Job Scheduling Model for Cloud Computing Based on Multi-Objective Genetic Algorithm
Cloud computing is an emerging high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. To improve the overall performance of cloud computing, with the deadline constraint, a task scheduling model is established for reducing the system power consumption of cloud computing and improving the profit of service providers. For the scheduling model, a solving method based on multi-objective genetic algorithm (MO-GA) is designed and the research is focused on encoding rules, crossover operators, selection operators and the method of sorting Pareto solutions. Based on open source cloud computing simulation platform CloudSim, compared to existing scheduling algorithms, the results show that the proposed algorithm can obtain a better solution, and it provides a balance for the performance of multiple objects.
Keywords: Task Scheduling, Cloud Computing, Multi-Objective Genetic Algorithm, CloudSim
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ABOUT THE AUTHORS
Jing Liu
Jing Liu is a Ph.D. student at National Digital Switching System Engineering & Technology Research Center, China. He has completed his Bachelor¡¯s and Master¡¯s degrees in Information Engineering University, Zhengzhou, Henan province. He is actively involved in research on resource management in virtualized data centers for Cloud computing, job scheduling and PSS.
Xing-Guo Luo
Xing-guo Luo is Professor of National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and wireless communication.
Xing-Ming Zhang
Xing-ming Zhang is Professor of National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and Network on a Chip
Fan Zhang
Fan Zhang is Lecturer of National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and Network on a Chip
Bai-Nan Li
Bai-nan Li is a Ph.D. student at National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and resource allocation.
Jing Liu
Jing Liu is a Ph.D. student at National Digital Switching System Engineering & Technology Research Center, China. He has completed his Bachelor¡¯s and Master¡¯s degrees in Information Engineering University, Zhengzhou, Henan province. He is actively involved in research on resource management in virtualized data centers for Cloud computing, job scheduling and PSS.
Xing-Guo Luo
Xing-guo Luo is Professor of National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and wireless communication.
Xing-Ming Zhang
Xing-ming Zhang is Professor of National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and Network on a Chip
Fan Zhang
Fan Zhang is Lecturer of National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and Network on a Chip
Bai-Nan Li
Bai-nan Li is a Ph.D. student at National Digital Switching System Engineering & Technology Research Center, China. His interests include cloud computing and resource allocation.
