Maximizing system's total accrued utility value for parallel and time-sensitive applications

For a time-sensitive application, the usefulness or the quality of the application's end result depends on the time when the result is delivered, or when the application is completed. A Time Utility Function (TUF) is often used to represent the dependency between an application's accrued value and its completion time. For parallel and time-sensitive applications, each application has multiple tasks that must be executed concurrently in order to produce a result. Therefore, their execution occupies resources in two dimensions: spatial, i.e., the number of processing units needed to support concurrent tasks, and temporal, i.e., time duration needed to complete the application. Because of the parallelism and time-sensitive features of the applications, the execution interference among parallel and time-sensitive applications can be both in spatial and temporal domains. In this paper, we first introduce a metric to measure the spatial-temporal interference on applications' accrued values. Second, based on the metric, we develop a scheduling algorithm, i.e., the Discounting Spatial-Temporal Interference (DSTI) scheduling algorithm, to maximize system's total accrued utility value for a given set of parallel and time-sensitive applications. Our simulation results show that the proposed DSTI algorithm results in close to optimal solutions and also has clear advantage over existing approaches in the literature in terms of system total accrued utility values and profitable application ratio. It accrues up to 164%, 150%, and 97% more system value, and up to 21%, 35%, and 18% higher profitable application ratio than the Gang EDF, the FCFS with backfilling, and the 0-1 Knapsack based scheduling algorithms, respectively.