Skip to main content
SpringerLink
Log in

Situation Detection on the Edge

  • Conference paper
  • First Online:
Web, Artificial Intelligence and Network Applications (WAINA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 927))

  • 2607 Accesses

Abstract

Situation Awareness in edge computing devices is necessary for detecting issues that may hinder their computation capacity and reliability. The Situation Detection Mechanism presented in this paper uses Complex Event Processing in order to detect situations where the edge infrastructure requires an adaptation. We designed the Situation Detection Mechanism so as it is modular and can be easily deployed as a Docker container or a set of Docker containers. Moreover, we designed it to be independent of Complex Event Processing libraries and we have shown that it can operate with both the Siddhi and Drools libraries. We evaluated our work with a real-world scenario indicative of the usage of our component, and its capabilities.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
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. Adi, A., Etzion, O.: Amit - the situation manager. VLDB J. 13(2), 177–203 (2004)

    Article  Google Scholar 

  2. Amazon (2018). https://aws.amazon.com/autoscaling

  3. Chen, H., Finin, T., Joshi, A.: An ontology for context-aware pervasive computing environments. Knowl. Eng. Rev. 18(3), 197–207 (2004)

    Article  Google Scholar 

  4. Cohen, N.H., Lei, H., Castro, P., Davis II., J.S., Purakayastha, A.: Composing pervasive data using iQL. In: Proceedings of the Fourth IEEE Workshop on Mobile Computing Systems and Applications, WMCSA 2002, pp. 94–104 (2002)

    Google Scholar 

  5. Haghighi, P.D., Krishnaswamy, S., Zaslavsky, A., Gaber, M.M.: Reasoning about context in uncertain pervasive computing environments. In: Proceedings of the 3rd European Conference on Smart Sensing and Context, EuroSSC 2008, pp. 112–125. Springer, Heidelberg (2008)

    Google Scholar 

  6. Endsley, M.: Designing for Situation Awareness: An Approach to User-Centered Design, 2nd edn. CRC Press, Boca Raton (2016)

    Google Scholar 

  7. Franke, U., Brynielsson, J.: Cyber situational awareness - a systematic review of the literature. Comput. Secur. 46, 18–31 (2014)

    Article  Google Scholar 

  8. Google Cloud (2018). https://cloud.google.com/compute/docs/autoscaler/

  9. Gray, P.D., Salber, D.: Modelling and using sensed context information in the design of interactive applications. In: Proceedings of the 8th IFIP International Conference on Engineering for Human-Computer Interaction, EHCI 2001, pp. 317–336. Springer, London (2001)

    Google Scholar 

  10. Gu, T., Chen, S., Tao, X., Lu, J.: A non supervised approach to activity recognition and segmentation based on object-use fingerprints. Data Knowl. Eng. 69(6), 533–544 (2010)

    Article  Google Scholar 

  11. Kubernetes (2018). https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/

  12. Lei, H., Sow, D.M., John, S., Davis, I., Banavar, G., Ebling, M.R.: The design and applications of a context service. SIGMOBILE Mob. Comput. Commun. Rev. 6(4), 45–55 (2002)

    Article  Google Scholar 

  13. Loia, V., D’Aniello, G., Gaeta, A., Orciuoli, F.: Enforcing situation awareness with granular computing: a systematic overview and new perspectives. Granular Comput. 1(2), 127–143 (2016)

    Article  Google Scholar 

  14. Loke, S.W.: Incremental awareness and compositionality: a design philosophy for context-aware pervasive systems. Pervasive Mob. Comput. 6(2), 239–253 (2010)

    Article  Google Scholar 

  15. OpenStack (2018). https://docs.openstack.org/senlin/latest/scenarios/autoscaling_heat.html

  16. Ranganathan, A., Al-Muhtadi, J., Campbell, R.H.: Reasoning about uncertain contexts in pervasive computing environments. IEEE Pervasive Comput. 03(2), 62–70 (2004)

    Article  Google Scholar 

  17. Yau, S.S., Liu, J.: Hierarchical situation modeling and reasoning for pervasive computing. In: The Fourth IEEE Workshop on Software Technologies for Future Embedded and Ubiquitous Systems, SEUS 2006/WCCIA 2006, pp. 6-pp, April 2006

    Google Scholar 

  18. Ye, J., Dobson, S., McKeever, S.: Situation identification techniques in pervasive computing: a review. Pervasive Mob. Comput. 8(1), 36–66 (2012)

    Article  Google Scholar 

Download references

Acknowledgments

This work is partly funded by the H2020 PrestoCloud project–Proactive Cloud Resources Management at the Edge for Efficient Real-Time Big Data Processing (732339).

Author information

Authors and Affiliations

  1. National Technical University of Athens, 9 Iroon Polytechniou str., 157 80, Zografou, Athens, Greece

    Nikos Papageorgiou, Dimitris Apostolou, Yiannis Verginadis, Andreas Tsagkaropoulos & Gregoris Mentzas

  2. University of Piraeus, 80 Karaoli & Dimitriou str., 185 34, Piraeus, Greece

    Dimitris Apostolou

Authors
  1. Nikos Papageorgiou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dimitris Apostolou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yiannis Verginadis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andreas Tsagkaropoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gregoris Mentzas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dimitris Apostolou .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Advanced Sciences, Hosei University, Koganei-Shi, Tokyo, Japan

    Makoto Takizawa

  3. Department of Computer Science, Technical University of Catalonia, Barcelona, Barcelona, Spain

    Fatos Xhafa

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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

Papageorgiou, N., Apostolou, D., Verginadis, Y., Tsagkaropoulos, A., Mentzas, G. (2019). Situation Detection on the Edge. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_97

Download citation

Publish with us

Policies and ethics

Search

Navigation