Skip to main content
SpringerLink
Log in

On the Interplay Between Self-adaptation and Energy Efficiency

  • Conference paper
  • First Online:
Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023 (AISI 2023)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 184))

  • 331 Accesses

Abstract

Self-adaptation is an increasingly popular approach for enabling systems to make agile and data-driven decisions without human intervention. However, techniques for measuring the performance of a self-adaptive system and its effects on context are lacking. In this study, we present a mechanism that enables customizable and comprehensive evaluation of self-adaptive systems in real time. We apply our proposal to an example of resource management in a data center setting. We find that a self-adaptive approach to managing resources is multiple orders of magnitude better in terms of energy efficiency, especially as the size of the infrastructure grows, at the expense of slightly lower performance (\({<}10\%\)).

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. IBM: An architectural blueprint for autonomic computing, 4th edn. Technical Report G507-2065-00, IBM, 17 Skyline Drive, Hawthorne, NY 10532, USA (2006)

    Google Scholar 

  2. Gerostathopoulos, I., Vogel, T., Weyns, D., Lago, P.: How do we evaluate self-adaptive software systems?: a ten-year perspective of seams. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 59–70 (2021). https://doi.org/10.1109/SEAMS51251.2021.00018

  3. Kruliš, M., Bureš, T., Hnětynka, P.: Simdex: a simulator of a real self-adaptive job-dispatching system backend. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 167–173 (2022). https://doi.org/10.1145/3524844.3528078

  4. Frey, D., Kermarrec, A.-M., Maddock, C., Mauthe, A., Roman, P.-L., Taïani, F.: Similitude: decentralised adaptation in large-scale P2P recommenders. In: Distributed Applications and Interoperable Systems (DAIS), pp. 51–65 (2015)

    Google Scholar 

  5. Nundloll, V., Elkhatib, Y., Elhabbash, A., Blair, G.S.: An ontological framework for opportunistic composition of IoT systems. In: International Conference on Informatics, IoT, and Enabling Technologies (ICIoT), pp. 614–621 (2020)

    Google Scholar 

  6. Elhabbash, A., Nundloll, V., Elkhatib, Y., Blair, G.S., Sanz Marco, V.: An ontological architecture for principled and automated system of systems composition. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 85–95 (2020). https://doi.org/10.1145/3387939.3391602

  7. Wang, Z., Elkhatib, Y., Elhabbash, A.: HolonCraft - an architecture for dynamic construction of smart home workflows. In: Conference on Future Internet of Things and Cloud (FiCloud), pp. 213–220 (2022). https://doi.org/10.1109/FiCloud57274.2022.00036

  8. Elhabbash, A., Elkhatib, Y., Bouloukakis, G., Salama, M.: A middleware for automatic composition and mediation in IoT systems. In: International Conference on the Internet of Things (IoT), pp. 127–134 (2022). https://doi.org/10.1145/3567445.3567451

  9. Najafizadegan, N., Nazemi, E., Khajehvand, V.: A MAPE-K loop based model for virtual machine consolidation in cloud data centers. J. Comput. Robot. 13(2), 33–60 (2020)

    Google Scholar 

  10. Elhabbash, A., Elkhatib, Y.: Energy-aware placement of device-to-device mediation services in IoT systems. In: Hacid, H., Kao, O., Mecella, M., Moha, N., Paik, H. (eds.) ICSOC 2021. LNCS, vol. 13121, pp. 335–350. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-91431-8_21

    Chapter  Google Scholar 

  11. Sliem, M., Salmi, N., Ioualalen, M.: Performance analysis of self-adaptive policies in containerized microservices. In: International Conference on Engineering and Emerging Technologies (ICEET) (2021). https://doi.org/10.1109/ICEET53442.2021.9659601

  12. Cheng, S.-W., Garlan, D., Schmerl, B.: Evaluating the effectiveness of the rainbow self-adaptive system. In: ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 132–141 (2009). https://doi.org/10.1109/SEAMS.2009.5069082

  13. Whittle, J., Sawyer, P., Bencomo, N., Cheng, B.H.C., Bruel, J.-M.: RELAX: incorporating uncertainty into the specification of self-adaptive systems. In: International Requirements Engineering Conference (RE), pp. 79–88 (2009). https://doi.org/10.1109/RE.2009.36

  14. Elkhodary, A., Esfahani, N., Malek, S.: FUSION: a framework for engineering self-tuning self-adaptive software systems. In: Symposium on Foundations of Software Engineering (FSE), pp. 7–16. ACM, New York (2010). https://doi.org/10.1145/1882291.1882296

  15. Elhabbash, A., Bahsoon, R., Tino, P.: Self-awareness for dynamic knowledge management in self-adaptive volunteer services. In: International Conference on Web Services (ICWS), pp. 180–187 (2017). https://doi.org/10.1109/ICWS.2017.31

  16. Tamura, G., Villegas, N.M., Muller, H.A., Duchien, L., Seinturier, L.: Improving context-awareness in self-adaptation using the DYNAMICO reference model. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 153–162 (2013). https://doi.org/10.1109/SEAMS.2013.6595502

  17. Becker, M., Becker, S., Meyer, J.: SimuLizar: design-time modeling and performance analysis of self-adaptive systems. In: Kowalewski, S., Rumpe, B. (eds.) Software Engineering, pp. 71–84. Gesellschaft für Informatik e.V, Bonn (2013)

    Google Scholar 

  18. Tallabaci, G., Silva Souza, V.E.: Engineering adaptation with Zanshin: an experience report. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 93–102 (2013). https://doi.org/10.1109/SEAMS.2013.6595496

  19. Sobhy, D., Minku, L., Bahsoon, R., Chen, T., Kazman, R.: Run-time evaluation of architectures: a case study of diversification in IoT. J. Syst. Software 159 (2020) https://doi.org/10.1016/j.jss.2019.110428

  20. Kit, M., Gerostathopoulos, I., Bures, T., Hnetynka, P., Plasil, F.: An architecture framework for experimentations with self-adaptive cyber-physical systems. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 93–96 (2015)

    Google Scholar 

  21. Schmid, S., Gerostathopoulos, I., Prehofer, C., Bures, T.: Self-adaptation based on big data analytics: A model problem and tool. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 102–108 (2017). https://doi.org/10.1109/SEAMS.2017.20

  22. Villegas, N., Müller, H., Tamura, G., Duchien, L., Casallas, R.: A framework for evaluating quality-driven self-adaptive software systems. In: Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), pp. 80–89 (2011). https://doi.org/10.1145/1988008.1988020

  23. Silva, M.B., Bezerra, C., Coutinho, E., Maia, P.H.: A catalog of performance measures for self-adaptive systems. In: The Brazilian Symposium on Software Quality (SBQS). ACM, New York (2021). https://doi.org/10.1145/3493244.3493259

Download references

Acknowledgement

This work was partly supported by the UK EPSRC under grant number EP/R010889/2.

Author information

Authors and Affiliations

  1. School of Computing Science, University of Glasgow, Glasgow, UK

    Soyaba Hasan & Yehia Elkhatib

Authors
  1. Soyaba Hasan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yehia Elkhatib
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yehia Elkhatib .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Cairo University, Giza, Egypt

    AboulElla Hassanien

  2. Port Said University, Port Fouad City, Egypt

    Rawya Y. Rizk

  3. Department of Operations Research and Statistics, The University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia

    Dragan Pamucar

  4. Faculty of Science, Helwan University, Cairo, Egypt

    Ashraf Darwish

  5. Shulin District, Fujian University of Technology, New Taipei, Taiwan

    Kuo-Chi Chang

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Hasan, S., Elkhatib, Y. (2023). On the Interplay Between Self-adaptation and Energy Efficiency. In: Hassanien, A., Rizk, R.Y., Pamucar, D., Darwish, A., Chang, KC. (eds) Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023. AISI 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 184. Springer, Cham. https://doi.org/10.1007/978-3-031-43247-7_12

Download citation

Publish with us

Policies and ethics

Search

Navigation