  The rapid and convenient provision of the available computing resources is a
crucial requirement in modern cloud computing environments. However, if only
the execution time is taken into account when the resources are scheduled, it
could lead to imbalanced workloads as well as to significant under-utilisation
of the involved Virtual Machines (VMs). In the present work a novel task
scheduling scheme is introduced, which is based on the proper adaptation of a
modern and quite effective evolutionary optimization method, the Gravitational
Search Algorithm (GSA). The proposed scheme aims at optimizing the entire
scheduling procedure, in terms of both the tasks execution time and the system
(VMs) resource utilisation. Moreover, the fitness function was properly
selected considering both the above factors in an appropriately weighted
function in order to obtain better results for large inputs. Sufficient
simulation experiments show the efficiency of the proposed scheme, as well as
its excellence over related approaches of the bibliography, with similar
objectives.
