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 …

To program in distributed computing environments such as grids and clouds, workflow is
adopted as an attractive paradigm for its powerful ability in expressing a wide range of …

When deploying workflows in cloud environments, the use of Spot Instances (SIs) is
intriguing as they are much cheaper than on-demand ones. However, SIs are volatile and …

Cloud computing evolved from the concept of utility computing, which is defined as the
provision of computational and storage resources as a metered service. Another key …

Abstract Bag-of-Tasks (BoT) workflows are widespread in many big data analysis fields.
However, there are very few cloud resource provisioning and scheduling algorithms tailored …

Task scheduling and resource utilization have always been among the most critical issues
for high performance in heterogeneous computing. The heterogeneity of computation costs …

We study the problem of scheduling tasks onto a heterogeneous multi-core processor
platform for makespan minimization, where each cluster on the platform has a probability of …

With the advent of heterogeneous multiprocessor architectures, efficient scheduling for high
performance has been of significant importance. However, joint considerations of reliability …

There is a growing interest in the development of in-network dispersed computing
paradigms that leverage the computing capabilities of heterogeneous resources dispersed …

In modern distributed computing systems, unpredictable and unreliable infrastructures result
in high variability of computing resources. Meanwhile, there is significantly increasing …