Abstract
Applications in ubiquitous environments need to adapt to a range of fluid factors, like user preferences, context, and various system configurations. In this paper, we address the problem of system adaptation in order to continuously achieve high user benefit while keeping reconfiguration costs low. To this end, the presented approach leverages not only the immediate context but also future transitions. In contrast to existing approaches that either maximize benefit or minimize reconfiguration costs, our proposed decision support mechanism achieves a trade-off between those factors. Considering user preferences, deployment constraints, and probabilistic context state transitions, we propose a multi-objective utility function to determine the best reconfiguration choices. Experimental results show that the proposed approach achieves high user benefit while keeping reconfigurations costs low.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
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.
References
Andersson, J., de Lemos, R., Malek, S., Weyns, D.: Modeling dimensions of self-adaptive software systems. In: SEAMS, pp. 27–47 (2009)
Autili, M., Di Benedetto, P., Inverardi, P.: Context-aware adaptive services: The PLASTIC approach. In: Chechik, M., Wirsing, M. (eds.) FASE 2009. LNCS, vol. 5503, pp. 124–139. Springer, Heidelberg (2009)
Baldauf, M., Dustdar, S., Rosenberg, F.: A survey on context-aware systems. IJAHUC 2(4), 263–277 (2007)
Cheng, B.H.C., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds.): Software Engineering for Self-Adaptive Systems. LNCS, vol. 5525. Springer, Heidelberg (2009)
Cheng, S.-W., Poladian, V., Garlan, D., Schmerl, B.R.: Improving architecture-based self-adaptation through resource prediction. In: SEAMS, pp. 71–88 (2009)
Classen, A., Heymans, P., Schobbens, P.-Y.: What’s in a feature: A requirements engineering perspective. In: Fiadeiro, J.L., Inverardi, P. (eds.) FASE 2008. LNCS, vol. 4961, pp. 16–30. Springer, Heidelberg (2008)
Dorn, C., Dustdar, S.: Interaction-driven self-adaptation of service ensembles. In: Pernici, B. (ed.) CAiSE 2010. LNCS, vol. 6051, pp. 393–408. Springer, Heidelberg (2010)
Garlan, D., Cheng, S.-W., Huang, A.-C., Schmerl, B.R., Steenkiste, P.: Rainbow: Architecture-based self-adaptation with reusable infrastructure. IEEE Computer 37(10), 46–54 (2004)
Inverardi, P., Mori, M.: Feature oriented evolutions for context-aware adaptive systems. In: EVOL/IWPSE, pp. 93–97 (2010)
Kapitsaki, G.M., Prezerakos, G.N., Tselikas, N.D., Venieris, I.S.: Context-aware service engineering: A survey. JSS 82(8) (2009)
Keck, D., Kuehn, P.: The feature and service interaction problem in telecommunications systems: a survey. In: IEEE TSE (1998)
Krause, A., Smailagic, A., Siewiorek, D.P.: Context-aware mobile computing: Learning context-dependent personal preferences from a wearable sensor array. IEEE Trans. Mob. Comput. 5(2), 113–127 (2006)
Li, F., Rasch, K., Truong, H., Ayani, R., Dustdar, S.: Proactive service discovery in pervasive environments. In: ICPS, pp. 126–133 (2010)
Maia, P.H.M., Kramer, J., Uchitel, S., Mendonça, N.C.: Towards accurate probabilistic models using state refinement. In: ESEC/FSE, pp. 281–284 (2009)
Poladian, V., Garlan, D., Shaw, M., Satyanarayanan, M., Schmerl, B.R., Sousa, J.P.: Leveraging resource prediction for anticipatory dynamic configuration. In: SASO, pp. 214–223 (2007)
Poladian, V., Sousa, J.P., Garlan, D., Shaw, M.: Dynamic configuration of resource-aware services. In: ICSE, pp. 604–613 (2004)
Salehie, M., Tahvildari, L.: Self-adaptive software: Landscape and research challenges. TAAS 4(2) (2009)
Sykes, D., Heaven, W., Magee, J., Kramer, J.: Exploiting non-functional preferences in architectural adaptation for self-managed systems. In: SAC, pp. 431–438 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mori, M., Li, F., Dorn, C., Inverardi, P., Dustdar, S. (2011). Leveraging State-Based User Preferences in Context-Aware Reconfigurations for Self-Adaptive Systems. In: Barthe, G., Pardo, A., Schneider, G. (eds) Software Engineering and Formal Methods. SEFM 2011. Lecture Notes in Computer Science, vol 7041. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24690-6_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-24690-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24689-0
Online ISBN: 978-3-642-24690-6
eBook Packages: Computer ScienceComputer Science (R0)