Quality matters: A comprehensive comparative study of edge computing simulators

Abstract

Edge computing, by pushing resources closer to the network’s edge, is revolutionizing data processing, enabling real-time analysis and localized decision-making on resource-constrained devices. However, designing and validating innovative solutions within this dynamic environment presents significant challenges.

While numerous edge simulators exist, their shortcomings often restrict researchers’ ability to address their research questions. Many of them serve specific use cases (e.g., small scale scenarios, static application placement, etc.), lacking the breadth and flexibility needed for diverse research requirements. Furthermore, the lack of benchmarking studies complicates the process of selecting the right simulators for a specific need.

This study addresses these limitations by presenting a comprehensive evaluation of 24 edge computing simulators, filling a critical gap in the literature. We propose a robust methodology that assesses the simulators based on functionality, maintenance, scalability, reliability, efficiency, and usability. Our study provides clear classifications and comparisons of the simulators to assist researchers in selecting the most suitable one for their edge computing scenarios. Additionally, we identify and discuss opportunities and challenges for advancing the current state of the art in edge simulation, highlighting potential areas for future research.