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Mobility management in ubiquitous environments

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Abstract

Ubiquitous computing is aiming at providing users with intelligent human-centric context-aware services at anytime anywhere. However, mobility increases dynamism and uncertainty conditions. This study therefore explores the management and uses of various contexts for automatically providing appropriate services to individual users. This issue is explored from an open framework perspective referred to as ubiquitous gate (U-gate). In this framework, a distributed context management architecture and a communication model based on standard protocols are proposed. To fit user requirements and to achieve complete mobility management, a context-aware path planning mechanism (UbiPaPaGo) and a context-aware handoff mechanism (UbiHandoff) are proposed based on context stored in an open and distributed context management server U-gate. Based on the path planning results of UbiPaPaGo, UbiHandoff derives a minimum access point (AP) handoff plan that satisfies multiple QoS requirements for individual users and services. The UbiHandoff mechanism includes multiple-attribute decision making method (MADM)–based handoff planning, referred to as MADM-based UbiHandoff, and genetic algorithm (GA)–based handoff planning, referred to as GA-based UbiHandoff. In the proposed MADM-based UbiHandoff, analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) provide efficient and seamless AP handoff to gain higher QoS performance. In GA-based UbiHandoff, genetic algorithm is employed to minimize handoff by finding appropriate APs along the path under QoS constraints. Finally, the effectiveness of the proposed mechanisms is evaluated through simulations. Numerical results demonstrate that both mechanisms minimize handoffs and ensure compliance with QoS requirements.

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References

  1. Weiser M (1991) The computer for the twenty-first century. Sci Am 265:94–104 IEEE Pervasive Comput 2002:19–25

    Article  Google Scholar 

  2. Lu JH, Wang CY, Hwang RH (2009) An open framework for distributed context management in ubiquitous environment. International symposium on UbiCom frontiers—innovative research, systems and technologies (Ufirst) 88–93

  3. Wang CY, Hwang RH (2009) Context-aware path planning in ubiquitous network. Ubiquitous Intell Comput 5585:54–67

    Article  Google Scholar 

  4. Kettani D, Moulin B (1999) A spatial model based on the notions of spatial conceptual map and of object’s influence areas. Spat Inf Theory Cogn Comput Found Geogr Inf Sci 1661:401–416

    Google Scholar 

  5. Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Massachusetts

    MATH  Google Scholar 

  6. Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26

    Article  MATH  Google Scholar 

  7. Fahy P, Clarke S (2004) CASS—middleware for mobile context-aware applications. Mobile systems, applications, and services (Mobisys) workshop on context awareness, pp 304–308

  8. Chen H, Finin T, Joshi A (2003) An intelligent broker for context-aware system. Ubiquitous computing (Ubicomp), pp 183–184

  9. Chin CY, Zhang D, Gurusamy M (2005) Orion P2P-based inter-space context discovery platform. Mobile and ubiquitous systems: networking and services (MobiQuitous), pp 490–493

  10. Zhang D, Chin CY, Gurusamy M (2005) Supporting context-aware mobile service adaptation with scalable context discovery platform. Vehicular Technol Conf 5:2859–2863

    Google Scholar 

  11. Moon S, Kim J, Park D (2007) USD protocol- ubiquitous service discovery protocol on infrastructure-based architecture for ubiquitous fashionable computer. Multimedia and ubiquitous engineering, pp 779–784

  12. Tu J, Yang S (2003) Genetic algorithm based path planning for a mobile robot. Robot Autom 1:1221–1226

    Google Scholar 

  13. Castilho O, Trujilo L (2005) Multiple objective optimization genetic algorithms for path planning in autonomous mobile robots. Comput Syst Signals 6:48–63

    Google Scholar 

  14. Lei L, Wang H, Wu Q (2006) Improved genetic algorithms based path planning of mobile robot under dynamic unknown environment. Mechatronics and automation, pp 1728–1732

  15. Li Q, Zhang W, Yin Y, Zhang W, Liu G (2006) An improved genetic algorithm of optimum path planning for mobile robots. Intell Syst Des Appl 2:637–642

    Google Scholar 

  16. Li Q, Liu G, Zhang W, Zhao C, Yin Y, Wang Z (2006) A specific genetic algorithm for optimum path planning in intelligent transportation system. ITS Telecommunications, pp 140–143

  17. Arikan O, Chenney S, Forsyth DA (2001) Efficient multi-agent path planning. Eurographic workshop on computer animation and simulation, pp 151–162

  18. Wan TR, Chen H, Earnshaw R (2003) Real-time path planning for navigation in unknown environment. Theory and practice of computer graphics, pp 138–145

  19. Sigg S, Haseloff S, David K (2006) A novel approach to context prediction in ubicomp environments. Personal, indoor and mobile radio communications, pp 1–5

  20. Anagnostopoulos T, Anagnostopoulos C, Hadjiefthymiades S, Kalousis A, Kyriakakos M (2007) Path prediction through data mining. Pervasive services, pp 128–135

  21. Samaan N, Karmouch A (2005) A mobility prediction architecture based on contextual knowledge and spatial conceptual maps. IEEE Trans Mob Comput 4:537–551

    Article  Google Scholar 

  22. Ylianttila M, Pande M, Makela J, Mahonen P (2001) Optimization scheme for mobile users performing vertical handoffs between IEEE 802.11 and GPRS/EDGE networks. Global Telecommun Conf 6:3439–3443

    Google Scholar 

  23. Misra S, Banerjee A (2003) A novel load sensitive algorithm for AP selection in 4G networks. CODEC

  24. Du L, Bai Y, Chen L (2007) Access point selection strategy for large-scale wireless local area networks. Wireless communications and networking conference (WCNC), pp 2161–2166

  25. Bejerano Y, Han S, Li L (2004) Fairness and load balancing in wireless LANs using association control. Mobile computing and networking (Mobicom), pp 315–329

  26. Fukuda Y, Abe T, OIE Y (2004) Decentralized access point for wireless LANs. WTS

  27. Zhu F, McNair J (2004) Optimizations for vertical handoff decision algorithms. Wirel Commun Netw Conf 2:867–872

    Google Scholar 

  28. McNair J, Zhu F (2004) Vertical handoffs in fourth-generation multinetwork environments. Wirel Commun 11:8–15

    Article  Google Scholar 

  29. Wang H, Katz R, Giese J (1999) Policy-enabled handoffs across heterogeneous wireless networks. Workshop on mobile computing systems and applications (WMCSA), pp 51–60

  30. Ahmed T, Kyamakya K, Ludwig M (2006) A context-aware vertical handover decision algorithm for multimode mobile terminals and its performance. IEEE/ACM EATIS, pp 19–28

  31. Song Q, Jamalipour A (2005) Network Selection in an integrated wireless LAN ans UMTS environment using mathematical modeling and computing techniques. IEEE Wirel Commun Mag 12:42–49

    Article  Google Scholar 

  32. Song Q, Jamalipour A (2005) An adaptive quality-of-service network selection mechanism for heterogeneous mobile networks. Wirel Commun Mob Comput 5:697–708

    Article  Google Scholar 

  33. Balasubramaniam S, Indulska J (2003) Handovers between heterogeneous networks in pervasive systems. IEEE ICCT 2:1056–1059

    Google Scholar 

  34. Dhar J, Kiran SR, Reddy KY (2007) Network selection in heterogeneous wireless environment: a ranking algorithm. WCNC, pp 41–44

  35. Bari F, Leung Victor CM (2007) Automated network selection in a heterogeneous wireless network environment. IEEE Netw 21:34–40

    Article  Google Scholar 

  36. Jahanshahloo GR, Hosseinzadeh Lotfi F, Izadikhah M (2006) An algorithmic method to extend TOPSIS for decision-making problems with interval data. Applied mathematics and computation, pp 1375–1384

  37. Simple Service Discovery Protocol (SSDP), retrieved from ftp://ftp.pwg.org/pub/pwg/ipp/new_SSDP/draft-cai-ssdp-v1-03.txt

  38. SOAP version 1.2, retrieved from http://www.w3.org/TR/soap/

  39. General Event Notification Architecture (GENA), retrieved from http://tools.ietf.org/html/draft-cohen-gena-p-base-01

  40. CyberLink UPnP Library, retrieved from http://www.cybergarage.org/net/upnp/java/index.html

  41. Samaan N, Karmouch A (2005) A mobility prediction architecture based on contextual knowledge and spatial conceptual maps. IEEE Trans Mob Comput 4:537–551

    Article  Google Scholar 

  42. Inagaki J, Haseyama M, Kitajima H (1999) A genetic algorithm for determining multiple routes and its applications. IEEE International symposium (ISCAS), pp 137–140

  43. Poon WT, Chan E (2000) Traffic management in wireless ATM network using a hierarchical neural-network based predication algorithm. Computers and their applications, New Orleans, pp 5–8

  44. Yeniay Ö (2005) Penalty function methods for constrained optimization with genetic algorithms. J Math Comput Appl 10:45–56

    Google Scholar 

  45. Wan TR, Chen H, Earnshaw R (2003) Real-time path planning for navigation in unknown environment. Theory and practice of computer graphics, pp 138–145

  46. Fang SH, Lin TN, Lin PC (2008) Location fingerprinting in a decorrelated space. IEEE Trans Knowl Data Eng 20:658–691

    Google Scholar 

  47. Goldberg DE, Deb K (1991) A comparative analysis of selection schemes used in genetic algorithms. Foundation of genetic algorithms, pp 69–93

Download references

Acknowledgments

The research was supported by the NSC97-2221-E-194-011-MY3 and NSC97-2221 -E-194-012-MY3, National Science Council, ROC.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Chung-Cheng University, Chiayi County, Taiwan, Republic of China

    Chiung-Ying Wang, Hsiao-Yun Huang & Ren-Hung Hwang

  2. Department of Information Management, Transworld Institute of Technology, Yunlin, Taiwan, Republic of China

    Chiung-Ying Wang

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  1. Chiung-Ying Wang
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  2. Hsiao-Yun Huang
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Correspondence to Ren-Hung Hwang.

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Wang, CY., Huang, HY. & Hwang, RH. Mobility management in ubiquitous environments. Pers Ubiquit Comput 15, 235–251 (2011). https://doi.org/10.1007/s00779-010-0328-2

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