Air Quality Forecasting (AQF) is a new discipline that attempts to reliably predict atmospheric pollution. The application has complex workflow and in order to produce timely and reliable forecast results daily, each execution requires multiple computational and storage resources to be simultaneously and collaboratively available. Deploying AQF on grid is one option to satisfy such needs, but r...

Data-intensive and long-lasting applications running in the form of workflows are being increasingly more 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 imp...

In this paper, we introduce a workflow-oriented system architecture for the processing of client requests (CRs) for container transportation. In the context of multi-transfer container transportation, the processing of CRs can be achieved by specific sequences of interdependent activities. These sequences need to be just-in time created. They also need to be adapted to deal with unexpected even...

The success of web services has infuenced the way in which grid applications are being written. Grid users seek to use combinations of web services to perform the overall task they need to achieve. In general this can be seen as a set of services with a workflow document describing how these services should be combined. The user may also have certain constraints on the workflow operations, such...

As the Grid is becoming the day-to-day infrastructure for e-Science and e-Business, support is required for more complex and demanding application scenarios in which not just a single resource is required, but a set of resources with certain dependencies. Such workflows complicate the management of resources, especially in cases where they are offered by several different resource providers, si...

Workflow scheduling on utility Grids is a complex multi-objective optimization problem which tries to optimize several scheduling criteria such as execution time and cost. One common approach to the problem is to optimize only one criterion, while other criteria are constrained within fixed thresholds. In this paper, we propose a new scheduling algorithm called Budget Partial Critical Path (Bud...

Scientific workflows comprising of many computational tasks including data dependency may require multiple and heterogeneous amount of computing resources during runtime. Scheduling such workflows with the objective of achieving minimal makespan and cost and maximal resource usage is a challenge in any computing environment. The researchers aim at developing novel algorithm to schedule scientif...

Large-scale scientific experiments are being conducted in collaboration with teams that are dispersed globally. Each team shares its data and utilizes distributed resources for conducting experiments. As a result, scientific data are replicated and cached at distributed locations around the world. These data are part of application workflows, which are designed for reducing the complexity of ex...

Based on the analysis of limitation of existing workflow management system, a workflow management system based on micro kernel is researched and designed. In this system, a micro kernel based workflow engine is designed by separating the service implementation and activity scheduling; the workflow engine interface is defined to connect the related workflow components seamlessly; and then graphi...

We examine the problem of reliable workflow scheduling with less resource redundancy. As scheduling workflow applications in heterogeneous systems, either for optimizing the reliability or for minimizing the makespan, are NP-Complete problems, we alternatively find schedules for meeting specific reliability and deadline requirements. First, we analyze the reliability of a given schedule using t...