Workload Schedulers -- Genesis, Algorithms and Differences
This work provides a systematic taxonomy for researchers and practitioners in computer systems, but it is incremental as it organizes existing knowledge rather than introducing new algorithms or performance improvements.
The paper categorizes modern workload schedulers into three classes (Operating Systems Process Schedulers, Cluster Systems Jobs Schedulers, and Big Data Schedulers), describing their evolution, algorithms, and differences, while highlighting similarities in scheduling strategies across local and distributed systems.
This paper presents a novel approach to categorization of modern workload schedulers. We provide descriptions of three classes of schedulers: Operating Systems Process Schedulers, Cluster Systems Jobs Schedulers and Big Data Schedulers. We describe their evolution from early adoptions to modern implementations, considering both the use and features of algorithms. In summary, we discuss differences between all presented classes of schedulers and discuss their chronological development. In conclusion we highlight similarities in the focus of scheduling strategies design, applicable to both local and distributed systems.