Prediction of dynamical, nonlinear, and unstable process behavior
The Journal of Supercomputing
A novel approach for distributed application scheduling based on prediction of communication events
Future Generation Computer Systems
Tackling trust issues in virtual organization load balancing
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
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Motivated by the first process allocation limitations of the original Route load balancing algorithm, this paper presents RouteGA (Route with Genetic Algorithm support) which considers historical information about parallel application executions in order to optimize the first scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify process occupation at the launch moment. Such occupation is used to parameterize a genetic algorithm responsible for optimizing the process allocation on heterogeneous computing environments such as Grids. Results confirm RouteGA overperforms the original Route, which had previously overperformed others from literature.