiency advantage, consuming between 14% and 25% less energy than fully centralized and partially distributed architectures, respectively. Notably, our work represents a pioneering effort in introducing a model that empowers researchers to analyze and compare the energy consumption of diverse Cloud-related architectures.