Advertisement

Architectures Server-Centric vs Mobile-Centric for Developing WoT Applications

  • Javier BerrocalEmail author
  • Jose Garcia-Alonso
  • Juan Manuel Murillo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11496)

Abstract

The massive adoption of smart devices has fostered the development of Web of Things (WoT) applications. Due to the limited capabilities of these devices (some of them are battery powered, or the data exchange is limited), these applications have very stringent requirements. The success or failure of these applications largely depends on how they address these requirements, being the resource consumption a crucial one. Our experience has shown us that with different architectural styles we can obtain a similar behaviour, but the selected style directly impacts on the resource consumption. During the last few years, different frameworks, tools and activities have been proposed to estimate this consumption in early development phases in order to guide the decision making process. However, they are still not incorporated by the industry and researchers. This tutorial delves into different architectural styles that can be applied and what tools can be used to early estimate their consumption.

Keywords

Web of Things Web application development Mobile-centric Server-centric 

Notes

Acknowledgments

This work was supported by the Spanish Ministry of Science and Innovation through projects TIN2015-69957-R), by the Department of Economy and Infrastructure of the Government of Extremadura (GR18112, IB18030), and by the European Regional Development Fund and by 4IE project (0045-4IE-4-P) funded by the Interreg V-A España-Portugal (POCTEP) 2014-2020 program.

References

  1. 1.
    The OpenAPI Specification Repository. Contribute to OAI/OpenAPI-Specification development by creating an account on GitHub. https://github.com/OAI/OpenAPI-Specification
  2. 2.
    Hirsch, M., Rodriguez, J.M., Zunino, A., Mateos, C.: Battery-aware centralized schedulers for CPU-bound jobs in mobile grids. Pervasive Mob. Comput. 29(C), 73–94 (2016).  https://doi.org/10.1016/j.pmcj.2015.08.003CrossRefGoogle Scholar
  3. 3.
    Berrocal, J., Garcia-Alonso, J., Murillo, J.M.: Tool - early analysis of resource consumption patterns. https://api-consumptions.herokuapp.com
  4. 4.
    Berrocal, J., et al.: Early analysis of resource consumption patterns in mobile applications. Pervasive Mob. Comput. 35, 32–50 (2017)CrossRefGoogle Scholar
  5. 5.
    Crockford, D.: The application/JSON media type for Javascript object notation (JSON). Technical report (2006)Google Scholar
  6. 6.
    Guillén, J., Miranda, J., Berrocal, J., Garcia-Alonso, J., Murillo, J.M., Canal, C.: People as a service: a mobile-centric model for providing collective sociological profiles. IEEE Softw. 31(2), 48–53 (2014)CrossRefGoogle Scholar
  7. 7.
    Guinard, D., Trifa, V.: Building the Web of Things: With Examples in Node.Js and Raspberry Pi, 1st edn. Manning Publications Co., Greenwich (2016)Google Scholar
  8. 8.
    Qian, H., Andresen, D.: Extending mobile device’s battery life by offloading computation to cloud. In: Abadi, A., Dig, D., Dubinsky, Y. (eds.) 2015 2nd ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2015, Florence, Italy, May 16–17, 2015, pp. 150–151. IEEE (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Escuela Politécnica, Quercus Software Engineering GroupUniversity of ExtremaduraCáceresSpain

Personalised recommendations