Abstract
Context-aware systems are able to sense and adapt to the environment. Mobile applications can benefit from context-awareness since they incur to context changes during their execution. A detailed understanding of the context is needed to know what a context-aware system should sense and adapt to. This paper introduces a statistical approach that helps in determining contextual situations that require adaptation. The approach starts from monitoring mobile context variables values, modeling their states, and deducing from these models a Markov chain model, where each state represents a contextual situation. Depending on transition probabilities and system quality at each state we can decide when it is necessary to apply context-awareness.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
References
Abowd, G.D., Dey, A.K., Brown, P.J., Davies, N., Smith, M., Steggles, P.: Towards a better understanding of context and context-awareness. In: Gellersen, H.-W. (ed.) HUC 1999. LNCS, vol. 1707, pp. 304–307. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-48157-5_29
Abusair, M.: User- and analysis-driven context aware software development in mobile computing. In: ESEC/FSE 2017 Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, Paderborn, Germany, September 2017, pp. 1022–1025. ACM (2017)
Abusair, M., Di Marco, A., Inverardi, P.: An empirical approach for determining context of mobile systems. In: Proceedings of the 11th European Conference on Software Architecture: Companion Proceedings, pp. 71–77 (2017)
Abusair, M., Sharaf, M., Di Marco, A., Inverardi, P., Muccini, H.: An approach for developing context-aware mobile application. In: WomENcourage2019, Rome, Italy (2019)
Abusair, M., Sharaf, M., Muccini, H., Inverardi, P.: Adaptation for situational-aware cyber-physical systems driven by energy consumption and human safety. In: Proceedings of the 11th European Conference on Software Architecture: Companion Proceedings, pp. 78–84 (2017)
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). https://doi.org/10.1007/978-3-642-00593-0_9
Dey, A.K.: Providing architectural support for building context-aware applications. Ph.D. thesis, Georgia Institute of Technology (2000)
van Engelenburg, S., Janssen, M., Klievink, B.: Designing context-aware systems: a method for understanding and analysing context in practice. J. Log. Algebr. Methods Program. 103, 79–104 (2019). https://doi.org/10.1016/j.jlamp.2018.11.003. http://www.sciencedirect.com/science/article/pii/S2352220818300191
Eskins, D., Sanders, W.H.: The multiple-asymmetric-utility system model: a framework for modeling cyber-human systems. In: 2011 Eighth International Conference on Quantitative Evaluation of Systems (QEST), pp. 233–242. IEEE (2011)
Mikic-Rakic, M., Malek, S., Medvidovic, N.: Architecture-driven software mobility in support of QoS requirements. In: Proceedings of the 1st International Workshop on Software Architectures and Mobility, pp. 3–8. ACM (2008)
Muccini, H., Sharaf, M., Weyns, D.: Self-adaptation for cyber-physical systems: a systematic literature review. In: Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-managing Systems, pp. 75–81 (2016)
Ravi, N., Scott, J., Han, L., Iftode, L.: Context-aware battery management for mobile phones. In: Sixth Annual IEEE International Conference on Pervasive Computing and Communications, PerCom 2008, pp. 224–233. IEEE (2008)
Abusair, M., Di Marco, A., Inverardi, P.: Context-aware adaptation of mobile applications driven by software quality and user satisfaction. In: Proceedings of the 2017 IEEE International Conference on Software Quality, Reliability and Security Companion, Information Assurance Workshop, Prague, Czech Republic, July 2017 (2017)
Wang, D., Trivedi, K.S.: Modeling user-perceived service availability. In: Malek, M., Nett, E., Suri, N. (eds.) ISAS 2005. LNCS, vol. 3694, pp. 107–122. Springer, Heidelberg (2005). https://doi.org/10.1007/11560333_10
Wang, D., Trivedi, K.S.: Modeling user-perceived reliability based on user behavior graphs. Int. J. Reliab. Qual. Saf. Eng. 16(04), 303–329 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Abusair, M., Sharaf, M., Di Marco, A., Inverardi, P. (2020). A Statistical Approach for Context-Awareness of Mobile Applications. In: Muccini, H., et al. Software Architecture. ECSA 2020. Communications in Computer and Information Science, vol 1269. Springer, Cham. https://doi.org/10.1007/978-3-030-59155-7_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-59155-7_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-59154-0
Online ISBN: 978-3-030-59155-7
eBook Packages: Computer ScienceComputer Science (R0)