Alessio Diamanti, industrial Ph.D. student in collaboration with Orange Labs, will defend his Ph.D. thesis on December 21, 2021, at 1:30 p.m, in the “Boris Vian” Thesis Room (37.2.43) at CNAM, 2 rue Conté, 75003 Paris, France.
Alessio worked on an industrial Ph.D in collaboration with Orange Labs and proposed a new network automation architecture that takes into consideration dynamic reconfiguration upon anomaly detection. He will shortly begin working on 5G core design at SWISSCOM.
Thesis Title: A novel network automation architecture : from anomaly detection to dynamic reconfiguration
Thesis Title (French): Une nouvelle architecture d’automatisation des réseaux : de la détection d’anomalie à la reconfiguration dynamique
Abstract:
Legacy and novel network services are expected to be migrated and designedto be deployed in fully virtualized environments which lead to novel network architecturesthat challenge legacy fault management systems and resilience characterization. Indeed, thecoordination among the different software components for, e.g., orchestration, switching, andvirtual machine and container management creates different monitoring points, besides novelsources of faults and bugs. In this thesis, we propose a network automation framework thatdetects anomalies and characterizes the resiliency state of a virtualized network service. ALong-Short-Term-Memory-Autoencoder-based algorithm analyzes a multidimensional timeseriesbuilt from hundreds of metrics collected at the physical, virtual, and service layers.It learns the nominal working conditions of both the infrastructure and the service, and foreach type of resource (i.e., CPU, network, memory, and disk); it then detects and analyzesdeviations (anomalies) from the learned reference. The produced deviations characterizationis finally used to generate both the transition state graph and the innovative radiographyvisualization. The latter compactly visualizes the propagation of anomalies across all thelayers down from the physical and up to the service, highlighting the temporal evolutionas well. The former aims at establishing the virtualized platform state as the basis for are-orchestration algorithm that leverages a novel reputation-based resiliency managementtechnique. We implement and validate the proposed framework through experimental tests onthe Kubernetes platform hosting a containerized, open-source, and virtualized network core service.
Alessio’s publications
Journal articles
- Alessio Diamanti, Jose Manuel Sanchez Vilchez, Stefano Secci. An AI-empowered framework for cross-layer softwarized infrastructure state assessment. IEEE Transactions on Network and Service Management, 2022, 19 (4), pp.4434-4448. ⟨10.1109/TNSM.2022.3161872⟩. ⟨hal-03621081⟩
Conference papers
- Alessio Diamanti, José Manuel Sanchez Vilchez, Stefano Secci. The SYRROCA AI-empowered network automation platform. 2021 24th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), Mar 2021, Paris, France. pp.140-142, ⟨10.1109/ICIN51074.2021.9385535⟩. ⟨hal-03376034⟩
- Alessio Diamanti, José Manuel Sanchez Vilchez, Stefano Secci. LSTM-based radiography for anomaly detection in softwarized infrastructures. International Teletraffic Congress, IEEE, Sep 2020, Osaka, Japan. ⟨10.1109/ITC3249928.2020.00012⟩. ⟨hal-02917660⟩
- Davide Aureli, Antonio Cianfrani, Alessio Diamanti, José Manuel Sanchez Vilchez, Stefano Secci. Going Beyond DiffServ in IP Traffic Classification. IEEE/IFIP Network Operations and Management Symposium (NOMS), Apr 2020, Budapest, Hungary. ⟨10.1109/NOMS47738.2020.9110430⟩. ⟨hal-02501916⟩
Reports
- Stefano Secci, Alessio Diamanti, José Manuel Sanchez Vilchez, Mamadou Tahirou Bah, Pedra Vizzarreta, et al.. Security and Performance Comparison of ONOS and ODL Controllers. [0] ONOS. 2019. ⟨hal-03188550⟩
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