To support the stringent requirements of the future intelligent and interactive applications, intelligence needs to become an essential part of the resource management in the edge environment. Developing intelligent orchestration solutions is a challenging and arduous task, where the evaluation and comparison of the proposed solution is a focal point. Simulation is commonly used to evaluate and compare proposed solutions. However, the currently existing, openly available simulators are lacking in terms of supporting the research on intelligent edge orchestration methods. To address this need, this article presents a simulation platform called Edge Intelligence Simulator (EISim), the purpose of which is to facilitate the research on intelligent edge orchestration solutions. EISim is extended from an existing fog simulator called PureEdgeSim. In its current form, EISim supports simulating deep reinforcement learning based solutions and different orchestration control topologies in scenarios related to task offloading and resource pricing on edge. The platform also includes additional tools for creating simulation environments, running simulations for agent training and evaluation, and plotting results.

翻译：为支撑未来智能交互应用对严苛性能的需求，智能已成为边缘环境中资源管理的核心要素。开发智能编排解决方案是一项极具挑战性的艰巨任务，其中对方案的评价与比较尤为关键。仿真技术常被用于评估和对比各类方案，然而当前公开可用的仿真器在支持智能边缘编排方法研究方面存在不足。针对这一需求，本文提出名为边缘智能仿真器（EISim）的仿真平台，旨在促进智能边缘编排解决方案的研究。EISim基于现有雾计算仿真器PureEdgeSim扩展而来。当前版本支持针对边缘任务卸载与资源定价场景的深度强化学习方案仿真，并兼容多种编排控制拓扑结构。该平台还包含创建仿真环境、运行智能体训练与评估仿真、以及结果可视化等辅助工具模块。