Proposal of a Load Balancing Architecture in Fog Computing environment

  • Eder Pereira UFSM
  • Roseclea D. Medina UFSM
  • Edson Luiz Padoin UNIJUI

Abstract


The Computing Mist is characterized as an extension of Cloud Computing and comes as a complement, filling gaps as lower response time and also less use of internet. This paper presents an architectural model of a load balancer computing environments in mist, whose objectives address the reduction of us mist overloaded and unbalanced as well, abstracting the end IoT device failures that occur in the nodes that comprise it. To prove the effectiveness of the proposed solution, it organized a simulation environment where ever compared to this work with some proposed solutions, and evaluated the proposed algorithm in heterogeneous computing environments. The results show that high-priority tasks consume the lowest possible response time in the environment or processing or in the queue, which raises the effectiveness of the proposed solution.

Keywords: Load Balancing for High Performance Systems, Cloud computing

References

Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., and Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE communications surveys & tutorials, 17(4):2347–2376.

Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pages 13–16. ACM.

Consortium, O. et al. (2017). Openfog reference architecture for fog computing. Architecture Working Group.

Pereira, E., Fischer, I. A., Medina, R. D., Carreno, E. D., and Padoin, E. L. (2019). A load balancing algorithm for fog computing environments. Latin America High Performance Computing Conference (CARLA), Costa Rica, pages 1–14.
Published
2020-04-15
PEREIRA, Eder; MEDINA, Roseclea D.; PADOIN, Edson Luiz. Proposal of a Load Balancing Architecture in Fog Computing environment. In: REGIONAL SCHOOL OF HIGH PERFORMANCE COMPUTING FROM SOUTHERN BRAZIL (ERAD-RS), 20. , 2020, Santa Maria. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 171-172. ISSN 2595-4164. DOI: https://doi.org/10.5753/eradrs.2020.10792.