Alocação de fatias de rede fim-a-fim para usuários móveis utilizando o simulador MobFogSim
Abstract
Network slicing has been presented as one promising technology for resource management in modern networks, e.g., 5G. Based on virtualisation technologies, network slicing creates different virtual networks over one common physical infrastructure. Simulators have been presented as one solution to evaluate new solutions in that context based on scalability, flexibility, and monetary aspects. MobFogSim was proposed to support the evaluation of solutions for resource management in fog computing environments, including service migration, network slicing, and support to users' mobility. This work introduces the new features of MobFogSim in terms of the simulator's scalability and support to end-to-end slices, which includes the management of Fog Nodes' processing and storage resources. Simulations based on realistic parameters show the impact of different slice allocation strategies in the slices' resource allocation as well as the improvements in the simulator's scalability.References
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Codeca, L., Frank, R., and Engel, T. (2015). Luxembourg SUMO Traffic (LuST) Scenario: 24 Hours of Mobility for Vehicular Networking Research. In IEEE Conference on Vehicular Networking (VNC), pages 1–8.
Ericsson (June 2021). Ericsson mobility report. https://www.ericsson.com/en/mobility-report.
Gonçalves, D., Puliafito, C., Mingozzi, E., Rana, O., Bittencourt, L., and Madeira, E. (2020). Dynamic network slicing in fog computing for mobile users in mobfogsim. In 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), pages 237–246. IEEE.
Gonçalves, D. M., Bittencourt, L. F., and Madeira, E. R. (2021). Fatiamento dinâmico de redes em computação em névoa para usuários móveis. In Anais do XXXIX Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 57–70. SBC.
Gupta, H., Vahid Dastjerdi, A., Ghosh, S. K., and Buyya, R. (2017). iFogSim: A Toolkit for Modeling and Simulation of Resource Management Techniques in the Internet of Things, Edge and Fog Computing Environments. Software: Practice and Experience, 47(9):1275–1296.
Lera, I., Guerrero, C., and Juiz, C. (2019). YAFS: A Simulator for IoT Scenarios in Fog Computing. IEEE Access, 7:91745–91758.
Lopes, M. M., Higashino, W. A., Capretz, M. A., and Bittencourt, L. F. (2017). Myi-FogSim: A Simulator for Virtual Machine Migration in Fog Computing. In ACM 6th International Workshop on Clouds and (eScience) Applications Management (CloudAM). Companion Proceedings of the 10th International Conference on Utility and Cloud Computing, pages 47–52.
Puliafito, C., Goncalves, D. M., Lopes, M. M., Martins, L. L., Madeira, E., Mingozzi, E., Rana, O., and Bittencourt, L. F. (2020). Mobfogsim: Simulation of mobility and migration for fog computing. Simulation Modelling Practice and Theory, 101:102062.
Qayyum, T., Malik, A. W., Khattak, M. A. K., Khalid, O., and Khan, S. U. (2018). Fog-NetSim++: A Toolkit for Modelling and Simulation of Distributed Fog Environment. IEEE Access, 6:63570–63583.
Scarpiniti, M., Baccarelli, E., and Momenzadeh, A. (2019). VirtFogSim: A Parallel Toolbox for Dynamic Energy-Delay Performance Testing and Optimization of 5G Mobile-Fog-Cloud Virtualized Platforms. MDPI Applied Sciences, 9(6).
Sonmez, C., Ozgovde, A., and Ersoy, C. (2018). EdgeCloudSim: An Environment for Performance Evaluation of Edge Computing Systems. Transactions on Emerging Telecommunications Technologies, 29(11).
Published
2022-05-23
How to Cite
GONÇALVES, Diogo M.; BITTENCOURT, Luiz F.; MADEIRA, Edmundo R. M..
Alocação de fatias de rede fim-a-fim para usuários móveis utilizando o simulador MobFogSim. In: BRAZILIAN SYMPOSIUM ON COMPUTER NETWORKS AND DISTRIBUTED SYSTEMS (SBRC), 40. , 2022, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 112-125.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2022.221973.
