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Resource Scheduling Method of Meteorological Satellite Ground System Based on Load Balancing

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DOI: 10.23977/jeis.2017.22008 | Downloads: 11 | Views: 2529

Author(s)

Zhanyun Zhang 1, Manyun Lin 1, Xiangang Zhao 1, Lan Wei 1, Cunqun Fan 1

Affiliation(s)

1 National Satellite Meteorological Centre, Beijing, China

Corresponding Author

Zhanyun Zhang

ABSTRACT

Meteorological satellite data is large, and the corresponding data tasks are complex and diverse. Satellite ground application system makes the entire ground system resources applications some bottlenecks due to carrying more tasks.  That how to improve the resource utilization of the whole system has become a key problem in how to allocate the resources of the satellite ground application system rationally. In this paper, a resource scheduling method for meteorological satellite terrestrial application system based on load balancing is proposed. Firstly, the resources are defined quantitatively. Then, the resource requirements are formally described by matrix. Finally, the reasonable scheduling of resources is realized by load balancing. The proposed method can realize the load balance of the system resources under the premise of guaranteeing the efficiency of task execution.

KEYWORDS

Meteorological satellite, Ground application system, Resource scheduling, Load balancing.

CITE THIS PAPER

Zhanyun, Z. , Manyun, L. , Xiangang, Z. , Lizi, X. , Lan, W. , Cunqun, F. , (2017) Resource Scheduling Method of Meteorological Satellite Ground System Based on Load Balancing. Journal of Electronics and Information Science (2017) 2: 98-102.

REFERENCES

[1] A. Rosenthal, P. Mork, M. Li, J. Stanford, D. Koester, P. Reynolds, Cloud Computing: A New Business Paradigm for Biomedical Information Sharing, Journal of Biomedical Informatics, 2010, vol. 42, issue. 2, pp. 342-353.
[2] N. Bansal, K. W. Lee, V. Nagarajan, M. Zafer, Minimum congestion mapping in a cloud, Proceedings of the 30th annual ACM SIGACT-SIGOPS symposium on Principles of distributed computing, New York, USA, 2011, pp.267-276.
[3] B. Huang, R. Lin, K. Peng, H. Zou, F. Yang, Minimizing Latency in Fetching Virtual Machine Images Based on Multi-Point Collaborative Approach, Green Computing and Communications (GreenCom 2013), Beijing, China, Aug. 20-23, pp. 262-267.
[4] A. Leivadeas, C. Papagianni, S. Papavassiliou, Energy Aware Networked Cloud Mapping, 2013 12th IEEE International Symposium on Network Computing and Applications (NCA), 2013, pp.195-202.
[5] H. Xu, B. Li, A Versatile and Efficient Framework for Resource Management in the Cloud, IEEE Transactions on Parallel & Distributed Systems, vol.24, issue. 6, 2013, pp.1066-1076.

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