RD-Gen：面向可复现调度评估的考虑多速率应用的随机有向无环图生成器
RD-Gen: Random DAG Generator Considering Multi-rate Applications for Reproducible Scheduling Evaluation
- Tier IV, Inc（Tier IV 公司）
- Graduate School of Science and Engineering, Saitama University（埼玉大学理工学研究科）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
针对现有随机DAG生成工具无法适配多速率应用、影响研究可靠性与可复现性的问题，本文提出RD-Gen工具，支持批量生成不同参数的随机DAG集，可适配各类研究需求。
中文摘要 AI 辅助
实时系统具有截止时间、资源约束等各类需求，且正变得更大更复杂，针对其性能分析与高效调度算法的研究愈发重要。有向无环图（DAG）模型可表达任务依赖关系与并行性，被用于此类研究；随机DAG集被用于验证实时系统相关方法的有效性与客观性。但目前尚无随机DAG生成工具能生成考虑最新多速率应用的DAG集，研究者需自行生成随机DAG集，这增加了额外工作量，降低了研究的可靠性与可复现性。为解决该问题，本文提出面向可复现调度评估的考虑多速率应用的随机DAG生成器（RD-Gen），该工具还支持批量生成不同参数的随机DAG集；案例研究表明，RD-Gen可适配各类问题设置与DAG研究需求。
英文摘要
Real-time systems have various requirements such as the deadline and resource constraints. In addition, real-time systems are becoming larger and more complex, and studies on performance analysis and efficient scheduling algorithms are becoming increasingly important. Directed acyclic graph (DAG) models, which can express task dependencies and parallelism, are used for such studies. Random DAG sets are used to demonstrate the effectiveness and objectivity of methods proposed for real-time systems. However, there is no random DAG generation tool available that can generate a DAG set that considers the latest multi-rate applications. Therefore, researchers need to generate random DAG sets on their own, leading to additional effort and reduced reliability and reproducibility. To solve this problem, we propose a random DAG generator considering multi-rate applications for reproducible scheduling evaluation (RD-Gen). RD-Gen also enables batch generation of random DAG sets with different parameters. Case studies are used to demonstrate that RD-Gen can manage various problem settings and DAG study requirements.
