Abstract
Smart Space is a major currently challenging domain that includes ubiquitous, grid, and pervasive computing to provide intelligence, insight, and vision for emerging world of intelligent environment, products, services and human interaction. Smart Space consists of various objects (devices and applications) and, their extremely tight integration of and coordination between information world and physical resources. In Smart Space, people are allowed to acquire useful information and control devices anytime and anywhere with various smart devices. However the physical world where devices are deployed has much uncertainty and uncontrollable conditions, so that it is impossible to make devices suited to all situations. To achieve user satisfaction and overcome the system failure, devices in Smart Space must be dependable, secure, safe, and efficient, and operate in real-time. In addition, they must be scalable, cost-effective and adaptive. Especially, to deal with uncertainty and uncontrollable condition, devices in Smart Space could be more intelligent in the adaptation.
In this paper, we propose an agent-based self-adaptation architecture for implementing smart devices in Smart Space. A self-adaptive smart device reasons about its state and environment, and adapts itself at runtime automatically and dynamically in response to changes. Also we present an adaptation mechanism used to implementing a self-adaptive system.
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References
Chetan, S., Ranfanthan, A., & Campbell, R. (2005). Towards fault tolerant pervasive computing. IEEE Technology and Society, 24(1), 38–44.
Northrop, L., Feiler, P., Gabriel, R. P., Goodenough, J., Linger, R., Longstaff, T., et al. (2006). Ultra-large-scale systems: the software challenge of the future. Pittsburgh: Software Engineering Institute, Carnegie Mellon University.
Cheng, B. H., Lemos, R., Giese, H., Inverardi, P., Magee, J., Andersson, J., Becker, B., Bencomo, N., Brun, Y., Cukic, B., Serugendo, G. D. M., Dustdar, S., Finkelstein, A., Gacek, C., Geihs, K., Grassi, V., Karsai, G., Kienle, H. M., Kramer, J., Litoiu, M., Malek, S., Mirandola, R., Muller, H. A., Park, S., Shaw, M., Tichy, M., Tivoli, M., Weyns, D., & Whittle, J. (2009). Software engineering for self-adaptive systems: a research roadmap, software engineering for self-adaptive systems. In Lecture notes in computer science: Vol. 5525. (pp. 1–26). Berlin: Springer.
Laddaga, R. (1997). Self-adaptive software. Tech Rep. 98-12. DARPA BBA.
Salehie, M., & Tahvildari, L. (2009). Self-adaptive software: landscape and research challenges. ACM Transactions on Autonomous and Adaptive Systems, 4(2), 14.
Garlan, D., Cheng, S.-W., Huang, A.-C., Schmerl, B., & Steenkiste, P. (2004). Rainbow: architecture-based self-adaptation with reusable infrastructure. IEEE Computer, 37(10), 46–54.
Tuttle, S., Batchellor, V., Hansen, M. B., & Sethuraman, M. (2003). Centralized risk management using Tivoli risk manager (4.2 Tech. rep.). IBM Tivoli Software.
Candea, G., Kiciman, E., Kawamoto, S., & Fox, A. (2006). Autonomous recovery in componentized Internet applications. Cluster Computing, 9(1), 175–190.
Mukhija, A., & Glinz, M. (2005). Runtime adaptation of applications through dynamic recomposition of components. In Proceedings of the international conference on architecture of computing systems (pp. 124–138).
White, J., Schmidt, D. C., & Gokhale, A. S. (2005). Simplifying autonomic enterprise java bean applications via model-driven development: a case study. In Proceedings of the international conference on model driven engineering languages and systems (pp. 601–615). doi:10.1007/11557432_45
Lapouchnian, A., Liaskos, S., Mylopoulos, J., & Yu, Y. (2005). Towards requirements-driven autonomic systems design. In Proceedings of the workshop on design and evolution of autonomic app. software (pp. 1–7). doi:10.1145/1082983.1083075
Floch, J., Hallsteinsen, S., Stav, E., Eliassen, F., Lund, K., & Gjørven, E. (2006). Using architecture models for runtime adaptability. IEEE Software, 23(2), 62–70.
Kumar, V., Cooper, B., Cai, Z., Eisenhauer, G., & Schwan, K. (2007). Middleware for enterprise scale data stream management using utility-driven self-adaptive information flows. Cluster Computing, 10(4), 443–455.
Oreizy, P., Gorlick, M. M., Taylor, R. N., Heimbigner, D., Johnson, G., Medvidovic, N., Quilici, A., Rosenblum, D. S., & Wolf, A. L. (1999). An architecture-based approach to self-adaptive software. IEEE Intelligent Systems, 14(3), 54–62.
Kephart, J. O., & Chess, D. M. (2003). The vision of autonomic computing. IEEE Computer, 36(1), 41–50.
Robertson, P., & Laddaga, R. (2005). Model based diagnosis and contexts in self adaptive software. In Proceedings of the conference on self-* properties in complex information systems (pp. 112–127). doi:10.1007/11428589_8
De Lemos, R., & Fiadeiro, J. L. (2002). An architectural support for self-adaptive software for treating faults. In Proceedings of the workshop on self-healing systems (pp. 39–42). doi:10.1145/582128.582136
Sterritt, R., Parashar, M., Tianfield, H., & Unland, R. (2005). A concise introduction to autonomic computing. Advanced Engineering Informatics, 19, 181–187.
Burns, R. (2001). Advanced control engineering. Stoneham: Butterworth-Heinemann.
Astrom, K., & Wittenmark, B. (1995). Adaptive control (2nd edn.). Reading: Addison-Wesley.
Söderström, T., & Stoica, P. (1988). System identification. Englewood Cliffs: Prentice-Hall.
Astrom, K., & Wittenmark, B. (1995). Adaptive control (2nd edn.). Reading: Addison-Wesley.
Delgado, N., Gates, A. Q., & Roach, S. (2004). A taxonomy and catalog of runtime software-fault monitoring tools. IEEE Transactions on Software Engineering, 30(12), 859–870.
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Chun, I., Park, J., Lee, H. et al. An agent-based self-adaptation architecture for implementing smart devices in Smart Space. Telecommun Syst 52, 2335–2346 (2013). https://doi.org/10.1007/s11235-011-9547-8
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DOI: https://doi.org/10.1007/s11235-011-9547-8