Implications of HCI in Energy Consumption Between Native and Rich-Client Applications for Navigations Widgets in Tablets

  • Ana Belem Márquez QuintosEmail author
  • Amilcar Meneses Viveros
  • Erika Hernández Rubio
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 529)


The mobile platforms could be classified among those using virtual machine and that not use to run native apps. A native app is developed in a specific way for an specific mobile platform. The Rich-Client Applications are structured multilayer form. Developers and users have the problem of working with the constraints of mobile devices such as the energy consumption. The developers have tried to do user-centered designs. Analyzes have been conducted to justify the feasibility of developing mobile device applications natively or rich-client. This paper presents a comparative study of navigation widget in rich-client applications against native iOS and Android applications is presented. The results presented do not make a quantitative comparison between native iOS and Android applications.


Mobile Device Virtual Machine Energy Saving Mobile Platform Multicore Processor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Koerber, T.: Lets talk about android-observations on competition in the field of mobile operating systems (2014). SSRN 2462393Google Scholar
  2. 2.
    Hernandez, I.M.T., Viveros, A.M., Rubio, E.H.: Analysis for the design of open applications on mobile devices. In: International Conference on Electronics, Communications and Computing (CONIELECOMP) 2013, PP. 126–131. IEEE (2013)Google Scholar
  3. 3.
    Robinson, S.: Cellphone energy gap: desperately seeking solutions. Strategy Analytics (2009)Google Scholar
  4. 4.
    Heikkinen, M.V., Nurminen, J.K., Smura, T., Hämmäinen, H.: Energy efficiency of mobile handsets: measuring user attitudes and behavior. Telematics Inform. 29(4), 387–399 (2012)CrossRefGoogle Scholar
  5. 5.
    Kumar, K., Liu, J., Lu, Y.H., Bhargava, B.: A survey of computation offloading for mobile systems. Mobile Netw. Appl. 18(1), 129–140 (2013)CrossRefGoogle Scholar
  6. 6.
    Thiagarajan, N., Aggarwal, G., Nicoara, A., Boneh, D., Singh, J.P.: Who killed my battery?: analyzing mobile browser energy consumption. In: Proceedings of the 21st International Conference on World Wide Web, pp. 41–50. ACM (2012)Google Scholar
  7. 7.
    Carroll, A., Heiser, G.: An analysis of power consumption in a smartphone. In: USENIX Annual Technical Conference, pp. 271–285 (2010)Google Scholar
  8. 8.
    Yuan, W., Nahrstedt, K.: Energy-efficient soft real-time cpu scheduling for mobile multimedia systems. ACM SIGOPS Opera. Syst. Rev. 37(5), 149–163 (2003)CrossRefzbMATHGoogle Scholar
  9. 9.
    Cuervo, E., Balasubramanian, A., Cho, D.k., Wolman, A., Saroiu, S., Chandra, R., Bahl, P.: Maui: making smartphones last longer with code offload. In: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, pp. 49–62. ACM (2010)Google Scholar
  10. 10.
    Hong, Y.J., Kumar, K., Lu, Y.H.: Energy efficient content-based image retrieval for mobile systems. In: IEEE International Symposium on Circuits and Systems 2009, ISCAS 2009, pp. 1673–1676. IEEE (2009)Google Scholar
  11. 11.
    Carroll, A., Heiser, G.: Unifying DVFS and offlining in mobile multicores. In: IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), Berlin, April 2014Google Scholar
  12. 12.
    Mittal, R., Kansal, A., Chandra, R.: Empowering developers to estimate app energy consumption. In: Proceedings of the 18th Annual International Conference on Mobile Computing and Networking, pp. 317–328. ACM (2012)Google Scholar
  13. 13.
    Looga, V., Xiao, Y., Ou, Z., Yla-Jaaski, A.: Exploiting traffic scheduling mechanisms to reduce transmission cost on mobile devices. In: Wireless Communications and Networking Conference (WCNC), Paris, Abril 1–4, pp. 1766–1770. IEEE (2012)Google Scholar
  14. 14.
    Rahmati, A., Zhong, L.: Human-battery interaction on mobile phones. Pervasive Mob. Comput. 5(5), 465–477 (2009)CrossRefGoogle Scholar
  15. 15.
    Rice, A., Hay, S.: Measuring mobile phone energy consumption for 802.11 wireless networking. Pervasive Mob. Comput. 6(6), 593–606 (2010)CrossRefGoogle Scholar
  16. 16.
    Perrucci, G.P., Fitzek, F.H., Widmer, J.: Survey on energy consumption entities on the smartphone platform. In: 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), Budapest, Hungary, pp. 1–6. IEEE, May 2011Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ana Belem Márquez Quintos
    • 1
    Email author
  • Amilcar Meneses Viveros
    • 1
  • Erika Hernández Rubio
    • 2
  1. 1.Departamento de ComputaciónCINVESTAV-IPNMéxico D.F.Mexico
  2. 2.SEPI-ESCOMInstituto Politécnico NacionalMéxico D.F.Mexico

Personalised recommendations