Detecção e Monitoramento de Anomalias em Data Centers Através de Análise Acústica: Abordagens e Direções Futuras
Resumo
A crescente complexidade das infraestruturas de Tecnologia da Informação, especialmente em data centers, tem ampliado a necessidade de monitoramento contínuo que considere não apenas aspectos computacionais, mas também fatores ambientais que impactam sua operação. Nesse contexto, ruídos e sons gerados pelos equipamentos emergem como uma fonte relevante de informação sobre o estado funcional da infraestrutura. Este mapeamento sistemático tem como objetivo identificar, organizar e analisar estudos que exploram o uso de sinais acústicos em ambientes de data centers, com foco em aplicações voltadas ao monitoramento e à detecção de anomalias. O trabalho também investiga a evolução das pesquisas, as principais técnicas e metodologias adotadas, bem como identifica lacunas e oportunidades na literatura. Ao sistematizar essas evidências, o mapeamento contribui para delinear o estado atual do conhecimento e para situar a análise acústica como uma fonte complementar de informação no monitoramento de infraestruturas críticas de TI.Referências
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Ahmed, S., Ahsan, M., Hadi, F., Ahmed, I., and Khan, A. (2017). A novel noise-measuring system based on wsn. In 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT), pages 1–6.
Akabane, A. T., Immich, R., Pazzi, R. W., Madeira, E. R. M., and Villas, L. A. (2018). Trusted: A distributed system for information management and knowledge distribution in vanets. In 2018 IEEE Symposium on Computers and Communications (ISCC), pages 1–6.
Alnuaimy, Ahmed, Shushurab, O., and Zhyrovc, G. (2022). Impact of noise inside server room.
Alves, D., Dalmazo, B., Riker, A., Filho, G. R., and Immich, R. (2025). Prevenção e detecção de intrusões em redes iot: Um mapeamento sistemático de soluções na borda e na nuvem. In Anais do XVII Simpósio Brasileiro de Computação Ubíqua e Pervasiva, pages 111–120, Porto Alegre, RS, Brasil. SBC.
Bittencourt, L., Immich, R., Sakellariou, R., Fonseca, N., Madeira, E., Curado, M., Villas, L., DaSilva, L., Lee, C., and Rana, O. (2018). The internet of things, fog and cloud continuum: Integration and challenges. Internet of Things, 3-4:134 – 155.
Buchinger, D., de Siqueira Cavalcanti, G. A., and da Silva Hounsell, M. (2014). Mecanismos de busca acadêmica: uma análise quantitativa. Revista Brasileira de Computação Aplicada, 6(1):108–120.
Campbell, K., Lawey, A., and Razavi, M. (2025). Quantum data centres: a simulation-based comparative noise analysis. Quantum Science and Technology, 10(1). Cited by: 1; All Open Access, Green Open Access, Hybrid Gold Open Access.
Chen, Z., Xiang, J., Xiang, M., Fu, S., and Qin, Y. (2025). Deep neural network-based joint monitoring of carrier-to-signal power ratio (cspr) and optical signal-to-noise ratio (osnr) for directly detected optical single-sideband transmission. Opt. Express, 33(6):12375–12388.
Chowdhury, U., Rodriguez, J., Tradat, M., Soud, Q., Wallace, S., O”Brien, D., Hambruch, S., Heydari, A., Radmard, V., and Shahi, P. (2024). Acoustics analysis of air and hybrid cooled data center. In 2024 23rd IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), pages 1–11.
Garcia-Mora, D. M., Garcia-Garcia, D., Yahyaei-Moayyed, F., Cinco-Galicia, J. C., Sanchez-Ortiz, C. R., and Sala, C. A. (2016). Filter design methodology for low noise power domains in datacenter platforms. In 2016 IEEE MTT-S Latin America Microwave Conference (LAMC), pages 1–3.
Ge, C., Chen, X., Wang, M., and Wang, J. (2022). Deep baseline network for time series modeling and anomaly detection. page 1137 – 1142. Cited by: 0.
Islam, M. A., Yang, L., Ranganath, K., and Ren, S. (2018). Why some like it loud: Timing power attacks in multi-tenant data centers using an acoustic side channel. Proc. ACM Meas. Anal. Comput. Syst., 2(1).
Jingyi, Guo, Hu, J., Rui, Z., and Wang, Z. (2024). Admm-1dnet: Online monitoring method for outdoor mechanical equipment part signals based on deep learning and compressed sensing. Applied Sciences, 14(6).
Katz, G. and Sonkin, E. (2019). Level optimization of pam-4 transmission with signal-dependent noise. IEEE Photonics Journal, 11(1):1–6.
Killeen, J., Davis, I., Wang, J., and Bennett, G. J. (2023). Fan-noise reduction of data centre telecommunications’ server racks, with an acoustic metamaterial broadband, low-frequency sound-absorbing liner. Applied Acoustics, 203. Cited by: 31; All Open Access, Green Open Access, Hybrid Gold Open Access.
Lee, C., Park, C., Jang, K., Moon, S., and Han, D. (2017). Dx: Latency-based congestion control for datacenters. IEEE/ACM Transactions on Networking, 25(1):335–348.
Levy, M. and Hallstrom, J. O. (2017). A new approach to data center infrastructure monitoring and management (dcimm). In 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), pages 1–6.
Liang, J., Liu, Y., Fang, M., and Xu, J. (2025). Fault prediction technology of data center based on voiceprint recognition. In International Conference on Electronics, Electrical, and Information Engineering (ICEEIE 2025), volume 14003, pages 185–193. SPIE.
Lin, S.-L. (2021). Application of machine learning to a medium gaussian support vector machine in the diagnosis of motor bearing faults. Electronics, 10(18).
Liu, C. (2025). Research on noise suppression in optical communication of data centers based on multi core fiber. IET Conference Proceedings, 2025(2):103 – 107. Cited by: 0.
Mebratu, D., John, J. J., Desai, R., and Khanna, R. (2022). Online server fan failure prediction by vibration analysis augmented by hardware and software telemetry. In 2022 21st IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (iTherm), pages 1–9.
Mihalache, C.-M., Bigan, C., Panduru, V., and Tsakiris, C. (2019). Modelling of noise reduction for datacentre buildings fire protection with inert gas systems. MATEC Web of Conferences, 290:12006.
Miljković, D. (2016). Noise within a data center. In 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pages 1145–1150.
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering.
Pisani, F., de Oliveira, F., Gama, E. S., Immich, R., Bittencourt, L. F., and Borin, E. (2020). Fog computing on constrained devices: Paving the way for the future iot. Advances in Edge Computing: Massive Parallel Processing and Applications, 35:22.
Prevedelli, D., Bergamaschi, L., Acquaviva, A., Persia, F., and Massolini, R. (2025). A 0.1-26ghz serdes-based broadband white noise generator for ethernet compliance tests. IEEE Transactions on Instrumentation and Measurement, PP:1–1.
Rodrigues, D. O., Santos, F. A., Filho, G. P. R., Akabane, A. T., Cabral, R., Immich, R., Junior, W. L., Cunha, F. D., Guidoni, D. L., Silva, T. H., Rosario, D., Cerqueira, E., Loureiro, A. A. F., and Villas, L. A. (2019). Computação urbana da teoria à prática: Fundamentos, aplicações e desafios. Technical report, Minicurso do Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC).
Santo, Y., Immich, R., Dalmazo, B. L., and Riker, A. (2023). Fault detection on the edge and adaptive communication for state of alert in industrial internet of things. Sensors, 23(7).
Sen Gupta, P. (2024). Phd forum abstract: Knowledge from noise: Emi-guided power monitoring. In 2024 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), page 317–318. IEEE Press.
Sevillano, X., Socoró, J. C., Alías, F., Bellucci, P., Peruzzi, L., Radaelli, S., Coppi, P., Nencini, L., Cerniglia, A., Bisceglie, A., Benocci, R., and Zambon, G. (2016). DYNAMAP – development of low cost sensors networks for real time noise mapping. Noise Mapping, 3(1).
Wasala, S., Stevens, L., Sosseh, R., and Persoons, T. (2022). Acoustic noise insulation for air-cooled data centre hard disk drive enclosures: Effect on thermal management. In 2022 28th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC), pages 1–4.
Wu, A., Zhu, C., Jiang, X., and Yang, Q. (2025). Streaming data anomaly detection in energy big data center using unsupervised learning. 2025 37th Chinese Control and Decision Conference (CCDC), pages 1776–1781.
Wüstrich, L., Gallenmüller, S., Günther, S., Carle, G., and Pahl, M.-O. (2024). Shells bells: Cyber-physical anomaly detection in data centers. MATEC Web of Conferences, pages 1–10.
Wüstrich, L., Gallenmüller, S., Pahl, M.-O., and Carle, G. (2022). AC/DCIM: Acoustic channels for data center infrastructure monitoring. MATEC Web of Conferences, pages 1–5.
Yang, C.-W., Lo, Y.-C., Tsai, T.-L., and Wu, A.-Y. (2024). Memory-oriented structural pruning for anomalous sound detection system on microcontrollers. page 669 – 673. Cited by: 1.
Yang, D. (2025). Modeling and key parameter identification method of data center thermal dynamic system towards demand response. Electric Power Automation Equipment, 45(4):186–193.
Zeng, W., Zhang, C., Liang, X., Xia, J., Li, Y., and Lin, Y. (2025). Chaos-enhanced quantization noise injection via dual delta-sigma modulation for secure data center optical interconnects. In 2025 Asia Communications and Photonics Conference (ACP), pages 1–4.
Agency, I. E. (2025). Energy demand from ai. Accessed: 2025-10-30.
Ahmed, S., Ahsan, M., Hadi, F., Ahmed, I., and Khan, A. (2017). A novel noise-measuring system based on wsn. In 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT), pages 1–6.
Akabane, A. T., Immich, R., Pazzi, R. W., Madeira, E. R. M., and Villas, L. A. (2018). Trusted: A distributed system for information management and knowledge distribution in vanets. In 2018 IEEE Symposium on Computers and Communications (ISCC), pages 1–6.
Alnuaimy, Ahmed, Shushurab, O., and Zhyrovc, G. (2022). Impact of noise inside server room.
Alves, D., Dalmazo, B., Riker, A., Filho, G. R., and Immich, R. (2025). Prevenção e detecção de intrusões em redes iot: Um mapeamento sistemático de soluções na borda e na nuvem. In Anais do XVII Simpósio Brasileiro de Computação Ubíqua e Pervasiva, pages 111–120, Porto Alegre, RS, Brasil. SBC.
Bittencourt, L., Immich, R., Sakellariou, R., Fonseca, N., Madeira, E., Curado, M., Villas, L., DaSilva, L., Lee, C., and Rana, O. (2018). The internet of things, fog and cloud continuum: Integration and challenges. Internet of Things, 3-4:134 – 155.
Buchinger, D., de Siqueira Cavalcanti, G. A., and da Silva Hounsell, M. (2014). Mecanismos de busca acadêmica: uma análise quantitativa. Revista Brasileira de Computação Aplicada, 6(1):108–120.
Campbell, K., Lawey, A., and Razavi, M. (2025). Quantum data centres: a simulation-based comparative noise analysis. Quantum Science and Technology, 10(1). Cited by: 1; All Open Access, Green Open Access, Hybrid Gold Open Access.
Chen, Z., Xiang, J., Xiang, M., Fu, S., and Qin, Y. (2025). Deep neural network-based joint monitoring of carrier-to-signal power ratio (cspr) and optical signal-to-noise ratio (osnr) for directly detected optical single-sideband transmission. Opt. Express, 33(6):12375–12388.
Chowdhury, U., Rodriguez, J., Tradat, M., Soud, Q., Wallace, S., O”Brien, D., Hambruch, S., Heydari, A., Radmard, V., and Shahi, P. (2024). Acoustics analysis of air and hybrid cooled data center. In 2024 23rd IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), pages 1–11.
Garcia-Mora, D. M., Garcia-Garcia, D., Yahyaei-Moayyed, F., Cinco-Galicia, J. C., Sanchez-Ortiz, C. R., and Sala, C. A. (2016). Filter design methodology for low noise power domains in datacenter platforms. In 2016 IEEE MTT-S Latin America Microwave Conference (LAMC), pages 1–3.
Ge, C., Chen, X., Wang, M., and Wang, J. (2022). Deep baseline network for time series modeling and anomaly detection. page 1137 – 1142. Cited by: 0.
Islam, M. A., Yang, L., Ranganath, K., and Ren, S. (2018). Why some like it loud: Timing power attacks in multi-tenant data centers using an acoustic side channel. Proc. ACM Meas. Anal. Comput. Syst., 2(1).
Jingyi, Guo, Hu, J., Rui, Z., and Wang, Z. (2024). Admm-1dnet: Online monitoring method for outdoor mechanical equipment part signals based on deep learning and compressed sensing. Applied Sciences, 14(6).
Katz, G. and Sonkin, E. (2019). Level optimization of pam-4 transmission with signal-dependent noise. IEEE Photonics Journal, 11(1):1–6.
Killeen, J., Davis, I., Wang, J., and Bennett, G. J. (2023). Fan-noise reduction of data centre telecommunications’ server racks, with an acoustic metamaterial broadband, low-frequency sound-absorbing liner. Applied Acoustics, 203. Cited by: 31; All Open Access, Green Open Access, Hybrid Gold Open Access.
Lee, C., Park, C., Jang, K., Moon, S., and Han, D. (2017). Dx: Latency-based congestion control for datacenters. IEEE/ACM Transactions on Networking, 25(1):335–348.
Levy, M. and Hallstrom, J. O. (2017). A new approach to data center infrastructure monitoring and management (dcimm). In 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), pages 1–6.
Liang, J., Liu, Y., Fang, M., and Xu, J. (2025). Fault prediction technology of data center based on voiceprint recognition. In International Conference on Electronics, Electrical, and Information Engineering (ICEEIE 2025), volume 14003, pages 185–193. SPIE.
Lin, S.-L. (2021). Application of machine learning to a medium gaussian support vector machine in the diagnosis of motor bearing faults. Electronics, 10(18).
Liu, C. (2025). Research on noise suppression in optical communication of data centers based on multi core fiber. IET Conference Proceedings, 2025(2):103 – 107. Cited by: 0.
Mebratu, D., John, J. J., Desai, R., and Khanna, R. (2022). Online server fan failure prediction by vibration analysis augmented by hardware and software telemetry. In 2022 21st IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (iTherm), pages 1–9.
Mihalache, C.-M., Bigan, C., Panduru, V., and Tsakiris, C. (2019). Modelling of noise reduction for datacentre buildings fire protection with inert gas systems. MATEC Web of Conferences, 290:12006.
Miljković, D. (2016). Noise within a data center. In 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pages 1145–1150.
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering.
Pisani, F., de Oliveira, F., Gama, E. S., Immich, R., Bittencourt, L. F., and Borin, E. (2020). Fog computing on constrained devices: Paving the way for the future iot. Advances in Edge Computing: Massive Parallel Processing and Applications, 35:22.
Prevedelli, D., Bergamaschi, L., Acquaviva, A., Persia, F., and Massolini, R. (2025). A 0.1-26ghz serdes-based broadband white noise generator for ethernet compliance tests. IEEE Transactions on Instrumentation and Measurement, PP:1–1.
Rodrigues, D. O., Santos, F. A., Filho, G. P. R., Akabane, A. T., Cabral, R., Immich, R., Junior, W. L., Cunha, F. D., Guidoni, D. L., Silva, T. H., Rosario, D., Cerqueira, E., Loureiro, A. A. F., and Villas, L. A. (2019). Computação urbana da teoria à prática: Fundamentos, aplicações e desafios. Technical report, Minicurso do Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC).
Santo, Y., Immich, R., Dalmazo, B. L., and Riker, A. (2023). Fault detection on the edge and adaptive communication for state of alert in industrial internet of things. Sensors, 23(7).
Sen Gupta, P. (2024). Phd forum abstract: Knowledge from noise: Emi-guided power monitoring. In 2024 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), page 317–318. IEEE Press.
Sevillano, X., Socoró, J. C., Alías, F., Bellucci, P., Peruzzi, L., Radaelli, S., Coppi, P., Nencini, L., Cerniglia, A., Bisceglie, A., Benocci, R., and Zambon, G. (2016). DYNAMAP – development of low cost sensors networks for real time noise mapping. Noise Mapping, 3(1).
Wasala, S., Stevens, L., Sosseh, R., and Persoons, T. (2022). Acoustic noise insulation for air-cooled data centre hard disk drive enclosures: Effect on thermal management. In 2022 28th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC), pages 1–4.
Wu, A., Zhu, C., Jiang, X., and Yang, Q. (2025). Streaming data anomaly detection in energy big data center using unsupervised learning. 2025 37th Chinese Control and Decision Conference (CCDC), pages 1776–1781.
Wüstrich, L., Gallenmüller, S., Günther, S., Carle, G., and Pahl, M.-O. (2024). Shells bells: Cyber-physical anomaly detection in data centers. MATEC Web of Conferences, pages 1–10.
Wüstrich, L., Gallenmüller, S., Pahl, M.-O., and Carle, G. (2022). AC/DCIM: Acoustic channels for data center infrastructure monitoring. MATEC Web of Conferences, pages 1–5.
Yang, C.-W., Lo, Y.-C., Tsai, T.-L., and Wu, A.-Y. (2024). Memory-oriented structural pruning for anomalous sound detection system on microcontrollers. page 669 – 673. Cited by: 1.
Yang, D. (2025). Modeling and key parameter identification method of data center thermal dynamic system towards demand response. Electric Power Automation Equipment, 45(4):186–193.
Zeng, W., Zhang, C., Liang, X., Xia, J., Li, Y., and Lin, Y. (2025). Chaos-enhanced quantization noise injection via dual delta-sigma modulation for secure data center optical interconnects. In 2025 Asia Communications and Photonics Conference (ACP), pages 1–4.
Publicado
19/07/2026
Como Citar
MOURA, Renan; DALMAZO, Bruno L.; RIKER, André; FONTES, Ramon; B. FILHO, Itamir M.; IMMICH, Roger.
Detecção e Monitoramento de Anomalias em Data Centers Através de Análise Acústica: Abordagens e Direções Futuras. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 18. , 2026, Gramado/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 162-175.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2026.23391.
