BANCO DE DADOS PARA IOT
UMA ABORDAGEM ANALÍTICA SOBRE DESEMPENHO E EFICIÊNCIA
Palavras-chave:
Internet das Coisas (IoT), Bancos de Dados, Bancos de dados temporais, Desempenho, Escalabilidade
Resumo
O desenvolvimento de sistemas de Internet das Coisas (IoT) dependem da eficiência e escalabilidade dos bancos de dados que suportam as operações de coleta, armazenamento e processamento de dados. Este artigo propõem um framework e oferece uma análise comparativa entre três tipos principais de bancos de dados - relacionais, NoSQL e temporais - aplicados a ambientes IoT, com o objetivo de avaliar o desempenho e a adequação de cada tecnologia. Foram analisados estudos experimentais e abordagens que utilizaram diferentes métricas de desempenho. Os resultados indicam que bancos de dados temporais, como o InfluxDB, apresentam a melhor eficiência em termos de latência e taxa de ingestão para grandes volumes de dados IoT em tempo real.
Referências
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A. NOORZADEH, et al., "Scalability challenges in IoT systems: A systematic review," IEEE Internet of Things Journal, vol. 7, no. 12, pp. 11324-11334, 2024. doi: 10.1109/JIOT.2024.3111398.
A. P. PLAGERAS, et al., "Efficient big data management in cloud environments," Big Data Research, vol. 12, pp. 44–58, 2018. doi: 10.1016/j.bdr.2018.05.003.
A. S. TANENBAUM AND H. BOS, Modern Operating Systems, 4th ed., Pearson, 2014.
B. COSTA, et al., "Efficient Data Management in IoT Systems," Journal of Systems and Software, vol. 120, pp. 55–67, 2016. doi: 10.1016/j.jss.2016.03.003.
C. ORDONEZ, "Data Warehousing and Big Data Analytics for IoT," IEEE Internet of Things Journal, vol. 6, no. 1, pp. 297–306, 2019. doi: 10.1109/JIOT.2018.2879950.
D. VENKATESH, et al., "Temporal and Spatial Data in IoT Systems," IEEE Transactions on Big Data, vol. 7, no. 4, pp. 788-798, 2021. doi: 10.1109/TBDATA.2021.3090 874.
F. LACERDA, et al., "Analyzing IoT systems: Challenges in scalability and security," IEEE Communications Magazine, vol. 55, no. 10, pp. 48–54, 2015. doi: 10.1109/MCOM.2015.7321983.
KITCHENHAM, Barbara. (2004). Procedures for Performing Systematic Reviews. Keele, UK, Keele University. 33.
H. XU, et al., "Machine learning for database optimization in IoT," IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 5, pp. 2044–2056, 2021. doi: 10.1109/TKDE.2020.2985725.
J. LESKOVEC, A. RAJARAMAN, AND J. D. ULLMAN, Mining of Massive Datasets, 3rd ed., Cambridge University Press, 2020. doi: 10.1017/9781108644589.
L. MÉDINI, et al., "Challenges in IoT: Data quality and security," Sensors, vol. 17, no. 4, pp. 674–691, 2017. doi: 10.3390/s17040674.
M. AAQIB, et al., "IoT: Prospects and challenges in the age of ubiquitous connectivity," IEEE Access, vol. 11, pp. 1143–1152, 2023. doi: 10.1109/ACCESS.2023.307 1921.
M. STONEBRAKER, et al., "The Case for Time-Series Databases in IoT," ACM SIGMOD Record, vol. 44, no. 2, pp. 12–19, 2015. doi: 10.1145/2822932.2822937.
P. P. Ray, "A survey on Internet of Things architectures," Journal of King Saud University - Computer and Information Sciences, vol. 30, no. 3, pp. 291-319, 2018. doi: 10.1016/j.jksuci.2016.10.003.
P. VERMESAN and O. FRIESS, Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems, River Publishers, 2014. doi: 10.13052/rp-9788792982717.
R. HECHT, et al., "Optimizing Data Ingestion for IoT Applications: A Comparative Study of Relational, NoSQL, and Temporal Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 12, pp. 2301–2313, 2019. doi: 10.1109/TKDE.2019.291684 1.
R. JIMENEZ, et al., "Real-time IoT analytics using edge computing and temporal databases," IEEE Access, vol. 9, pp. 35891–35905, 2021. doi: 10.1109 /ACCESS.2021.3063992.
R. KIRAN and D. GOEL, "Integrating time-series databases in IoT systems: An empirical study," Internet Technology Letters, vol. 3, no. 2, pp. 122–131, 2020. doi: 10.1002/itl2.1045.
S. ZHANG, et al., "NoSQL databases for IoT applications: A comparative analysis," IEEE Transactions on Cloud Computing, vol. 9, no. 3, pp. 652–665, 2021. doi: 10.1109/TCC.2020.3041863.
Z. LI, et al., "Exploring the performance of NoSQL databases in IoT environments," Future Generation Computer Systems, vol. 92, pp. 475–490, 2019. doi: 10.1016/j.future.2018.10.014.
A. NOORZADEH, et al., "Scalability challenges in IoT systems: A systematic review," IEEE Internet of Things Journal, vol. 7, no. 12, pp. 11324-11334, 2024. doi: 10.1109/JIOT.2024.3111398.
A. P. PLAGERAS, et al., "Efficient big data management in cloud environments," Big Data Research, vol. 12, pp. 44–58, 2018. doi: 10.1016/j.bdr.2018.05.003.
A. S. TANENBAUM AND H. BOS, Modern Operating Systems, 4th ed., Pearson, 2014.
B. COSTA, et al., "Efficient Data Management in IoT Systems," Journal of Systems and Software, vol. 120, pp. 55–67, 2016. doi: 10.1016/j.jss.2016.03.003.
C. ORDONEZ, "Data Warehousing and Big Data Analytics for IoT," IEEE Internet of Things Journal, vol. 6, no. 1, pp. 297–306, 2019. doi: 10.1109/JIOT.2018.2879950.
D. VENKATESH, et al., "Temporal and Spatial Data in IoT Systems," IEEE Transactions on Big Data, vol. 7, no. 4, pp. 788-798, 2021. doi: 10.1109/TBDATA.2021.3090 874.
F. LACERDA, et al., "Analyzing IoT systems: Challenges in scalability and security," IEEE Communications Magazine, vol. 55, no. 10, pp. 48–54, 2015. doi: 10.1109/MCOM.2015.7321983.
KITCHENHAM, Barbara. (2004). Procedures for Performing Systematic Reviews. Keele, UK, Keele University. 33.
H. XU, et al., "Machine learning for database optimization in IoT," IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 5, pp. 2044–2056, 2021. doi: 10.1109/TKDE.2020.2985725.
J. LESKOVEC, A. RAJARAMAN, AND J. D. ULLMAN, Mining of Massive Datasets, 3rd ed., Cambridge University Press, 2020. doi: 10.1017/9781108644589.
L. MÉDINI, et al., "Challenges in IoT: Data quality and security," Sensors, vol. 17, no. 4, pp. 674–691, 2017. doi: 10.3390/s17040674.
M. AAQIB, et al., "IoT: Prospects and challenges in the age of ubiquitous connectivity," IEEE Access, vol. 11, pp. 1143–1152, 2023. doi: 10.1109/ACCESS.2023.307 1921.
M. STONEBRAKER, et al., "The Case for Time-Series Databases in IoT," ACM SIGMOD Record, vol. 44, no. 2, pp. 12–19, 2015. doi: 10.1145/2822932.2822937.
P. P. Ray, "A survey on Internet of Things architectures," Journal of King Saud University - Computer and Information Sciences, vol. 30, no. 3, pp. 291-319, 2018. doi: 10.1016/j.jksuci.2016.10.003.
P. VERMESAN and O. FRIESS, Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems, River Publishers, 2014. doi: 10.13052/rp-9788792982717.
R. HECHT, et al., "Optimizing Data Ingestion for IoT Applications: A Comparative Study of Relational, NoSQL, and Temporal Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 12, pp. 2301–2313, 2019. doi: 10.1109/TKDE.2019.291684 1.
R. JIMENEZ, et al., "Real-time IoT analytics using edge computing and temporal databases," IEEE Access, vol. 9, pp. 35891–35905, 2021. doi: 10.1109 /ACCESS.2021.3063992.
R. KIRAN and D. GOEL, "Integrating time-series databases in IoT systems: An empirical study," Internet Technology Letters, vol. 3, no. 2, pp. 122–131, 2020. doi: 10.1002/itl2.1045.
S. ZHANG, et al., "NoSQL databases for IoT applications: A comparative analysis," IEEE Transactions on Cloud Computing, vol. 9, no. 3, pp. 652–665, 2021. doi: 10.1109/TCC.2020.3041863.
Z. LI, et al., "Exploring the performance of NoSQL databases in IoT environments," Future Generation Computer Systems, vol. 92, pp. 475–490, 2019. doi: 10.1016/j.future.2018.10.014.
Publicado
2025-11-30
Como Citar
Dos Santos Pires, L. F. (2025). BANCO DE DADOS PARA IOT. Revista De Ubiquidade, 8(2), 23-38. Recuperado de https://revistas.anchieta.br/index.php/RevistaUbiquidade/article/view/2292
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