Workflow scheduling is a key component behind the process for an optimal workflow enactment. It is a well-known NP-hard problem and is more challenging in the heterogeneous computing environment. The increasing complexity of the workflow applications is forcing researchers to explore hybrid approaches to solve the workflow scheduling problem. The performance of genetic algorithms can be enhance...

Data streaming applications, usually composed with sequential/parallel data processing tasks organized in a workflow manner, bring new challenges to workflow scheduling and resource allocation in grid environments. Due to high volumes of data and relatively limit storage capability, resource allocation and data streaming have to be storage aware. Also in order to improve system performance, dat...

Grid technology brings about a lot of innovative ideas and technologies for the development of Decision Support System. The existence of description languages, semantics, service publishing methods and Grid middleware have up to now enabled interoperability between decision resources available across the Grid environment. However, there is an emerging need for the ability to dynamically discove...

Data streaming applications, usually composed of sequential/parallel data processing tasks organized as a workflow, bring new challenges to workflow scheduling and resource allocation in grid environments. Due to the high volumes of data and relatively limited storage capability, resource allocation and data streaming have to be storage aware. Also to improve system performance, the data stream...

EMWF (Embedded Workflow Framework) is an open source middleware for flexible (i.e., configurable, customizable and adaptable), usercentric automation and assistive devices and systems. EMWF 1.0 provides a light-weight workflow manager and engines on Windows CE, Windows XP Embedded, and Linux. It is for small embedded automation devices. EMWF 2.0 also provides basic message passing and real-time...

Workflow management within DIET applied to multi-application scheduling Raphael Bolze Ecole Normale Superiere de Lyon The aim of my talk is to present the workflow management system implemented within DIET. DIET is a Network Enabled System built upon a set of distributed schedulers. I will explain the different solutions developed within DIET and how it is applied to the scope of workflow sched...

Task scheduling in heterogeneous computing environment such as grid computing is a critical and challenging problem. Many parallel applications consist of multiple computational components. While the execution of some of these components or tasks depends on the completion of other tasks, others can be executed at the same time, which increases parallelism of the problem. The task scheduling pro...

Data-intensive and long-lasting applications running in the form of workflows are being increasingly dispatched to cloud computing systems. Current scheduling approaches for graphs of dependencies fail to deliver high resource efficiency while keeping computation costs low, especially for continuous data processing workflows, where the scheduler does not perform any reasoning about the impact n...

Over the years, distributed environments have evolved from shared community platforms to utility-based models; the latest of these being Cloud computing. This technology enables the delivery of IT resources over the Internet and follows a pay-as-you-go model where users are charged based on their usage. There are various types of Cloud providers each of which has different product offerings. Th...

Pipelined workflows are a popular programming paradigm for parallel applications. In these workflows, the computation is divided into several stages and these stages are connected to each other through first-in first-out channels. In order to execute these workflows on a parallel machine, we must first determine the mapping of the stages onto the various processors on the machine. After finding...