@inproceedings{b25807c7193a49188b7b39bd365b019d,
title = "A multi-task assignment method in cloud-based simulation",
abstract = "Cloud-based Simulation (Cloud Simulation) can significantly improve the capacity of existing networked modeling and simulation systems. The performance of the Cloud Simulation Platform tightly couples with the partitioning and allocation of simulation modules among different hosts. This paper proposed a Cloud Simulation resources scheduling strategy for initial partitioning based on Genetic Algorithm (GA). The Cloud Simulation resources scheduling model was given by considering the computing resources of involved hosts as well as the predicted computing load of simulation modules. The improved strategy of GA is designed according to the characteristics of the Cloud Simulation multi-task assignment problem. The simulation results demonstrate the feasibility and efficiency of the proposed method.",
keywords = "Cloud Computing, Cloud Simulation, Genetic Algorithm, Multi-task assignment",
author = "Lei Ren and Hejian Ou and Jin Cui and Bowen Li and Baocun Hou",
year = "2014",
language = "英语",
series = "26th European Modeling and Simulation Symposium, EMSS 2014",
publisher = "Dime University of Genoa",
pages = "171--174",
editor = "Yuri Merkuryev and Lin Zhang and Emilio Jimenez and Francesco Longo and Michael Affenzeller and Bruzzone, \{Agostino G.\}",
booktitle = "26th European Modeling and Simulation Symposium, EMSS 2014",
note = "26th European Modeling and Simulation Symposium, EMSS 2014 ; Conference date: 10-09-2014 Through 12-09-2014",
}