Modelagem e Simulação de Offloading para Computação Móvel em Nuvem

  • Luis Sérgio da Silva Jr. UFC/GREat
  • Deborah Magalhães UFC/GREat
  • Danielo Gomes UFC/GREat

Abstract


Mobile Cloud Computing (MCC) uses cloud services to spread out the energy and computing resources of mobile devices. Despite these devices have grown in use, we observe a lack of models and simulation tools to study and analyse mobile devices resource limitation using cloud computing as solution. In this paper, we model a typical MCC architecture which focuses on an offloading perspective. Our model provides a development environment to validate offloading strategies without using a real cloud infrastructure. To validate our approach, we simulate the execution time of a task on a local (mobile device) and in a remote cloud. Results show that our models represent MCC scenarios with an maximum accuracy of 98.9%. Moreover, we verified the workload algorithm complexity impacts on the offloading decisions.

References


Ahmed, A. e Sabyasachi, A. (2014). Cloud computing simulators: A detailed survey and future direction. In Advance Computing Conference (IACC), 2014 IEEE International, pages 866–872.

Calheiros, R. N., Ranjan, R., Beloglazov, A., De Rose, C. A. F., and Buyya, R. (2011). Cloudsim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw. Pract. Exper., 41(1):23–50.

Chun, B.-G., Ihm, S., Maniatis, P., Naik, M., and Patti, A. (2011). Clonecloud: Elastic execution between mobile device and cloud. In Proceedings of the Sixth Conference on Computer Systems, EuroSys ’11, pages 301–314, New York, NY, USA. ACM.

Costa, P. B., Rego, P. A. L., Coutinho, E. F., Trinta, F. A. M., and de Souza, J. N. (2014). Uma análise do impacto da qualidade da internet móvel na utilização de cloudlets. In Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2014), pages 223–236, Florianópolis. SBC.

Cuervo, E., Balasubramanian, A., Cho, D.-k., Wolman, A., Saroiu, S., Chandra, R., and Bahl, P. (2010). Maui: Making smartphones last longer with code offload. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, MobiSys ’10, pages 49–62, New York, NY, USA. ACM.

Dinh, H. T., Lee, C., Niyato, D., and Wang, P. (2013). A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing.

Fernando, N., Loke, S. W., and Rahayu, W. (2013). Mobile cloud computing: A survey. Future Gener. Comput. Syst., 29(1):84–106.

Justino, T. and Buyya, R. (2014). Outsourcing resource-intensive tasks from mobile apps to clouds: Android and aneka integration. In Cloud Computing in Emerging Markets (CCEM), 2014 IEEE International Conference on, pages 1–8.

Kumar, K., Liu, J., Lu, Y.-H., and Bhargava, B. (2013). A survey of computation offloading for mobile systems. Mob. Netw. Appl., 18(1):129–140.

Li, J., Bu, K., Liu, X., and Xiao, B. (2013). Enda: Embracing network inconsistency for dynamic application offloading in mobile cloud computing. In Proceedings of the Second ACM SIGCOMM Workshop on Mobile Cloud Computing, MCC ’13, pages 39–44, New York, NY, USA. ACM.

Mell, P. and Grance, T. (2011). The nist definition of cloud computing. Technical Report 800-145, National Institute of Standards and Technology (NIST), Gaithersburg, MD.

Qi and Gani, A. (2012). Research on mobile cloud computing: Review, trend and perspectives. In Digital Information and Communication Technology and it’s Applications (DICTAP), 2012 Second International Conference on, pages 195–202.

Satyanarayanan, M., Bahl, P., Caceres, R., and Davies, N. (2009). The case for vm-based cloudlets in mobile computing. IEEE Pervasive Computing, 8(4):14–23.

Published
2015-07-20
DA SILVA JR., Luis Sérgio; MAGALHÃES, Deborah; GOMES, Danielo. Modelagem e Simulação de Offloading para Computação Móvel em Nuvem. In: PROCEEDINGS OF BRAZILIAN SYMPOSIUM ON UBIQUITOUS AND PERVASIVE COMPUTING (SBCUP), 7. , 2015, Recife. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2015 . p. 91-100. ISSN 2595-6183. DOI: https://doi.org/10.5753/sbcup.2015.10172.