Scheduling Critical Periodic Jobs with Selective Partial Computations along with Gang Jobs

One of the main issues with distributed systems, like clouds, is scheduling complex workloads, which are made up of various job types with distinct features. Gang jobs are one kind of parallel applications that these systems support. This paper examines the scheduling of workloads that comprise gangs and critical periodic jobs that can allow for partial computations when necessary to overcome gang job execution. The simulation's results shed important light on how gang performance is impacted by partial computations of critical jobs. The results also reveal that, under the proposed scheduling scheme, partial computations which take into account gangs’ degree of parallelism, might lower the average response time of gang jobs, resulting in an acceptable level of the average results precision of the critical jobs. Additionally, it is observed that as the deviation from the average partial computation increases, the performance improvement due to partial computations increases with the aforementioned tradeoff remaining significant.