Datasets of synthetic workflows for cyber-physical edge-hub-cloud systems

These datasets of synthetic workflows were generated to evaluate the performance and scalability of a multi-constrained scheduling approach for workflow applications of various structures, sizes, and sensing/actuating requirements in a cyber-physical system (CPS) following the edge-hub-cloud paradigm. The examined CPS comprised four edge devices (i.e., single-board computers, each attached to an unmanned aerial vehicle (UAV) equipped with sensors/actuators) interacting with a hub device (e.g., a laptop), which in turn communicated with a more computationally capable cloud server. All system devices featured heterogeneous multicore processors and varied sensing/actuating or other specialized capabilities. The problem objective was the minimization of the overall latency of the application under deadline, memory, storage, energy, capability, and task precedence constraints. We generated 25 random workflows (task graphs) with 10, 20, 30, 40, and 50 nodes (5 task graphs for each size), utilizing the Task Graphs For Free (TGFF) random task graph generator [1],[2]. Additional task parameters (e.g., execution time, power consumption, memory, storage, output data size, capability) were included post-generation, using appropriate values. More details are provided in README.txt. References: [1] R. P. Dick, D. L. Rhodes, and W. Wolf, "TGFF: Task graphs for free," Proceedings of the Sixth International Workshop on Hardware/Software Codesign (CODES/CASHE), 1998, pp. 97-101, doi: 10.1109/HSC.1998.666245. [2] R. P. Dick, D. L. Rhodes, and K. Vallerio, "TGFF," https://robertdick.org/projects/tgff/.本合成工作流数据集旨在评估遵循边-枢纽-云范式的信息物理系统（CPS, cyber-physical system）中，针对不同结构、规模及传感/执行需求的工作流应用的多约束调度方法的性能与可扩展性。本次研究所涉CPS包含4台边缘设备（即单板计算机，每台均搭载配备传感/执行器的无人机（UAV, unmanned aerial vehicle）），与一台枢纽设备（如笔记本电脑）交互；枢纽设备进一步与算力更强的云服务器通信。所有系统设备均搭载异构多核处理器，并具备差异化的传感/执行或其他专用功能。该调度问题的优化目标为，在截止时间、内存、存储、能耗、功能适配及任务前置约束下，最小化应用的整体延迟。本研究使用免费任务图生成器（TGFF, Task Graphs For Free）的随机任务图生成工具[1],[2]，生成了25个随机工作流（任务图），其节点数分别为10、20、30、40和50（每种规模各5个任务图）。在生成任务图后，我们为其补充了合适的任务参数，包括执行时长、功耗、内存占用、存储需求、输出数据规模及功能适配要求等。更多细节详见README.txt文件。参考文献：[1] R. P. Dick、D. L. Rhodes及W. Wolf，《TGFF：免费任务图生成工具》，发表于第六届硬件/软件协同设计国际研讨会（CODES/CASHE, International Workshop on Hardware/Software Codesign），1998年，第97-101页，DOI: 10.1109/HSC.1998.666245。[2] R. P. Dick、D. L. Rhodes及K. Vallerio，《TGFF》，https://robertdick.org/projects/tgff/。