Recent studies focus primarily on low energy consumption or execution time for task
scheduling with precedence constraints in heterogeneous computing systems. In most …

Heterogeneous cloud datacenters are well-suited and cost-efficient platforms for execution
of scientific workflows requested from academics. Workflow scheduling algorithms have …

Cloud data centers consume huge amounts of electrical energy which results in an
increased operational cost, decreased system reliability and carbon dioxide footprints. Thus …

In the last years, scientific workflows have emerged as a fundamental abstraction for
structuring and executing scientific experiments in computational environments. Scientific …

Distributed computing workflow is an effective paradigm to express a range of applications
with cloud computing platforms for scientific research explorations. One of the most difficult …

Workflows may be defined as abstractions used to model the coherent flow of activities in the
context of an in silico scientific experiment. They are employed in many domains of science …

As the scale and complexity of heterogeneous computing systems grow, failures occur
frequently and have an adverse effect on solving large-scale applications. Hence, fault …

The enormous energy consumed by cloud data centers (CDCs) increases the carbon
footprints, operational cost and decreases the system reliability, so it becomes a great …

League championship algorithm is a recently proposed population-based evolutionary
algorithm for finding global optimal solutions in continuous optimization problems. The …

Finding feasible schedules for tasks running in hard, real-time distributed computing
systems is generally NP-hard. This paper describes a heuristic algorithm using evolutionary …