Stochastic Fluid Model Analysis for Campus Grid Storage Service

  • Xiaofeng Shi
  • Huifeng Xue
  • Zhiqun Deng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3516)


Campus grid storage service is to aggregate the storage resources in the servers of Campus Grid Center and colleges (or institutes, departments), and the storage resources of personal computers in the campus network. It provides storage resources registration, allocation, scheduling, and release services for users by three levels storage architecture. Due to the storage nodes’ dynamites, the total storage space that nodes contribute will dynamically change with time. To study the performance of the storage service, the stochastic fluid model is adopted. By this analytical model, we got the mathematical results as follows: the function between the storage allocation probability and the number of nodes is got; if more nodes join the campus grid, the aggregated storage space will be larger, and then the available storage resources will be more; if the storage resources allocation rate is larger than the storage resources release rate, then the available storage resources will decrease.


Storage Space Busy Period Storage Service Storage Node Storage Resource 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Deng, Z., Liu, Z., Dai, G., Zhang, X., Mu, D.: Nodes’ Organization Mechanisms on Campus Grid Services Environment. In: Jin, H., Pan, Y., Xiao, N., Sun, J. (eds.) GCC 2004. LNCS, vol. 3251, pp. 247–250. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Barbot, N., Sericola, B.: Distribution of busy period in stochastic fluid models. Communications in Statistics-Stochastic Models 17(4) (2001)Google Scholar
  3. 3.
    Kulkarni, V.G.: Fluid Models for Single Buffer Systems. In: Dshalalow, J.H. (ed.) Frontiers in Queuing: Models and Applications in Science and Engineering, pp. 321–338. CRC Press, Boca Raton (1997)Google Scholar
  4. 4.
    Clévenot, F., Nain, P.: A Simple Fluid Model for the Analysis of the Squirrel P2P Caching System. In: Proceedings of the IEEE INFOCOM 2004 (2004)Google Scholar
  5. 5.
    Clévenot, F., Nain, P., Ross, K.W.: Stochastic Fluid Models for Cache Clusters. Performance Evaluation 59(1), 1–18 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xiaofeng Shi
    • 1
  • Huifeng Xue
    • 1
  • Zhiqun Deng
    • 1
  1. 1.College of AutomationNorthwestern Polytechnical UniversityXi’anChina

Personalised recommendations