Energy-aware stochastic scheduler for batch of precedence-constrained jobs on heterogeneous computing system

The problem of optimal scheduling of precedence-constrained jobs as well as finding the Pareto-optimal sets for multi objective scheduling problem have been proven to be nondeterministic polynomial time (NP)-complete. The growing consumption of energy has compelled the researchers to consider energy consumption as an important parameter along with other parameters in multi-objective scheduling problem. Accordingly, many energy-aware precedence-constraints scheduling algorithms have been reported in the literature. Most of the algorithms have a limitation of treating this problem as a single objective optimization problem modelling with deterministic execution times rather than stochastic execution times. This work proposes energy-aware stochastic scheduler to schedule the batch of precedence-constrained jobs on dynamic voltage frequency scaling-enabled processors in order to optimize the energy consumption and the turnaround time. The execution and inter-communication times are stochastic which are drawn from independent probability distributions. A novel encoding for batch of precedence-constrained jobs, stochastic turnaround time and energy models are also proposed. Experimental results show that, compared with other algorithms, the proposed scheduler offers reduced turnaround time and reduced energy consumption.