Browsing by Author "Russo, Alessandra"

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  • Data for NFVSDN experiments
    Rankothge, Windhya; Le, Franck; Russo, Alessandra; Lobo, Jorge (Universitat Pompeu Fabra, 2017)
    Network Function Virtualization (NFV) proposes to move packet processing from dedicated hardware middle-boxes to software running on commodity servers: virtualized Network Function (NFs) (i.e, Firewall, Proxy, Intrusion ...
  • Data modelling for the evaluation of virtualized network functions resource allocation algorithms
    Rankothge, Windhya; Le, Franck; Russo, Alessandra; Lobo, Jorge (2017)
    To conduct a more realistic evaluations on resource allocation algorithms for Virtualized Network Functions (VNFs), researches need data on: (1) potential Network Functions (NFs) chains (policies), (2) traffic flows ...
  • Embed2Sym: scalable neuro-symbolic reasoning via clustered embeddings
    Aspis, Yaniv; Broda, Krysia; Lobo, Jorge; Russo, Alessandra (International Joint Conferences on Artificial Intelligence Organization, 2022)
    Neuro-symbolic reasoning approaches proposed in recent years combine a neural perception component with a symbolic reasoning component to solve a downstream task. By doing so, these approaches can provide neural networks ...
  • Experimental results on the use of genetic algorithms for scaling virtualized network functions
    Rankothge, Windhya; Le, Franck; Russo, Alessandra; Lobo, Jorge (Institute of Electrical and Electronics Engineers (IEEE), 2015)
    Network Function Virtualization (NFV) is bringing closer the possibility to truly migrate enterprise data centers into the cloud. However, for a Cloud Service Provider to offer such services, important questions include ...
  • FastLAS: scalable inductive logic programming incorporating domain-specific optimisation criteria
    Law, Mark; Russo, Alessandra; Bertino, Elisa; Broda, Krysia; Lobo, Jorge (Association for the Advancement of Artificial Intelligence (AAAI), 2020)
    Inductive Logic Programming (ILP) systems aim to find a set of logical rules, called a hypothesis, that explain a set of examples. In cases where many such hypotheses exist, ILP systems often bias towards shorter solutions, ...
  • FFNSL: Feed-Forward Neural-Symbolic Learner
    Cunnington, Daniel; Law, Mark; Lobo, Jorge; Russo, Alessandra (Springer, 2023)
    Logic-based machine learning aims to learn general, interpretable knowledge in a data-efficient manner. However, labelled data must be specified in a structured logical form. To address this limitation, we propose a ...
  • Induction and exploitation of subgoal automata for reinforcement learning
    Furelos Blanco, Daniel; Law, Mark; Jonsson, Anders, 1973-; Broda, Krysia; Russo, Alessandra (AI Access Foundation, 2021)
    In this paper we present ISA, an approach for learning and exploiting subgoals in episodic reinforcement learning (RL) tasks. ISA interleaves reinforcement learning with the induction of a subgoal automaton, an automaton ...
  • On security policy migrations
    Lobo, Jorge; Bertino, Elisa; Russo, Alessandra (ACM Association for Computer Machinery, 2020)
    There has been over the past decade a rapid change towards computational environments that are comprised of large and diverse sets of devices, many of them mobile, which can connect in flexible and context-dependent ways. ...
  • Online symbolic learning of policies for explainable security
    Drozdov, Arthur; Law, Mark; Lobo, Jorge; Russo, Alessandra; Wilathgamuwage Don, Mercion (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Statistical Machine Learning (ML) has been proved to be an invaluable tool in many areas including privacy and security. On the other hand, recent advances in the field of Symbolic Learning have included novel scalable ...
  • Optimizing resource allocation for virtualized network functions in a cloud center using genetic algorithms
    Rankothge, Windhya; Le, Franck; Russo, Alessandra; Lobo, Jorge (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    With the introduction of network function virtualization technology, migrating entire enterprise data centers into the cloud has become a possibility. However, for a cloud service provider (CSP) to offer such services, ...
  • Representing and learning grammars in answer set programming
    Law, Mark; Russo, Alessandra; Bertino, Elisa; Broda, Krysia; Lobo, Jorge (Association for the Advancement of Artificial Intelligence (AAAI), 2019)
    In this paper we introduce an extension of context-free grammars called answer set grammars (ASGs). These grammars allow annotations on production rules, written in the language of Answer Set Programming (ASP), which can ...
  • Towards making network function virtualization a cloud computing service
    Rankothge, Windhya; Ma, Jiefei; Le, Franck; Russo, Alessandra; Lobo, Jorge (Institute of Electrical and Electronics Engineers (IEEE), 2015)
    By allowing network functions to be virtualized and run on commodity hardware, NFV enables new properties (e.g., elastic scaling), and new service models for Service Providers, Enterprises, and Telecommunication Service ...

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