2023 Journal article Open Access

Data-aware declarative application management in the cloud-IoT continuum
Massa J, Forti S, Dazzi P, Brogi A
Nowadays billions of devices are connected to the Internet of Things and can reach computing facilities along the Cloud-IoT continuum to process the data they produce, leading to a dramatic increase in the number of deployed applications as well as in the amount of data they need to crunch. Following a continuous reasoning approach to speed up the decision-making process, our research proposes a declarative and data-aware solution to determine service-based application placements over the Cloud-IoT continuum while meeting functional and non-functional application requirements.Source: ERCIM NEWS, pp. 35-36

2024 Conference article Open Access

Urgent edge computing
Dazzi P., Ferrucci L., Danelutto M., Tserpes K., Makris A., Theodoropoulos T., Massa J., Carlini E., Mordacchini M.
This position paper introduces Urgent Edge Computing (UEC) as a paradigm shift addressing the evolving demands of time-sensitive applications in distributed edge environments, in time-critical scenarios. With a focus on ultra-low latency, availability, resource management, decentralization, self-organization, and robust security, UEC aims to facilitate operations in critical scenarios such as disaster response, environmental monitoring, and smart city management. This paper outlines and discusses the key requirements, challenges, and enablers along with a conceptual architecture. The paper also outlines the potential applications of Urgent Edge Computing.DOI: 10.1145/3659994.3660315
DOI: 10.48550/arxiv.2404.13411
Project(s): NOUS , Spoke 1 “FutureHPC & BigData” and Spoke 6 “Multiscale Modelling & Engineering Applications f the Italian Research Center on High-Performance Com- puting, Big Data and Quantum Computing (ICSC)
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2025 Conference article Open Access

Marginal Cost of Computation as a Collaborative Strategy for Resource Management at the Edge
Emanuele Carlini, Patrizio Dazzi, Luca Ferrucci, Jacopo Massa, Matteo Mordacchini
This paper explores an extended applications’ cost function to model the willingness of Edge data centres to accommodate additional users in decentralized edge computing environments. By enhancing the Marginal Computing Cost per User (MCU) concept, we introduce a dynamic cost factor influenced by the number of users currently served. Through extensive simulations conducted on the PureEdgeSim platform, we evaluate the impact of this variable MCU on system performance across various configurations. The results reveal a critical trade-off between cost sensitivity (i.e., collaboration willingness) of Edge data centres and optimization potential. This work offers insights into user allocation strategies in heterogeneous edge systems and sets the stage for future research into non-linear MCU configurations and diverse application workloads.Source: LECTURE NOTES IN COMPUTER SCIENCE, pp. 15-27
DOI: 10.1007/978-3-031-81226-2_3
Project(s): EDGELESS
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