A green SLA constrained scheduling algorithm for parallel/scientific applications in heterogeneous cluster systems

Abstract

Cloud services utilize Heterogeneous Clusters as the hardware infrastructure at the backend. Minimal energy consumption in Heterogeneous Cluster System (HCS) is an important but challenging job. It can bring numerous benefits such as drop in operational cost, enhanced system reliability and green environment. Scheduling on HCS, with the objectives of minimizing the energy consumption, is being addressed by the research community at large. This work proposes a scheduling algorithm with green Service Level Agreement (SLA) constrained execution of parallel applications. The green SLA assumes that the tasks are to be scheduled on Dynamic Voltage Frequency Scaling (DVFS) enabled HCS. The proposed algorithm acts in two phases: first, it minimizes the energy consumption for the slacks of the schedule using DVFS technique, and second, a green SLA is made between a customer and service provider to maintain a good energy-performance trade-off. With this strategy, makespan of the schedule is extended a bit but the energy consumption is minimized for the period of extended makespan. It is observed that the decrease in one level of voltage and frequency of high-speed Processing Element (PE) saves more energy compared to that of low-speed PE. To utilize this, jobs running on higher voltage and frequency level of the PE are prioritized first. The performance of the proposed algorithm is studied by simulation on several standard Directed Acyclic Graphs (DAGs) and few other well-known real-world scientific workflows. The comparative study exhibits the effectiveness of the proposed algorithm over state of the art on four real heterogeneous PEs.