Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
Journal of Global Optimization
Hypertool: A Programming Aid for Message-Passing Systems
IEEE Transactions on Parallel and Distributed Systems
An Evolutionary Measure for Image Matching
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
QoS guided min-min heuristic for grid task scheduling
Journal of Computer Science and Technology - Grid computing
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
An Incremental Genetic Algorithm Approach to 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
A Multiobjective Resources Scheduling Approach Based on Genetic Algorithms in Grid Environment
GCCW '06 Proceedings of the Fifth International Conference on Grid and Cooperative Computing Workshops
Differential evolution for sequencing and scheduling optimization
Journal of Heuristics
Scientific Programming - Scientific Workflows
Multi-objective planning for workflow execution on Grids
GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
A review of multiobjective test problems and a scalable test problem toolkit
IEEE Transactions on Evolutionary Computation
An innovative perspective on mapping in grids
BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
An adaptive multisite mapping for computationally intensive grid applications
Future Generation Computer Systems
International Journal of Approximate Reasoning
Flexible service selection with user-specific QoS support in service-oriented architecture
Journal of Network and Computer Applications
Meta-schedulers for grid computing based on multi-objective swarm algorithms
Applied Soft Computing
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Most algorithms developed for scheduling applications on global Grids focus on a single Quality of Service (QoS) parameter such as execution time, cost or total data transmission time. However, if we consider more than one QoS parameter (eg. execution cost and time may be in conflict) then the problem becomes more challenging. To handle such scenarios, it is convenient to use heuristics rather than a deterministic algorithm. In this paper we have proposed a workflow execution planning approach using Multiobjective Differential Evolution (MODE). Our goal was to generate a set of trade-off schedules according to two user specified QoS requirements (time and cost). The alternative tradeoff solutions offer more flexibility to users when estimating their QoS requirements of workflow executions. We have compared our results with two baseline multiobjective evolutionary algorithms. Simulation results show that our modified MODE is able to find a comparatively better spread of compromise solutions.