Big Data has emerged in the past few years as a new paradigm providing abundant data
and opportunities to improve and/or enable research and decision-support applications with …

For task-scheduling problems in cloud computing, a multi-objective optimization method is
proposed here. First, with an aim toward the biodiversity of resources and tasks in cloud …

Workflow scheduling concerns the mapping of complex tasks to cloud resources by taking
into account various Quality of Service requirements. In virtue of continuous proliferation in …

Given the dynamic and uncertain production environment of job shops, a scheduling
strategy with adaptive features must be developed to fit variational production factors …

Since cloud computing provides computing resources on a pay per use basis, a task
scheduling algorithm directly affects the cost for users. In this paper, we propose a novel …

In cloud computing, with full control of the underlying infrastructures, cloud providers can
flexibly place user jobs on suitable physical servers and dynamically allocate computing …

Due to the advancement of technology the datasets that are being processed nowadays in
modern computer clusters extend beyond the petabyte scale–the 4 detectors of the Large …

Services are delivered promptly and efficiently managed over the Internet using cloud
computing. Data and storage services are offered to users through cloud computing without …

In cloud computing, resources are dynamic, and the demands placed on the resources
allocated to a particular task are diverse. These factors could lead to load imbalances, which …

Hadoop has become a popular framework for processing data-intensive applications in
cloud environments. A core constituent of Hadoop is the scheduler, which is responsible for …