Skip to main content

Method for Modeling and Simulation of Parallel Data Integration Processes in Wireless Sensor Networks

  • Conference paper
  • First Online:
Book cover Flexible Query Answering Systems (FQAS 2019)

Abstract

The parallel sensor data integration local processing in Wireless Sensor Networks (WSNs) is one of the possible solutions to reduce the neighbor sensor node’s communication and to save energy. At the same time, the process of local sensor node integration needs an additional processor and energy resources. Therefore the development of a realistic and reliable model of data integration processes in WSNs is critical in many aspects. The proposed GN based method and the related modeling process covers most of the aspects of the parallel sensor data integration in the WSN’s, based on 802.15.4 protocols. For simulation and analysis tool is used the WSNet simulator and some additional software libraries.

The article presents a new method for modeling and simulation of sensor data integration parallel processing in WSNs. The proposed method uses modeling based on the Generalized Nets (GN) approach which is a new and an advanced way of parallel data processing analysis of Wireless Sensor Systems (WSS).

This paper is supported by the National Scientific Program “Information and Communication Technologies for a Single Digital Market in Science, Education and Security (ICTinSES)”, financed by the Ministry of Education and Science.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Atanassov, K.: Generalized Nets. World Scientific, Singapore (1991)

    Book  Google Scholar 

  2. Fidanova, S., Atanasov, K., Marinov, P.: Generalized Nets and Ant Colony Optimization. Prof. Marin Drinov Academic Publishing House, Sofia (2011). ISBN 978-954-322-473-9

    Google Scholar 

  3. Sotirov, S., Atanasov, K.: Generalized Nets and Supervised Neural Networks. Prof. Marin Drinov Academic Publishing House, Sofia (2011). ISBN 978-954-322-623-8

    Google Scholar 

  4. Doukovska, L., Atanassova, V., Shahpazov, G., Sotirova, E.: Generalized net model of the creditworthiness financial support mechanism for the SMEs. Int. J. Comput. Inform. (2016). ISSN 1335–9150

    Google Scholar 

  5. Balabanov, T., Sevova, J., Kolev, K.: Optimization of string rewriting operations for 3D fractal generation with genetic algorithms. In: Nikolov, G., Kolkovska, N., Georgiev, K. (eds.) NMA 2018. LNCS, vol. 11189, pp. 48–54. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-10692-8_5

    Chapter  Google Scholar 

  6. Alexandrov, A., Monov, V.: Method for adaptive node clustering in AD HOC wireless sensor networks. In: Vishnevskiy, V.M., Kozyrev, D.V. (eds.) DCCN 2018. CCIS, vol. 919, pp. 257–263. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99447-5_22

    Chapter  Google Scholar 

  7. Hall, D.L., Llinas, J.: An introduction to multisensor data fusion. Proc. IEEE 85(1), 6–23 (1997)

    Article  Google Scholar 

  8. Durrant-Whyte, H.F., Stevens, M.: Data fusion in decentralized sensing networks. In: Proceedings of the 4th International Conference on Information Fusion, Montreal, Canada, pp. 302–307 (2001)

    Google Scholar 

  9. Tcheshmedjiev, P.: Synchronizing parallel processes using generalized nets, NT. J. “Bioautom.” 14(1), 69–74 (2010)

    Google Scholar 

  10. Atanasova T.: Modelling of complex objects in distance learning systems. In: Proceedings of the First International Conference - “Innovative Teaching Methodology”, Tbilisi, Georgia, 25–26 October 2014, pp. 180–190 (2014). ISBN 978-9941-9348-7-2

    Google Scholar 

  11. Alexandrov, A.: Ad-hoc Kalman filter based fusion algorithm for real-time wireless sensor data integration. In: Andreasen, T., et al. (eds.) Flexible Query Answering Systems 2015. AISC, vol. 400, pp. 151–159. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-26154-6_12

    Chapter  Google Scholar 

  12. Luo, R.C., Yih, C.-C., Su, K.L.: Multisensor fusion and integration: approaches, applications, and future research directions. IEEE Sens. J. 2(2), 107–119 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexander Alexandrov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Alexandrov, A. et al. (2019). Method for Modeling and Simulation of Parallel Data Integration Processes in Wireless Sensor Networks. In: Cuzzocrea, A., Greco, S., Larsen, H., Saccà, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2019. Lecture Notes in Computer Science(), vol 11529. Springer, Cham. https://doi.org/10.1007/978-3-030-27629-4_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27629-4_27

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27628-7

  • Online ISBN: 978-3-030-27629-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics