A Genetic Algorithm for Multiprocessor Scheduling
IEEE Transactions on Parallel and Distributed Systems
Dynamic scheduling of scientific workflow applications on the grid: a case study
Proceedings of the 2005 ACM symposium on Applied computing
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Service-Oriented Environments for Dynamically Interacting with Mesoscale Weather
Computing in Science and Engineering
Taverna: lessons in creating a workflow environment for the life sciences: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
Scientific workflow management and the Kepler system: Research Articles
Concurrency and Computation: Practice & Experience - Workflow in Grid Systems
A Framework for Collecting Provenance in Data-Centric Scientific Workflows
ICWS '06 Proceedings of the IEEE International Conference on Web Services
Grid capacity planning with negotiation-based advance reservation for optimized QoS
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Efficient scheduling of scientific workflows in a high performance computing cluster
CLADE '08 Proceedings of the 6th international workshop on Challenges of large applications in distributed environments
Service-Oriented Architecture for VIEW: A Visual Scientific Workflow Management System
SCC '08 Proceedings of the 2008 IEEE International Conference on Services Computing - Volume 1
Towards Quality of Service in Scientific Workflows by Using Advance Resource Reservations
SERVICES '09 Proceedings of the 2009 Congress on Services - I
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications
Adaptive grid job scheduling with genetic algorithms
Future Generation Computer Systems
Managing rapidly-evolving scientific workflows
IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
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Scientific applications are more and more faced with very large volumes of data and complex, resource-intensive workflows that process or analyze these data. The recent interest in web services and service-oriented architectures has strongly facilitated the development of individual workflow activities as well as their composition and the distributed execution of complete workflows. However, in many applications concurrent scientific workflows may be served by multiple competing providers, with each of them offering only limited resources. At the same time, these workflows need to be executed in a predictable manner, with dedicated Quality of Service guarantees. In this paper, we introduce an approach to Advance Resource Reservation for service-oriented complex scientific workflows that optimize resource consumption based on user-defined criteria (e.g., cost or time). It exploits optimization techniques using genetic algorithms for finding optimal or near-optimal allocations in a distributed system. The approach takes into account the locality of services and in particular enforces constraints imposed by control or data flow dependencies within workflows. Finally, we provide a comprehensive evaluation of the effectiveness of the proposed approach.