Ghari et al., 2025
| Publication | Publication Date | Title |
|---|---|---|
| Varghese et al. | A survey on edge performance benchmarking | |
| Han et al. | Benchmarking big data systems: A review | |
| Silva et al. | Cloudbench: Experiment automation for cloud environments | |
| JP7590088B2 (en) | Dynamic automation of pipeline artifact selection | |
| Bautista Villalpando et al. | Performance analysis model for big data applications in cloud computing | |
| CA3036812A1 (en) | Test case generator built into data-integration workflow editor | |
| US9971669B2 (en) | Predicting performance of a software application over a target system | |
| Fursin et al. | Collective knowledge: Towards R&D sustainability | |
| Barve et al. | FECBench: A holistic interference-aware approach for application performance modeling | |
| CN110740079A (en) | full link benchmark test system for distributed scheduling system | |
| Kumar et al. | Association learning based hybrid model for cloud workload prediction | |
| Harichane et al. | KubeSC‐RTP: Smart scheduler for Kubernetes platform on CPU‐GPU heterogeneous systems | |
| Sfaxi et al. | Babel: a generic benchmarking platform for Big Data architectures | |
| Augusto et al. | RETORCH: an approach for resource-aware orchestration of end-to-end test cases | |
| Bodik | Automating datacenter operations using machine learning | |
| Jha et al. | A cost-efficient multi-cloud orchestrator for benchmarking containerized web-applications | |
| Buzato et al. | Optimizing microservices performance and resource utilization through containerized grouping: An experimental study | |
| Ghari et al. | SparkPerf: A Benchmarking Framework for Evaluating the Performance of Spark Data Analytics Projects | |
| Ferme et al. | Performance comparison between BPMN 2.0 workflow management systems versions | |
| Ghari et al. | SparkPerf: A Machine Learning Benchmarking Framework for Spark-based Data Science Projects | |
| Tzenetopoulos et al. | Orchestration Extensions for Interference-and Heterogeneity-Aware Placement for Data-Analytics | |
| Ataie et al. | An Empirical Study on Impact of Programming Languages on Performance of Open-source Serverless Platforms | |
| Müller | Ml-based power consumption prediction models for edge devices | |
| Yoo et al. | Performance analysis tool for HPC and big data applications on scientific clusters | |
| Daniel et al. | Workflow engine performance evaluation by a black-box approach |