Workflow scheduling in scientific computing systems is one of the most challenging
problems that focuses on satisfying user-defined quality of service requirements while …

Large-scale applications expressed as scientific workflows are often grouped into
ensembles of inter-related workflows. In this paper, we address a new and important …

Cloud computing is emerging as a new paradigm of large-scale distributed computing. In
order to utilize the power of cloud computing completely, we need an efficient task …

The elasticity of Cloud infrastructures makes them a suitable platform for execution of
deadline-constrained workflow applications, because resources available to the application …

Cloud Service Providers are speedily becoming the target platform for scientific workflow
computations due to the massive possible and flexible pay-as-you-go pricing model …

The rapid development of the latest distributed computing paradigm, ie, cloud computing,
generates a highly fragmented cloud market composed of numerous cloud providers and …

In recent years, research has been conducted in the area of large systems models,
especially distributed systems, to analyze and understand their behavior. Simulators are …

In the last decade, cloud computing has become an effective and efficient service delivery
platform to offer resources, innovation, and economies of scale on telecommunication …

Scheduling multiple large-scale parallel workflow applications on heterogeneous computing
systems like hybrid clouds is a fundamental NP-complete problem that is critical to meeting …

Many resource management techniques for task scheduling, energy and carbon efficiency,
and cost optimization in workflows rely on a-priori task runtime knowledge. Building runtime …