ECLYPSE: a Python Framework for Simulation and Emulation of the Cloud-Edge Continuum

2025-01-28

AI Summary

Evaluating resource management and service placement strategies in dynamic, heterogeneous cloud–edge collaborative environments is challenging due to poor experimental reproducibility, difficulty in quantitative assessment, and prolonged prototype validation cycles. Method: This paper proposes an event-driven, configurable simulation framework built upon discrete-event simulation (DES) and Linux containerization. It introduces a novel architecture integrating network-state awareness with resource-aware adaptive scheduling, enabling seamless operation across pure simulation, simulation–physical hybrid, and other execution modes, and supporting rapid cross-scenario prototyping via RESTful APIs. Contribution/Results: Evaluated on three representative use cases, the framework significantly reduces strategy evaluation time, enhances experimental reproducibility and system scalability, and provides a general-purpose, flexible platform for designing and validating cloud–edge coordination mechanisms.

Technology Category

• Planning, Routing, and Scheduling: Plan Execution and Monitoring
• Search and Optimization: Sampling/Simulation-based Search
• Multiagent Systems: Coordination and Collaboration

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

The Cloud-Edge continuum enhances application performance by bringing computation closer to data sources. However, it presents considerable challenges in managing resources and determining service placement, as these tasks require navigating diverse, dynamic environments characterised by fluctuating network conditions. Addressing these challenges calls for tools combining simulation and emulation of Cloud-Edge systems to rigorously assess novel application and resource management strategies. In this paper, we introduce ECLYPSE, a Python-based framework that enables the simulation and emulation of the Cloud-Edge continuum via adaptable resource allocation and service placement models. ECLYPSE features an event-driven architecture for dynamically adapting network configurations and resources. It also supports seamless transitions between simulated and emulated setups. In this work, ECLYPSE capabilities are illustrated over three use cases, showing how the framework supports rapid prototyping across diverse experimental settings.

Problem

• Cloud-Edge Communication
• Dynamic Network Environment
• Resource Management

Innovation

• Cloud-Edge Simulation
• Adaptive Networking
• Service Placement Optimization