Energy-Aware Scheduling on Multicore Heterogeneous Grid Computing Systems

We address a multicriteria nonpreemptive
energy-aware scheduling problem for
computationalGrid systems. This work introduces
a new formulation of the scheduling problem for
multicore heterogeneous computational Grid
systems in which the minimization of the energy
consumption, along with the makespan metric,
is considered. We adopt a two-level model, in
which a meta-broker agent (level 1) receives all
user tasks and schedules them on the available
resources, belonging to different local providers
(level 2). The computing capacity and energy consumption of resources are taken from real
multi-core processors from the main current
vendors. Twenty novel list scheduling methods
for the problem are proposed, and a comparative
analysis of all of them over a large set of problem
instances is presented. Additionally, a scalability
study is performed in order to analyze the contribution
of the best new bi-objective list scheduling
heuristics when the problem dimension grows.
We conclude after the experimental analysis that
accurate trade-off schedules are computed by
using the new proposed methods.