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We present the ASKALON environment whose goal is to simplify the development and execution of workflow applications on the Grid. ASKALON is centered around a set of high-level services for transparent and effective Grid access, including a Scheduler for optimized mapping of workflows onto the Grid, an Enactment Engine for reliable application execution, a(More)
Most existing Grid application development environments provide the application developer with a nontransparent Grid. Commonly, application developers are explicitly involved in tedious tasks such as selecting software components deployed on specific sites, mapping applications onto the Grid, or selecting appropriate computers for their applications.(More)
Grid schedulers require individual activity performance predictions to map workflow activities on different Grid sites. The effectiveness of the scheduling systems is hampered by inaccurate predictions due to the inability of existing predictors to effectively model the dynamic and heterogeneous nature of Grid resources, or the wide range of problem sizes(More)
Scheduling multiple large-scale parallel workflow applications on heterogeneous computing systems like hybrid clouds is a fundamental NP-complete problem that is critical to meeting various types of QoS (Quality of Service) requirements. This paper addresses the scheduling problem of large-scale applications inspired from real-world, characterized by a huge(More)
The execution of workflow applications on the grid is a complex issue because of its dynamic and heterogeneous nature. While the grid provides good potential for achieving high performance, it also introduces a broad set of unpredictable overheads and possible failures. In this paper we present new methods for scalable and fault tolerant coordination of(More)
It is a large and complex task to design and implement a workflow management system that supports scalable executions of largescale scientific workflows in distributed and unstable Grid environments. In this paper we describe the Distributed workflow Enactment Engine (DEE) of the ASKALON application development environment for Grid computing. DEE proposes a(More)
As more and more data can be generated at a faster-than-ever rate nowadays, it becomes a challenge to processing large volumes of data for complex data analysis. In order to address performance and cost issues of big data processing on clouds, we present a novel design of adaptive workflow management system which includes a data mining based prediction(More)
Personalized location-based service recommendation is an important trend in the development of online ecommerce applications. In this work, we integrate the application of location-based service with recommendation technologies to present a hybrid recommendation model and a prototype system (HiPerData) to evaluate and measure the validity based on the Yelp(More)
Scheduling large-scale applications on the Grid is a fundamental challenge and is critical to application performance and cost. Large-scale applications typically contain a large number of homogeneous and concurrent activities which are main bottlenecks, but open great potentials for optimization. This paper presents a new formulation of the well-known(More)