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R&D challenges and solutions for mobile cyber-physical applications and supporting Internet services

Journal of Internet Services and Applications volume 1, pages45–56(2010)Cite this article

Abstract

The powerful processors and variety of sensors in new and planned mobile Internet devices, such as Apple’s iPhone and Android-based smartphones, can be leveraged to build cyber-physical applications that collect sensor data from the real world and communicate it back to Internet services for processing and aggregation. This article presents key R&D challenges facing developers of mobile cyber-physical applications that integrate with Internet services and summarizes emerging solutions to address these challenges. For example, application software should be architected to conserve power, which motivates R&D on tools that can predict the power consumption characteristics of mobile software architectures. Other R&D challenges involve the relative paucity of work on software and sensor data collection architectures that cater to the powerful capabilities and cyber-physical aspects of mobile Internet devices, which motivates R&D on architectures tailored to the latest mobile Internet devices.

References

  1. 1.

    Arisha K, Youssef M, Younis M (2002) Energy-aware TDMA-based MAC for sensor networks. In: IEEE IMPACCT, pp 21–40

  2. 2.

    Barisic D, Krogmann M, Stromberg G, Schramm P (2007) Making embedded software development more efficient with SOA. In: International conference on advanced information networking and applications workshops (AINAW). IEEE Computer Society, Los Alamitos, pp 941–946

    Google Scholar 

  3. 3.

    Benavides D, Trinidad P, Ruiz-Cortés A (2005) Automated reasoning on feature models. In: Advanced information systems engineering: 17th international conference, CAiSE 2005. LNCS, vol 3520. Springer, Berlin, pp 491–503

    Google Scholar 

  4. 4.

    Bohrer P, Elnozahy E, Keller T, Kistler M, Lefurgy C, McDowell C, Rajamony R (2002) The case for power management in web servers. In: Power aware computing, pp 261–289

  5. 5.

    Buyya R, Yeo C, Venugopal S (2008) Market-oriented cloud computing: vision, hype, and reality for delivering IT services as computing utilities. In: Proceedings of the 10th IEEE international conference on high performance computing and communications (HPCC-08). IEEE Comput Soc Press, Los Alamitos

    Google Scholar 

  6. 6.

    Clements P, Northrop L (2002) Software product lines: practices and patterns. Addison-Wesley, Boston

    Google Scholar 

  7. 7.

    de Deugd S, Carroll R, Kelly K, Millett B, Ricker J (2006) SODA: service-oriented device architecture. IEEE Pervasive Comput 5(3):94–96

    Article  Google Scholar 

  8. 8.

    Denton T, Jones E, Srinivasan S, Owens K, Buskens R (2008) NAOMI—an experimental platform for multi-modeling. In: Proceedings of MODELS, pp 143–157, Toulouse, France, October 2008

  9. 9.

    DPWS (2006) Devices profile for web services (DPWS). http://schemas.xmlsoap.org/ws/2006/02/devprof/

  10. 10.

    Fok C-L, Roman G-C, Lu C (2009) Enhanced coordination in sensor networks through flexible service provisioning. In: Field J, Vasconcelos VT (eds) Coordination models and languages (COORDINATION). Lecture notes in computer science, vol 5521. Springer, Berlin, pp 66–85

    Google Scholar 

  11. 11.

    Froehlich J, Dillahunt T, Klasnja P, Mankoff J, Consolvo S, Harrison B, Landay J (2009) UbiGreen: investigating a mobile tool for tracking and supporting Green transportation habits. In: Proceedings of the 27th international conference on human factors in computing systems. ACM, New York, pp 1043–1052

    Google Scholar 

  12. 12.

    Gay D, Levis P, Culler D (2007) Software design patterns for TinyOS. ACM Trans Embed Comput Syst 6(4):22

    Article  Google Scholar 

  13. 13.

    Henrysson A, Ollila M (2004) UMAR: ubiquitous mobile augmented reality. In: Proceedings of the 3rd international conference on Mobile and ubiquitous multimedia. ACM, New York, p 45

    Google Scholar 

  14. 14.

    Hill J, Schmidt DC, Slaby J, Porter A (2008) CiCUTS: combining system execution modeling tools with continuous integration environments. In: Proceedings of 15th annual IEEE international conference and workshops on the engineering of computer based systems (ECBS), Belfast, Northern Ireland, March 2008

  15. 15.

    Hoeller N, Reinke C, Neumann J, Groppe S, Boeckmann D, Linnemann V (2008) Efficient XML usage within wireless sensor networks. In: International conference on wireless Internet (WICON), pp 1–10. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)

  16. 16.

    Jones W (2001) Forecasting traffic flow. IEEE Spectr 38(1):90–91

    Article  Google Scholar 

  17. 17.

    Kang KC, Kim S, Lee J, Kim K, Shin E, Huh M (1998) FORM: a feature-oriented reuse method with domain-specific reference architectures. Ann Softw Eng 5(0):143–168

    Article  Google Scholar 

  18. 18.

    Leijdekkers P, Gay V (2006) Personal heart monitoring and rehabilitation system using smart phones. In: Proceedings of the international conference on mobile business, Citeseer, p 29

  19. 19.

    Levis P, Madden S, Gay D, Polastre J, Szewczyk R, Woo A, Brewer E, Culler D (2004) The emergence of networking abstractions and techniques in TinyOS. In: Proceedings of the first USENIX/ACM symposium on networked systems design and implementation (NSDI 2004)

  20. 20.

    Levis P, Patel N, Culler D, Shenker S (2004) Trickle: a self-regulating algorithm for code propagation and maintenance in wireless sensor networks. In: Proceedings of the first USENIX/ACM symposium on networked systems design and implementation (NSDI 2004), vol 246

  21. 21.

    Lindsey S, Raghavendra C (2002) PEGASIS: power-efficient gathering in sensor information systems. In: IEEE aerospace conference proceedings, vol 3

  22. 22.

    Mannion M (2002) Using first-order logic for product line model validation. In: Proceedings of the second international conference on software product lines, vol 2379, pp 176–187

  23. 23.

    Mitchell-Jackson J (2001) Energy needs in an Internet economy: a closer look at data centers. PhD thesis, Citeseer

  24. 24.

    Mohan P, Padmanabhan V, Ramjee R (2008) Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In: Proceedings of the 6th ACM conference on embedded network sensor systems. ACM, New York, pp 323–336

    Google Scholar 

  25. 25.

    Moritz G, Zeeb E, Prüter S, Golatowski F, Timmermann D, Stoll R (2009) Devices profile for web services in wireless sensor networks: adaptations and enhancements. In: International conference on emerging technologies and factory automation (ETFA). IEEE, New York

    Google Scholar 

  26. 26.

    Priyantha NB, Kansal A, Goraczko M, Zhao F (2008) Tiny web services: design and implementation of interoperable and evolvable sensor networks. In: International conference on embedded networked sensor systems (SenSys). ACM, New York, pp 253–266

    Google Scholar 

  27. 27.

    Rezgui A, Eltoweissy M (2007) Service-oriented sensor-actuator networks: promises, challenges, and the road ahead. Comput Commun 30(13):2627–2648

    Article  Google Scholar 

  28. 28.

    Rose G (2006) Mobile phones as traffic probes: practices, prospects, and issues. Transp Rev 26(3):275–291

    Article  Google Scholar 

  29. 29.

    Saponas T, Lester J, Froehlich J, Fogarty J, Landay J (2008) iLearn on the iPhone: real-time human activity classification on commodity mobile phones. University of Washington CSE Tech Report UW-CSE-08-04-02

  30. 30.

    Schmidt DC (2006) Model-driven engineering. IEEE Comput 39(2):25–31

    Article  Google Scholar 

  31. 31.

    Sztipanovits J (2007) Composition of cyber-physical systems. In: 14th annual IEEE international conference and workshops on the engineering of computer-based systems, ECBS’07, pp 3–6

  32. 32.

    Thompson C, White J, Dougherty B, Schmidt D (2009) Optimizing mobile application performance with model-driven engineering. In: Proceedings of the 7th IFIP workshop on software technologies for future embedded and ubiquitous systems

  33. 33.

    Varia J (2008) Cloud architectures. White Paper of Amazon, jineshvaria.s3.amazonaws.com/public/cloudarchitectures-varia.pdf

  34. 34.

    Villa D, Villanueva FJ, Moya F, Rincón F, Barba J, López JC (2009) Web services for deeply embedded extra low-cost devices. In: International conference on advances in grid and pervasive computing. Springer, Berlin, pp 400–409

    Google Scholar 

  35. 35.

    White J, Dougherty B, Schmidt DC (2008) Filtered Cartesian flattening: an approximation technique for optimally selecting features while adhering to resource constraints. In: Workshop on analysis of software product-lines at the international conference on software product-lines, October 2008

  36. 36.

    Zhang W, Jarzabek S (2005) Reuse without compromising performance: industrial experience from RPG software product line for mobile devices. Lect Notes Comput Sci 3714:57

    Article  Google Scholar 

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Author information

Affiliations

  1. Vanderbilt University, VU Station B #351679, Nashville, TN, 37235-1679, USA

    Jules White, Brian Dougherty, Chris Thompson & Douglas C. Schmidt

  2. School of Computer Science and Statistics, Trinity College, Dublin, 2, Ireland

    Siobhan Clarke & Christin Groba

Authors
  1. Jules White
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  2. Siobhan Clarke
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  3. Christin Groba
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  4. Brian Dougherty
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  5. Chris Thompson
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  6. Douglas C. Schmidt
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Correspondence to Jules White.

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White, J., Clarke, S., Groba, C. et al. R&D challenges and solutions for mobile cyber-physical applications and supporting Internet services. J Internet Serv Appl 1, 45–56 (2010). https://doi.org/10.1007/s13174-010-0004-9

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Keywords

  • Cyber-physical applications
  • Mobile computing
  • Sensor networks
  • Software product-lines
  • Model-driven engineering
  • Software architectures