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A New Distributed Strategy to Schedule Computing Resource

  • Qi WangEmail author
  • Pan Deng
  • Qinghong Yang
  • Wei Yuan
  • Yaolong Nie
  • Chaofan Bi
  • Han-Chieh Chao
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 142)

Abstract

Distributed scheduling strategy for computing resource (DSSCR) talks about a wide range of knowledge, such as distributed parallel computing, resource scheduling, heartbeat monitoring and data security. When people deal with a large number of concurrent computing tasks, designing a reasonable, efficient, safe scheduling system becomes important, it needs not only to execute safely, reduce the pressure on the server, but also improve the efficiency of task execution and correct results return. So the focus of this paper is to propose a DCRSS to solve the above problems. Nine categories of test cases are designed to assess its efficiency. There are 355 tests are executed, the success rate is over 90 %, saving 60 % time.

Keywords

Distributed scheduling Computing resource Parallel computing Video analysis task 

Notes

Acknowledgement

The work was supported by the National Natural Science Foundation of China (No. 61100066).

References

  1. 1.
    Deng, P., Zhang, J.W., Rong, X.H., Chen, F.: A model of large-scale device collaboration system based on PI-calculus for green communication. Telecommun. Syst. 52, 1313–1326 (2013)Google Scholar
  2. 2.
    Deng, P., Zhang, J.W., Rong, X.H., Chen, F.: Modeling the large scale device control system based on PI-calculus. Adv. Sci. Lett. 4, 2374–2379 (2011)CrossRefGoogle Scholar
  3. 3.
    Zhang, J.W., Deng, P., Wan, J.F., Yan, B.Y., Rong, X.H., Chen, F.: A novel multimedia device ability matching technique for ubiquitous computing environments. EURASIP J. Wireless Commun. Netw. 2013, 1–12 (2013)CrossRefGoogle Scholar
  4. 4.
    Rong, X.H., Deng, P., Chen, F.: A large-scale device collaboration resource selection method with multi-Qos constraint supported. Adv. Mater. Res. 143, 894–898 (2011)Google Scholar
  5. 5.
    Rong, X.H., Chen, F., Deng, P., Ma, S.L.: A large scale device collaboration mechanism. J. Comput. Res. Dev. 9, 1589–1596 (2011)Google Scholar
  6. 6.
    Chen, F., Rong, X.H., Deng, P., Ma, S.L.: A survey of device collaboration technology and system software. Acta Electronica Sinica 39, 440–447 (2011)Google Scholar
  7. 7.
    Mezmaz, M., Melab, N., Kessaci, Y., et al.: A bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing system. J. Parallel Distrib. Comput. (JPDC) 71(11), 1497–1508 (2011)CrossRefGoogle Scholar
  8. 8.
    You, X-d., Xu, X-h., Wan, J., el al.: RAS-M: resource allocation strategy based on market mechanism in cloud computing. In: Fourth ChinaGrid Annual Conference, pp. 256–263 (2009)Google Scholar
  9. 9.
    Lee, Y.C., Zomaya, A.Y.: Energy efficient utilization of resources in cloud computing system. J. Supercomput. 53, 1–13 (2010)CrossRefGoogle Scholar

Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015

Authors and Affiliations

  • Qi Wang
    • 1
    Email author
  • Pan Deng
    • 2
  • Qinghong Yang
    • 1
  • Wei Yuan
    • 2
  • Yaolong Nie
    • 2
  • Chaofan Bi
    • 2
  • Han-Chieh Chao
    • 3
    • 4
  1. 1.Department of SoftwareBeihang UniversityBeijingChina
  2. 2.Institute of Software, Chinese Academy of SciencesBeijingPeople’s Republic of China
  3. 3.Institute of Computer Science and Information and Department of Electronic EngineeringNational Ilan University, I-LanHualienTaiwan
  4. 4.Department of Electrical EngineeringNational Dong Hwa UniversityHualienTaiwan

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