Skip to main content

Selecting the Shortest Itinerary in a Cloud-Based Distributed Mobility Network

  • Conference paper

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 217)

Abstract

New Internet technologies can considerably enhance contemporary traffic control and management systems (TCMS). Such systems need to process increasing volumes of data available in clouds, and so new algorithms and techniques for statistical data analysis are required. A very important problem for cloud-based TCMS is the selection of the shortest itinerary, which requires route comparison on the basis of historical data and dynamic observations. In the paper we compare two non-overlapping routes in a stochastic graph. The weights of the edges are considered to be independent random variables with unknown distributions. Only historical samples of the weights are available, and some edges may have common samples. Our purpose is to estimate the probability that the weight of the first route is greater than that of the second one. We consider the resampling estimator of the probability in the case of small samples and compare it with the parametric plugin estimator. The analytical expressions for the expectations and variances of the proposed estimators are derived, which allow theoretical evaluation of the estimators’ quality. The experimental results demonstrate that the resampling estimator is a suitable alternative to the parametric plug-in estimator. This problem is very important for a vehicle decision-making procedure to choose route from the available alternatives.

Keywords

  • traffic control and management
  • future Internet
  • stochastic graph
  • shortest route
  • resampling
  • small samples
  • estimation
  • simulation

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-00551-5_13
  • Chapter length: 8 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   229.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-00551-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   299.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Afanasyeva, H.: Resampling-approach to a task of comparison of two renewal processes. In: Proc. of the 12th Int. Conf. on Analytical and Stochastic Modelling Techniques and Applications, Riga, pp. 94–100 (2005)

    Google Scholar 

  2. Andronov, A., Fioshina, H., Fioshin, M.: Statistical estimation for a failure model with damage accumulation in a case of small samples. Journal of Statistical Planning and Inference 139(5), 1685–1692 (2009), doi:10.1016/j.jspi.2008.05.026

    CrossRef  MATH  MathSciNet  Google Scholar 

  3. Davison, A., Hinkley, D.: Bootstrap Methods and their Application. Cambridge university Press (1997)

    Google Scholar 

  4. Efron, B., Tibshirani, R.: Introduction to the Bootstrap. Chapman & Hall (1993)

    Google Scholar 

  5. Fioshin, M.: Efficiency of resampling estimators of sequential-parallel systems reliability. In: Proc. of 2nd Int. Conf. on Simulation, Gaming, Training and Business Process Reengineering in Operations, Riga, pp. 112–117 (2000)

    Google Scholar 

  6. Fiosins, M., Fiosina, J., Müller, J., Görmer, J.: Reconciling strategic and tactical decision making in agent-oriented simulation of vehicles in urban traffic. In: Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques, pp. 144–151 (2011)

    Google Scholar 

  7. Gentle, J.E.: Elements of Computational Statistics. Springer (2002)

    Google Scholar 

  8. Li, Z., Chen, C., Wang, K.: Cloud computing for agent-based urban transportation systems. IEEE Intelligent Systems 26(1), 73–79 (2011)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jelena Fiosina .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Fiosina, J., Fiosins, M. (2013). Selecting the Shortest Itinerary in a Cloud-Based Distributed Mobility Network. In: Omatu, S., Neves, J., Rodriguez, J., Paz Santana, J., Gonzalez, S. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 217. Springer, Cham. https://doi.org/10.1007/978-3-319-00551-5_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00551-5_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00550-8

  • Online ISBN: 978-3-319-00551-5

  • eBook Packages: EngineeringEngineering (R0)