• AUTOnomously Optimizing Cloud Applications
  2013 – 2025 / AUTO-Cloud

2024

• A systematic review on privacy-aware IoT personal data stores / Pinto, G., Donta, P. K., Dustdar, S., & Prazeres, C. (2024). A systematic review on privacy-aware IoT personal data stores. Sensors, 24(7), Article 2197. https://doi.org/10.3390/s24072197
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  Project: TEADAL (2022–2025)
• Distributed AI in Zero-Touch Provisioning for Edge Networks: Challenges and Research Directions / Hazra, A., Morichetta, A., Murturi, I., Lovén, L., Dehury, C. K., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2024). Distributed AI in Zero-Touch Provisioning for Edge Networks: Challenges and Research Directions. Computer, 57(3), 69–78. https://doi.org/10.1109/MC.2023.3334913
• Learning Techniques for the Internet of Things / Donta, P. K., Hazra, A., & Lovén, L. (Eds.). (2024). Learning Techniques for the Internet of Things. Springer. https://doi.org/10.1007/978-3-031-50514-0
  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Intelligence Inference on IoT Devices / Zhang, Q., Li, Y., Zhang, D., Murturi, I., Casamayor Pujol, V., Dustdar, S., & Wang, S. (2024). Intelligence Inference on IoT Devices. In P. K. Donta, A. Hazra, & L. Loven (Eds.), Learning Techniques for the Internet of Things (pp. 171–195). Springer. https://doi.org/10.1007/978-3-031-50514-0_9
• Federated Learning for Internet of Things / Li, Y., Zhang, Q., Wang, X., Zeng, R., Li, H., Murturi, I., Dustdar, S., & Huang, M. (2024). Federated Learning for Internet of Things. In P. K. Donta, A. Hazra, & L. Loven (Eds.), Learning Techniques for the Internet of Things (pp. 33–55). Springer. https://doi.org/10.1007/978-3-031-50514-0_3
• Securing Clustered Edge Intelligence With Blockchain / Dehury, C. K., Srirama, S. N., Donta, P. K., & Dustdar, S. (2024). Securing Clustered Edge Intelligence With Blockchain. IEEE Consumer Electronics Magazine, 13(1), 22–29. https://doi.org/10.1109/MCE.2022.3164529

2023

• A new fault feature extraction method of rolling bearings based on the improved self-selection ICEEMDAN-permutation entropy / Xiao, M., Wang, Z., Zhao, Y., Geng, G., Dustdar, S., Donta, P. K., & Ji, G. (2023). A new fault feature extraction method of rolling bearings based on the improved self-selection ICEEMDAN-permutation entropy. ISA Transactions, 143, 536–547. https://doi.org/10.1016/j.isatra.2023.09.009
• Blockchain-based Zero Trust on the Edge / Bicer, C., Murturi, I., Donta, P. K., & Dustdar, S. (2023). Blockchain-based Zero Trust on the Edge. arXiv. https://doi.org/10.34726/5941
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  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Equilibrium in the Computing Continuum through Active Inference / Sedlak, B., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Equilibrium in the Computing Continuum through Active Inference. arXiv. https://doi.org/10.34726/5944
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  Project: TEADAL (2022–2025)
• Active Inference on the Edge : A Design Study / Sedlak, B., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Active Inference on the Edge : A Design Study. arXiv. https://doi.org/10.34726/5939
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  Project: TEADAL (2022–2025)
• Designing Reconfigurable Intelligent Systems with Markov Blankets / Sedlak, B., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Designing Reconfigurable Intelligent Systems with Markov Blankets. arXiv. https://doi.org/10.34726/5943
  Download: PDF (1.5 MB)
  Project: TEADAL (2022–2025)
• Collaborative Inference in DNN-based Satellite Systems with Dynamic Task Streams / Guan, J., Zhang, Q., Murturi, I., Donta, P. K., Dustdar, S., & Wang, S. (2023). Collaborative Inference in DNN-based Satellite Systems with Dynamic Task Streams. arXiv. https://doi.org/10.34726/5942
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• Towards Serverless Data Exchange Within Federations / Sedlak, B., Casamayor Pujol, V., Donta, P. K., Werner, S., Wolf, K., Falconi, M., Pallas, F., Dustdar, S., Tai, S., & Plebani, P. (2023). Towards Serverless Data Exchange Within Federations. In M. Aiello, J. Barzen, S. Dustdar, & F. Leymann (Eds.), Service-Oriented Computing, 17th Symposium and Summer School, SummerSOC 2023 (pp. 144–153). Springer. https://doi.org/10.1007/978-3-031-45728-9_9
  Project: TEADAL (2022–2025)
• Exploring the Potential of Distributed Computing Continuum Systems / Donta, P. K., Murturi, I., Casamayor Pujol, V., Sedlak, B., & Dustdar, S. (2023). Exploring the Potential of Distributed Computing Continuum Systems. Computers, 12(10), Article 198. https://doi.org/10.3390/computers12100198
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  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Learning‐driven ubiquitous mobile edge computing: Network management challenges for future generation Internet of Things / Donta, P. K., Monteiro, E., Dehury, C. K., & Murturi, I. (2023). Learning‐driven ubiquitous mobile edge computing: Network management challenges for future generation Internet of Things. International Journal of Network Management, 33(5), Article e2250. https://doi.org/10.1002/nem.2250
• Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey / Ravi, B., Varghese, B., Murturi, I., Donta, P. K., Dustdar, S., Dehury, C. K., & Srirama, S. N. (2023). Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey. Computers, 12(8), Article 162. https://doi.org/10.3390/computers12080162
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• Unleashing the Potential of Distributed Computing Continuum Systems / Donta, P. K. (2023, July 21). Unleashing the Potential of Distributed Computing Continuum Systems [Conference Presentation]. 2nd China-Austria Innovation Cooperation Exchange Conference & International Symposium on AI and Digital Economy (CAICC-IDIA 2023), Nanjing, Jiangsu Povince, China.
• Edge Intelligence—Research Opportunities for Distributed Computing Continuum Systems / Casamayor Pujol, V., Donta, P. K., Morichetta, A., Murturi, I., & Dustdar, S. (2023). Edge Intelligence—Research Opportunities for Distributed Computing Continuum Systems. IEEE Internet Computing, 27(4), 53–74. https://doi.org/10.1109/MIC.2023.3284693
• Optimal rendezvous points selection and mobile sink trajectory construction for data collection in WSNs / Gutam, B. G., Donta, P. K., Annavarapu, C. S. R., & Hu, Y.-C. (2023). Optimal rendezvous points selection and mobile sink trajectory construction for data collection in WSNs. Journal of Ambient Intelligence and Humanized Computing, 14, 7147–7158. https://doi.org/10.1007/s12652-021-03566-2
• A Bi-FPN-Based Encoder–Decoder Model for Lung Nodule Image Segmentation / Annavarapu, C. S. R., Parisapogu, S. A. B., Keetha, N. V., Donta, P. K., & Rajita, G. (2023). A Bi-FPN-Based Encoder–Decoder Model for Lung Nodule Image Segmentation. Diagnostics, 13(8), Article 1406. https://doi.org/10.3390/diagnostics13081406
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• Editorial: Efficient deep neural network for intelligent robot system: Focusing on visual signal processing / Bai, X., Ning, X., Donta, P. K., & Li, W. (2023). Editorial: Efficient deep neural network for intelligent robot system: Focusing on visual signal processing. Frontiers in Neurorobotics, 17, Article 1191655. https://doi.org/10.3389/fnbot.2023.1191655
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• Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks / Liu, J.-S., Lin, C.-H., Hu, Y.-C., & Donta, P. K. (2023). Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks. Sensors, 23(8), Article 3900. https://doi.org/10.3390/s23083900
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• On distributed computing continuum systems / Dustdar, S., Casamayor Pujol, V., & Donta, P. K. (2023). On distributed computing continuum systems. IEEE Transactions on Knowledge and Data Engineering, 35(4), 4092–4105. https://doi.org/10.34726/2381
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• Fundamental Research Challenges for Distributed Computing Continuum Systems / Casamayor Pujol, V., Morichetta, A., Murturi, I., Donta, P. K., & Dustdar, S. (2023). Fundamental Research Challenges for Distributed Computing Continuum Systems. Information, 14(3), Article 198. https://doi.org/10.3390/info14030198
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• Federated Domain Generalization: A Survey / Li, Y., Wang, X., Zeng, R., Donta, P. K., Murturi, I., Huang, M., & Dustdar, S. (2023). Federated Domain Generalization: A Survey. arXiv. https://doi.org/10.34726/5945
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  Project: TEADAL (2022–2025)
• Cooperative Transmission Scheduling and Computation Offloading With Collaboration of Fog and Cloud for Industrial IoT Applications / Hazra, A., Donta, P. K., Amgoth, T., & Dustdar, S. (2023). Cooperative Transmission Scheduling and Computation Offloading With Collaboration of Fog and Cloud for Industrial IoT Applications. IEEE Internet of Things Journal, 10(5), 3944–3953. https://doi.org/10.1109/JIOT.2022.3150070
• An Ensemble Learning Approach for Reversible Data Hiding in Encrypted Images with Fibonacci Transform / Panchikkil, S., Vegesana, S. P., Manikandan, V. M., Donta, P. K., Maddikunta, P. K. R., & Gadekallu, T. R. (2023). An Ensemble Learning Approach for Reversible Data Hiding in Encrypted Images with Fibonacci Transform. Electronics, 12(2), Article 450. https://doi.org/10.3390/electronics12020450
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• Governance and sustainability of distributed continuum systems: a big data approach / Donta, P. K., Sedlak, B., Casamayor Pujol, V., & Dustdar, S. (2023). Governance and sustainability of distributed continuum systems: a big data approach. Journal Of Big Data, 10, Article 53. https://doi.org/10.1186/s40537-023-00737-0
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  Project: TEADAL (2022–2025)
• CommunityAI: Towards Community-based Federated Learning / Murturi, I., Donta, P. K., & Dustdar, S. (2023). CommunityAI: Towards Community-based Federated Learning. In Proceedings 2023 IEEE 5th International Conference on Cognitive Machine Intelligence (CogMI) (pp. 141–149). IEEE. https://doi.org/10.1109/CogMI58952.2023.00029
  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Learning-driven Zero Trust in Distributed Computing Continuum Systems / Murturi, I., Donta, P. K., Casamayor Pujol, V., Morichetta, A., & Dustdar, S. (2023). Learning-driven Zero Trust in Distributed Computing Continuum Systems. arXiv. https://doi.org/10.48550/arXiv.2311.17447
  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Distributed AI in Zero-touch Provisioning for Edge Networks: Challenges and Research Directions / Hazra, A., Morichetta, A., Murturi, I., Loven, L., Dehury, C. K., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Distributed AI in Zero-touch Provisioning for Edge Networks: Challenges and Research Directions. arXiv. https://doi.org/10.48550/arXiv.2311.17471
• CommunityAI: Towards Community-based Federated Learning / Murturi, I., Donta, P. K., & Dustdar, S. (2023). CommunityAI: Towards Community-based Federated Learning. arXiv. https://doi.org/10.48550/arXiv.2311.17958
  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Learning-Driven Zero Trust in Distributed Computing Continuum Systems / Murturi, I., Donta, P. K., Casamayor Pujol, V., Morichetta, A., & Dustdar, S. (2023). Learning-Driven Zero Trust in Distributed Computing Continuum Systems. In 2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) (pp. 0044–0049). IEEE. https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy59711.2023.10361352
  Projects: AloTwin (2023–2025) / TEADAL (2022–2025)
• Designing Reconfigurable Intelligent Systems with Markov Blankets / Sedlak, B., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Designing Reconfigurable Intelligent Systems with Markov Blankets. In F. Monti, S. Rinderle-Ma, A. Ruiz-Cortes, Z. Zheng, & M. Mecella (Eds.), SService-Oriented Computing ; 21st International Conference, ICSOC 2023, Rome, Italy, November 28 – December 1, 2023, Proceedings, Part I / 2023 (pp. 42–50). Springer Cham. https://doi.org/10.1007/978-3-031-48421-6_4
  Project: TEADAL (2022–2025)
• Distributed Computing Continuum Systems – Opportunities and Research Challenges / Casamayor Pujol, V., Donta, P. K., Morichetta, A., Murturi, I., & Dustdar, S. (2023). Distributed Computing Continuum Systems – Opportunities and Research Challenges. In J. Troya, R. MIRANDOLA, E. Navarro, A. Delgado, S. Segura, G. Ortiz, C. Pautasso, C. Zirpins, P. Fernandez, & A. Ruiz-Cortes (Eds.), Service-Oriented Computing – ICSOC 2022 Workshops (pp. 405–407). Springer Cham. https://doi.org/10.1007/978-3-031-26507-5_41
• Towards Intelligent Data Protocols for the Edge / Donta, P. K., & Dustdar, S. (2023). Towards Intelligent Data Protocols for the Edge. In C. A. ARDAGNA, F. Awaysheh, H. Bian, C. K. Chang, R. N. Chang, F. Delicato, N. Desai, J. Fan, G. Fox, A. Goscinski, Z. Jin, A. Kobusinska, & O. Rana (Eds.), 2023 IEEE International Conference on Edge Computing and Communications (EDGE) (pp. 372–380). IEEE. https://doi.org/10.1109/EDGE60047.2023.00060
  Project: TEADAL (2022–2025)
• Controlling Data Gravity and Data Friction: From Metrics to Multidimensional Elasticity Strategies / Sedlak, B., Casamayor Pujol, V., Donta, P. K., & Dustdar, S. (2023). Controlling Data Gravity and Data Friction: From Metrics to Multidimensional Elasticity Strategies. In C. Ardagna, N. Atukorala, C. C. Chang, R. N. Chang, J. Fan, G. Fox, S. Helal, Z. Jin, Q. Lu, T. Seceleanu, & S. S. Yau (Eds.), Proceedings. 2023 IEEE International Conference on Software Services Engineering (IEEE SSE 2023) (pp. 43–49). IEEE. https://doi.org/10.1109/SSE60056.2023.00017
  Project: TEADAL (2022–2025)

2022

• Blockchain for Internet of Underwater Things: State-of-the-Art, Applications, Challenges, and Future Directions / Bhattacharya, S., Victor, N., Chengoden, R., Ramalingam, M., Selvi, G., Maddikunta, P., Donta, P., Dustdar, S., Jhaveri, R., & Gadekallu, T. (2022). Blockchain for Internet of Underwater Things: State-of-the-Art, Applications, Challenges, and Future Directions. Sustainability, 14(23), 1–21. https://doi.org/10.3390/su142315659
  Download: pdf (1.3 MB)
• Secured Wireless Energy Transfer for the Internet of Everything in Ambient Intelligent Environments / Sah, D. K., Poongodi, M., Donta, P. K., Hamdi, M., Cengiz, K., Kamruzzaman, M. M., & Rauf, H. T. (2022). Secured Wireless Energy Transfer for the Internet of Everything in Ambient Intelligent Environments (Vol. 5, Issue 1, pp. 62–66). https://doi.org/10.1109/iotm.001.2100116
• The Promising Role of Representation Learning for Distributed Computing Continuum Systems / Donta, P. K., & Dustdar, S. (2022). The Promising Role of Representation Learning for Distributed Computing Continuum Systems. In 2022 IEEE International Conference on Service-Oriented System Engineering (SOSE) (pp. 126–132). IEEE. https://doi.org/10.1109/SOSE55356.2022.00021
• CCEI-IoT: Clustered and Cohesive Edge Intelligence in Internet of Things / Dehury, C. K., Donta, P. K., Dustdar, S., & Srirama, S. N. (2022). CCEI-IoT: Clustered and Cohesive Edge Intelligence in Internet of Things. In C. A. ARDAGNA, H. Bian, C. C. Chang, R. N. Chang, E. Damiani, G. Elia, Q. He, V. Puig, R. Ward, F. XHAFA, & J. Zhang (Eds.), Proceedings of the 2022 IEEE International Conference on Edge Computing & Communications (IEEE EDGE 2022) (pp. 33–40). IEEE. https://doi.org/10.1109/EDGE55608.2022.00017
• Joint Beamforming, Power Allocation, and Splitting Control for SWIPT-Enabled IoT Networks with Deep Reinforcement Learning and Game Theory / Liu, J., Lin, C.-H. R., Hu, Y.-C., & Donta, P. K. (2022). Joint Beamforming, Power Allocation, and Splitting Control for SWIPT-Enabled IoT Networks with Deep Reinforcement Learning and Game Theory. Sensors, 22(6), 2328. https://doi.org/10.3390/s22062328
• Delay-aware data fusion in duty-cycled wireless sensor networks: A Q-learning approach / Donta, P. K., Amgoth, T., & Annavarapu, C. S. R. (2022). Delay-aware data fusion in duty-cycled wireless sensor networks: A Q-learning approach. Sustainable Computing: Informatics and Systems, 33(100642), 100642. https://doi.org/10.1016/j.suscom.2021.100642