Resource and Instance Hour Minimization for Deadline Constrained DAG Applications Using Computer Clouds

In this paper, we address the resource and virtual machine instance hour minimization problem for directed-acyclic-graph-based deadline constrained applications deployed on computer clouds. The allocated resources and instance hours on computer clouds must: (1) guarantee the satisfaction of a deadline constrained application's end-to-end deadline; (2) ensure that the number of virtual machine (VM) instances allocated to the application is minimized; (3) under the allocated number of VM instances, determine application execution schedule that minimizes the application's makespan; and (4) under the decided application execution schedule, determine a VM operation schedule, i.e., when a VM should be turned on or off, that minimizes total VM instance hours needed to execute the application. We first give lower and upper bounds for the number of VM instances needed to guarantee the satisfaction of a deadline constrained application's end-to-end deadline. Based on the bounds, we develop a heuristic algorithm called minimal slack time and minimal distance (MSMD) algorithm that finds the minimum number of VM instances needed to guarantee the application's deadline and schedules tasks on the allocated VM instances so that the application's makespan is minimized. Once the application execution schedule and the number of VM instances needed are determined, the proposed VM instance hour minimization (IHM) algorithm is applied to further reduce the instance hours needed by VMs to complete the application's execution. Our experimental results show that the MSMD algorithm can guarantee applications' end-to-end deadlines with less resources than the HEFT [32], MOHEFT [16], DBUS [9], QoS-base [40] and Auto-Scaling [25] heuristic scheduling algorithms in the literature. Furthermore, under allocated resources, the MSMD algorithm can, on average, reduce an application's makespan by 3.4 percent of its deadline. In addition, with the IHM algorithm we can effectively reduce the application's execution instance hours compared with when IHM is not applied.