Scheduling of scientific workflows on hybrid cloud architecture, which contains private and
public clouds, is a challenging task because schedulers should be aware of task inter …

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

Workflow Scheduling in cloud computing has drawn enormous attention due to its wide
application in both scientific and business areas. This is particularly an NP-complete …

Cloud computing is a distributed computing paradigm, that provides infrastructure and
services to the users using the pay-as-you-use billing model. With the increasing demands …

Now-a-days, Cloud computing is a technology which eludes provision cost while providing
scalability and elasticity to accessible resources on a pay-per-use basis. To satisfy the …

With the increase in deployment of scientific workflow applications on an IaaS cloud
computing environment, the distribution of workflow tasks to particular cloud instances to …

Cloud computing has emerged as a high-performance computing environment with a large
pool of abstracted, virtualized, flexible, and on-demand resources and services. Scheduling …

Benefiting from rich resources and virtualization technologies, hybrid cloud has emerged as
a promising solution to processing large-scale scientific workflow applications for users in a …

Clouds appear as appropriate infrastructures for executing Scientific Workflows (SWfs). A
cloud is typically made of several sites (or data centers), each with its own resources and …

Abstract The emergence of Cloud Computing as a model of service provisioning in
distributed systems instigated researchers to explore its pros and cons on executing different …