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Gabriele Russo Russo
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2020 – today
- 2024
- [j7]Gabriele Russo Russo, Daniele Ferrarelli, Diana Pasquali, Valeria Cardellini, Francesco Lo Presti:
QoS-aware offloading policies for serverless functions in the Cloud-to-Edge continuum. Future Gener. Comput. Syst. 156: 1-15 (2024) - [j6]Gabriele Russo Russo, Valeria Cardellini, Francesco Lo Presti:
A framework for offloading and migration of serverless functions in the Edge-Cloud Continuum. Pervasive Mob. Comput. 100: 101915 (2024) - [c22]Gabriele Russo Russo, Enrico D'Alessandro, Valeria Cardellini, Francesco Lo Presti:
Towards a Multi-Armed Bandit Approach for Adaptive Load Balancing in Function-as-a-Service Systems. ACSOS-C 2024: 103-108 - [c21]Cecilia Calavaro, Gabriele Russo Russo, Martina Salvati, Valeria Cardellini, Francesco Lo Presti:
Towards Energy-Aware Execution and Offloading of Serverless Functions. FRAME@HPDC 2024 - [c20]Anton Semjonov, Heiko Bornholdt, Janick Edinger, Gabriele Russo Russo:
Artifact: Wasimoff: Distributed Computation Offloading Using WebAssembly in the Browser. PerCom Workshops 2024: 17-18 - [c19]Anton Semjonov, Heiko Bornholdt, Janick Edinger, Gabriele Russo Russo:
Wasimoff: Distributed Computation Offloading Using WebAssembly in the Browser. PerCom Workshops 2024: 203-208 - [c18]Matteo Nardelli, Gabriele Russo Russo:
Function Offloading and Data Migration for Stateful Serverless Edge Computing. ICPE 2024: 247-257 - 2023
- [j5]Gabriele Russo Russo, Valeria Cardellini, Francesco Lo Presti:
Hierarchical Auto-scaling Policies for Data Stream Processing on Heterogeneous Resources. ACM Trans. Auton. Adapt. Syst. 18(4): 14:1-14:44 (2023) - [c17]Matteo Nardelli, Gabriele Russo Russo, Valeria Cardellini:
Compute Continuum: What Lies Ahead? Euro-Par Workshops (1) 2023: 5-17 - [c16]Gabriele Russo Russo, Valeria Cardellini, Francesco Lo Presti:
Serverless Functions in the Cloud-Edge Continuum: Challenges and Opportunities. PDP 2023: 321-328 - [c15]Gabriele Russo Russo, Tiziana Mannucci, Valeria Cardellini, Francesco Lo Presti:
Artifact: Serverledge: Decentralized Function-as-a-Service for the Edge-Cloud Continuum. PerCom Workshops 2023: 1-2 - [c14]Gabriele Russo Russo, Tiziana Mannucci, Valeria Cardellini, Francesco Lo Presti:
Serverledge: Decentralized Function-as-a-Service for the Edge-Cloud Continuum. PERCOM 2023: 131-140 - [c13]Federica Filippini, Riccardo Cavadini, Danilo Ardagna, Riccardo Lancellotti, Gabriele Russo Russo, Valeria Cardellini, Francesco Lo Presti:
FIGARO: reinForcement learnInG mAnagement acRoss the computing cOntinuum. UCC 2023: 47 - [c12]Gabriele Russo Russo:
Using Reinforcement Learning to Control Auto-Scaling of Distributed Applications. ICPE (Companion) 2023: 137-138 - 2022
- [j4]Valeria Cardellini, Francesco Lo Presti, Matteo Nardelli, Gabriele Russo Russo:
Runtime Adaptation of Data Stream Processing Systems: The State of the Art. ACM Comput. Surv. 54(11s): 237:1-237:36 (2022) - [c11]Cecilia Calavaro, Gabriele Russo Russo, Valeria Cardellini:
Real-time analysis of market data leveraging Apache Flink. DEBS 2022: 162-165 - [c10]Gabriele Russo Russo, Alfredo Milani, Stefano Iannucci, Valeria Cardellini:
Towards QoS-Aware Function Composition Scheduling in Apache OpenWhisk. PerCom Workshops 2022: 693-698 - 2021
- [c9]Gabriele Russo Russo, Valeria Cardellini, Giuliano Casale, Francesco Lo Presti:
MEAD: Model-Based Vertical Auto-Scaling for Data Stream Processing. CCGRID 2021: 314-323 - [c8]Gabriele Russo Russo, Antonio Schiazza, Valeria Cardellini:
Elastic Pulsar Functions for Distributed Stream Processing. ICPE (Companion) 2021: 9-16 - 2020
- [c7]Gabriele Russo Russo:
Model-based auto-scaling of distributed data stream processing applications. Middleware Doctoral Symposium 2020: 5-8
2010 – 2019
- 2019
- [c6]Gabriele Russo Russo, Valeria Cardellini, Francesco Lo Presti:
Reinforcement Learning Based Policies for Elastic Stream Processing on Heterogeneous Resources. DEBS 2019: 31-42 - [c5]Gabriele Russo Russo:
Self-Adaptive Data Stream Processing in Geo-Distributed Computing Environments. DEBS 2019: 276-279 - 2018
- [j3]Gabriele Russo Russo, Matteo Nardelli, Valeria Cardellini, Francesco Lo Presti:
Multi-Level Elasticity for Wide-Area Data Streaming Systems: A Reinforcement Learning Approach. Algorithms 11(9): 134 (2018) - [j2]Valeria Cardellini, Francesco Lo Presti, Matteo Nardelli, Gabriele Russo Russo:
Optimal operator deployment and replication for elastic distributed data stream processing. Concurr. Comput. Pract. Exp. 30(9) (2018) - [j1]Valeria Cardellini, Francesco Lo Presti, Matteo Nardelli, Gabriele Russo Russo:
Decentralized self-adaptation for elastic Data Stream Processing. Future Gener. Comput. Syst. 87: 171-185 (2018) - [c4]Matteo Nardelli, Gabriele Russo Russo, Valeria Cardellini, Francesco Lo Presti:
A Multi-level Elasticity Framework for Distributed Data Stream Processing. Euro-Par Workshops 2018: 53-64 - [c3]Gabriele Russo Russo:
Towards Decentralized Auto-Scaling Policies for Data Stream Processing Applications. ZEUS 2018: 47-54 - 2017
- [c2]Valeria Cardellini, Francesco Lo Presti, Matteo Nardelli, Gabriele Russo Russo:
Towards Hierarchical Autonomous Control for Elastic Data Stream Processing in the Fog. Euro-Par Workshops 2017: 106-117 - [c1]Valeria Cardellini, Francesco Lo Presti, Matteo Nardelli, Gabriele Russo Russo:
Auto-Scaling in Data Stream Processing Applications: A Model-Based Reinforcement Learning Approach. InfQ@VALUETOOLS 2017: 97-110
Coauthor Index
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last updated on 2024-12-15 01:24 CET by the dblp team
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