Model Reference Adaptive Control in Fuzzy-Based Context-Aware Middleware

Abstract Owing to the dynamic characteristics of mobile environments, a mobile application needs to adapt to changing contexts to improve performance and resource utilization. We have developed an adaptive middleware infrastructure that simultaneously satisfies the individual needs of applications while maintaining overall system performance. A Model Reference Adaptive Control mechanism has been implemented in the middleware using control theory and fuzzy-based techniques. With reference to the model reference adaptive control theory, we also present a Self-Adaptive Fuzzy-based Service Adaptation Model (SA-FSAM) by taking historical adaptation information into account, and utilizing a closed-loop control mechanism to fine-tune adaptation decisions. The SAFSAM and a conventional threshold-based linear-control model have been evaluated using a campus assistant mobile application. With the introduction of self-adaptive elements in the control model, the SA-FSAM shows significant improvements in service adapt...

[1]  Jiannong Cao,et al.  A fuzzy service adaptation engine for context-aware mobile computing middleware , 2008, Int. J. Pervasive Comput. Commun..

[2]  Jiannong Cao,et al.  Service adaptation using fuzzy theory in context-aware mobile computing middleware , 2005, 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'05).

[3]  Cecilia Mascolo,et al.  CARISMA: Context-Aware Reflective mIddleware System for Mobile Applications , 2003, IEEE Trans. Software Eng..

[4]  Jiannong Cao,et al.  A Fuzzy-Based Service Adaptation Middleware for Context-Aware Computing , 2006, EUC.

[5]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[6]  Guy A. Dumont,et al.  Concepts, methods and techniques in adaptive control , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[7]  Pramod K. Varshney,et al.  Adaptive online bandwidth allocation and reservation for QoS sensitive multimedia networks , 2005, Comput. Commun..

[8]  Cecilia Mascolo,et al.  Mobile Computing Middleware , 2002, NETWORKING Tutorials.

[9]  Klara Nahrstedt,et al.  Gaia: A Middleware Infrastructure to Enable Active Spaces1 , 2002 .

[10]  Klara Nahrstedt,et al.  A control-based middleware framework for quality-of-service adaptations , 1999, IEEE J. Sel. Areas Commun..

[11]  Y. M. Siu,et al.  CDMA mobile systems with tailor made power control to each mobile station , 2000 .

[12]  Ray E. Sheriff,et al.  Mobility management incorporating fuzzy logic for a heterogeneous IP environment , 2001, IEEE Commun. Mag..

[13]  Bin Qiu,et al.  The application of fuzzy prediction for the improvement of QoS performance , 1998, ICC '98. 1998 IEEE International Conference on Communications. Conference Record. Affiliated with SUPERCOMM'98 (Cat. No.98CH36220).

[14]  Klara Nahrstedt,et al.  A Middleware Infrastructure for Active Spaces , 2002, IEEE Pervasive Comput..

[15]  Jadwiga Indulska,et al.  A survey of context modelling and reasoning techniques , 2010, Pervasive Mob. Comput..

[16]  Jyh-Shing Roger Jang,et al.  Self-learning fuzzy controllers based on temporal backpropagation , 1992, IEEE Trans. Neural Networks.

[17]  Rogério de Lemos,et al.  Software Engineering for Self-Adaptive Systems [outcome of a Dagstuhl Seminar] , 2009, Software Engineering for Self-Adaptive Systems.

[18]  Jonathan J. Cadiz,et al.  Interaction Issues in Context-Aware Intelligent Environments , 2001, Hum. Comput. Interact..

[19]  Mary Shaw,et al.  Software Engineering for Self-Adaptive Systems: A Research Roadmap , 2009, Software Engineering for Self-Adaptive Systems.

[20]  Cho-Li Wang,et al.  Functionality adaptation: a context-aware service code adaptation for pervasive computing environments , 2003, Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003).

[21]  Witold Pedrycz,et al.  Analysis and synthesis of fuzzy systems by the use of probabilistic sets , 1983 .

[22]  H. Takagi.  Cooperative systems of neural networks and fuzzy logic and its applications , 1992, [1992] Conference Record of the Twenty-Sixth Asilomar Conference on Signals, Systems & Computers.

[23]  Terry Winograd,et al.  Architectures for Context , 2001, Hum. Comput. Interact..

[24]  Po-Rong Chang,et al.  Adaptive fuzzy power control for CDMA mobile radio systems , 1996 .

[25]  C. V. Altrock.  Fuzzy logic and neurofuzzy applications explained , 1995 .

[26]  Euiho Suh,et al.  Context-aware systems: A literature review and classification , 2009, Expert Syst. Appl..

[27]  P. Hanrahan,et al.  The Event Heap : An Enabling Infrastructure for Interactive Workspaces , 2000 .

[28]  Jiannong Cao,et al.  Dynamic service reconfiguration for wireless web access , 2003, WWW '03.

[29]  A. Robertson,et al.  Analysis and design of admission control in Web-server systems , 2003, Proceedings of the 2003 American Control Conference, 2003..

[30]  Song Liu,et al.  Load shedding in stream databases: a control-based approach , 2006, VLDB.

[31]  Murali Mani,et al.  Managing context for Internet videoconferences: the multimedia Internet recorder and archive , 1999, Electronic Imaging.

[32]  R. Cheung.  An adaptive middleware infrastructure incorporating fuzzy logic for mobile computing , 2005, International Conference on Next Generation Web Services Practices (NWeSP'05).

[33]  Context-Aware Computing,et al.  Reconfigurable Context- Sensitive Middleware for Pervasive Computing , 2002 .

[34]  Mary Shaw,et al.  Visibility of control in adaptive systems , 2008, ULSSIS '08.

[35]  George D. Magoulas,et al.  Perceptual, considerations in a QoS framework: a fuzzy logic formulation , 2001, 2001 IEEE Fourth Workshop on Multimedia Signal Processing (Cat. No.01TH8564).

[36]  Chung-Ju Chang,et al.  A QoS-guaranteed fuzzy channel allocation controller for hierarchical cellular systems , 2000, IEEE Trans. Veh. Technol..