Accelerating Random Forest on Memory-Constrained Devices Through Data Storage Optimization

Autor: Camélia Slimani, Chun-Feng Wu, Stéphane Rubini, Yuan-Hao Chang, Jalil Boukhobza

Publikováno v: IEEE Transactions on Computers. 72:1595-1609

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0c0da9e108a7e418c4430772927a2512
https://doi.org/10.1109/tc.2022.3215898

Serverless Cloud Computing: State of the Art and Challenges

Autor: Vincent Lannurien, Laurent D’Orazio, Olivier Barais, Jalil Boukhobza

Publikováno v: Serverless Computing: Principles and Paradigms
Serverless Computing: Principles and Paradigms, 162, Springer International Publishing, pp.275-316, 2023, Lecture Notes on Data Engineering and Communications Technologies, ⟨10.1007/978-3-031-26633-1_11⟩
Serverless Computing: Principles and Paradigms ISBN: 9783031266324

The serverless model represents a paradigm shift in the cloud: as opposed to traditional cloud computing service models, serverless customers do not reserve hardware resources. The execution of their code is event-driven (HTTP requests, cron jobs, et

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0794ef6832708e460ca7a8fe4e9e83cd
https://hal-ensta-bretagne.archives-ouvertes.fr/hal-04114984

The Lannion report on Big Data and Security Monitoring Research

Autor: Laurent d'Orazio, Jalil Boukhobza, Omer Rana, Juba Agoun, Le Gruenwald, Herve Rannou, Elisa Bertino, Mohand-Said Hacid, Taofik Saidi, Georges Bossert, Van Long Nguyen Huu, Dimitri Tombroff, Makoto Onizuka

Publikováno v: 2022 IEEE International Conference on Big Data (Big Data)
Workshop on Big Data for CyberSecurity (BigCyber-2022)
Workshop on Big Data for CyberSecurity (BigCyber-2022), Dec 2022, Osaka, Japan. pp.2960-2969, ⟨10.1109/BigData55660.2022.10020852⟩

International audience; During the last decade, big data management has attracted increasing interest from both the industrial and academic communities. In parallel, Cyber Security has become mandatory due to various and more intensive threats. In Ju

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdd1902fbd51460e8fdb9db231e5159c
https://doi.org/10.1109/bigdata55660.2022.10020852

When IoT Data Meets Streaming in the Fog

Autor: Lydia Ait-Oucheggou, Mohammed Islam Naas, Yassine Hadjadj-Aoul, Jalil Boukhobza

Publikováno v: ICFEC 2022-IEEE 6th International Conference on Fog and Edge Computing (ICFEC)
ICFEC 2022-IEEE 6th International Conference on Fog and Edge Computing (ICFEC), May 2022, Messina, Italy. pp.50-57, ⟨10.1109/ICFEC54809.2022.00014⟩

International audience; IoT and video streaming are the main driving applications for digital data generation today. The traditional way of storing and processing data in the Cloud cannot satisfy many latency critical applications. This is why Fog co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e05069419d5a99a7f32b8f413169f468
https://hal.science/hal-03703516

RISCLESS: A Reinforcement Learning Strategy to Guarantee SLA on Cloud Ephemeral and Stable Resources

Autor: SidAhmed Yalles, Mohamed Handaoui, Jean-Emile Dartois, Olivier Barais, Laurent d'Orazio, Jalil Boukhobza

Publikováno v: 2022 PDP-30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing
2022 PDP-30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, Mar 2022, Valladolid, Spain. pp.83-87, ⟨10.1109/PDP55904.2022.00021⟩
2022 30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)
2022 30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Mar 2022, Valladolid, Spain. pp.83-87, ⟨10.1109/PDP55904.2022.00021⟩
2022 30th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), Mar 2022, Valladolid, France. pp.83-87, ⟨10.1109/PDP55904.2022.00021⟩

International audience; In this paper, we propose RISCLESS, a Reinforcement Learning strategy to exploit unused Cloud resources. Our approach consists in using a small proportion of stable on-demand resources alongside the ephemeral ones in order to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9763aafce129988d8f74bcd41539368
https://hal.archives-ouvertes.fr/hal-03652734