| 1. |
- Coelho, Frederico, et al.
(författare)
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Forecasting power load curves from spatial and temporal mobile data
- 2020
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Ingår i: World Review of Science, Technology and Sustainable Development. - 1741-2234 .- 1741-2242. ; 16:1, s. 4-21
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Tidskriftsartikel (refereegranskat)abstract
- This work aims at applying computational intelligence approaches to telecommunication data, in order to associate mobile data to energy consumption load curves. Clustering methods are applied in order to allow the telecommunication network to infer about its topology and consumption load forecasting. Through an extensive analysis of Telecom Italia dataset and power distribution lines data available for the city of Trento, it was possible to confirm the high correlation between them, mainly when voice data is considered. To a great extent, this correlation can be explained by the fact that cellular communication devices are physically present in the service area of the distribution lines and when people are communicating, they are also consuming energy. Based on the aforementioned dataset, load curves for the city of Trento were constructed having as inputs data from telecommunication transactions. Results show that it is possible to use the telecommunication load as the input to predict the energy load, with the proposed model performing better than the naive predictor in 82% of the tested distribution lines.
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| 2. |
- Araujo, Igor M., et al.
(författare)
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Availability-Guaranteed Service Function Chain Provisioning with Optional Shared Backups
- 2020
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Ingår i: 2020 16TH INTERNATIONAL CONFERENCE ON THE DESIGN OF RELIABLE COMMUNICATION NETWORKS DRCN 2020. - : IEEE.
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Konferensbidrag (refereegranskat)abstract
- The dynamic provisioning of Service Function Chain (SFC) using Virtual Network Functions (VNFs) is a challenging problem, especially for availability-constrained services. The provisioning of backup resources is often used to ensure that availability requirements are fulfilled. However, the assignment of backup resources should be carefully designed to avoid resource inefficiencies as much as possible. This paper proposes the Optional Backup with Shared Path and Shared Function (OBSPSF) strategy, which aims at improving resource efficiency while fulfilling the availability requirements of SFC requests. The strategy uses optional backup provisioning to ensure that backup resources are assigned only when strictly needed (i.e., when the SFC alone does not meet the availability constraint). Moreover, OBSPSF encourages backup sharing (among both connectivity and backup VNFs) to reduce the backup resource overhead. Results show that the strategy can accommodate orders-of-magnitude more services than benchmark heuristics from the literature.
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| 3. |
- Cardoso, Evelin, et al.
(författare)
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A Heuristic Approach for the Design of UAV-Based Disaster Relief in Optical Metro Networks
- 2020
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Ingår i: International Conference on Transparent Optical Networks. - 2162-7339. - 9781728184234 ; 2020-July, s. 1-5
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Konferensbidrag (refereegranskat)abstract
- We propose a novel algorithm to dimension the backup elements in an optical metro network, by considering the adoption of Unmanned Aerial Vehicles (UAVs) and wireless interfaces to realize backup wireless links. Our key idea is to efficiently find the set of node pairs that have to be connected by means of multi-hop UAV-based wireless links, which are selected based on the simulation of multiple disaster events. Results, obtained over a set of meaningful scenarios, demonstrate that our solution can greatly reduce the total installation costs compared to a naive approach, which is instead solely tailored to the restoration of the disrupted links in a given disaster scenario.
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| 4. |
- Chan, Vincent, et al.
(författare)
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Network-wide localization of optical-layer attacks
- 2020
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11616 LNCS, s. 310-322
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Konferensbidrag (refereegranskat)abstract
- Optical networks are vulnerable to a range of attacks targeting service disruption at the physical layer, such as the insertion of harmful signals that can propagate through the network and affect co-propagating channels. Detection of such attacks and localization of their source, a prerequisite for secure network operation, is a challenging task due to the limitations in optical performance monitoring, as well as the scalability and cost issues. In this paper, we propose an approach for localizing the source of a jamming attack by modeling the worst-case scope of each connection as a potential carrier of a harmful signal. We define binary words called attack syndromes to model the health of each connection at the receiver which, when unique, unambiguously identify the harmful connection. To ensure attack syndrome uniqueness, we propose an optimization approach to design attack monitoring trails such that their number and length is minimal. This allows us to use the optical network as a sensor for physical-layer attacks. Numerical simulation results indicate that our approach obtains network-wide attack source localization at only 5.8% average resource overhead for the attack monitoring trails.
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| 5. |
- de Sousa, Amaro, et al.
(författare)
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Structural Methods to Improve the Robustness of Anycast Communications to Large-Scale Failures
- 2020
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Ingår i: Guide to Disaster-Resilient Communication Networks. - Cham : Springer International Publishing. - 9783030446857 ; , s. 401-425
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter is dedicated to the description of structural methods aiming to improve the robustness of anycast communications to large-scale failures, either due to natural disasters or malicious human activities. The chapter considers both software-defined networks (SDNs) where the anycast nodes are the nodes hosting SDN controllers, and content delivery networks (CDNs) where the anycast nodes are the nodes hosting content replicas. Most of the structural methods described in this chapter aim to optimally select the anycast nodes in a given network. The chapter first addresses the robustness of anycast communications to natural disasters based on geodiversity routing. Then, different methods are described to select the SDN controller locations aiming to maximize the SDN control plane robustness to malicious node attacks. Finally, the chapter addresses the robustness of CDNs to malicious link cuts by describing methods for the network upgrade (based either on the addition of new links or new replica locations) and for the optimal selection of content replica locations.
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| 6. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
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Design of Programmable Filterless Optical Networks
- 2020
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Ingår i: 2020 Photonics North, PN 2020.
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Konferensbidrag (refereegranskat)abstract
- We present the main operating principles and guidelines for the design of programmable filterless networks.
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| 7. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
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Machine Learning for Cognitive Optical Network Security Management
- 2020
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Ingår i: Optics InfoBase Conference Papers. - 2162-2701.
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Konferensbidrag (refereegranskat)abstract
- This talk surveys the security threats pertinent to the optical network and outlines the progress and challenges in developing machine learning approaches for cognitive management of optical network security.
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| 8. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
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Machine Learning for Optical Network Security Management
- 2020
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Ingår i: Conference on Optical Fiber Communication, Technical Digest Series. - 9781943580712 ; Part F174-OFC 2020
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Konferensbidrag (refereegranskat)abstract
- We discuss the role of supervised, unsupervised and semi-supervised learning techniques in identification of optical network security breaches. The applicability, performance and challenges related to practical deployment of these techniques are examined.
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| 9. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
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Machine Learning for Optical Network Security Monitoring: A Practical Perspective
- 2020
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Ingår i: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 38:11, s. 2860-2871
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Forskningsöversikt (refereegranskat)abstract
- In order to accomplish cost-efficient management of complex optical communication networks, operators are seeking automation of network diagnosis and management by means of Machine Learning (ML). To support these objectives, new functions are needed to enable cognitive, autonomous management of optical network security. This paper focuses on the challenges related to the performance of ML-based approaches for detection and localization of optical-layer attacks, and to their integration with standard Network Management Systems (NMSs). We propose a framework for cognitive security diagnostics that comprises an attack detection module with Supervised Learning (SL), Semi-Supervised Learning (SSL) and Unsupervised Learning (UL) approaches, and an attack localization module that deduces the location of a harmful connection and/or a breached link. The influence of false positives and false negatives is addressed by a newly proposed Window-based Attack Detection (WAD) approach. We provide practical implementation guidelines for the integration of the framework into the NMS and evaluate its performance in an experimental network testbed subjected to attacks, resulting with the largest optical-layer security experimental dataset reported to date.
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| 10. |
- Natalino Da Silva, Carlos, 1987, et al.
(författare)
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Content placement in 5G‐enabled edge/core datacenter networks resilient to link cut attacks
- 2020
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Ingår i: Networks. - : Wiley. - 1097-0037 .- 0028-3045. ; 75:4, s. 392-392
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Tidskriftsartikel (refereegranskat)abstract
- High throughput, resilience, and low latency requirements drive the development of 5G‐enabled content delivery networks (CDNs) which combine core data centers (cDCs) with edge data centers (eDCs) that cache the most popular content closer to the end users for traffic load and latency reduction. Deployed over the existing optical network infrastructure, CDNs are vulnerable to link cut attacks aimed at disrupting the overlay services. Planning a CDN to balance the stringent service requirements and increase resilience to attacks in a cost‐efficient way entails solving the content placement problem (CPP) across the cDCs and eDCs. This article proposes a framework for finding Pareto‐optimal solutions with minimal user‐to‐content distance and maximal robustness to targeted link cuts, under a defined budget. We formulate two optimization problems as integer linear programming (ILP) models. The first, denoted as K‐best CPP with minimal distance (K‐CPP‐minD), identifies the eDC/cDC placement solutions with minimal user‐to‐content distance. The second performs critical link set detection to evaluate the resilience of the K‐CPP‐minD solutions to targeted fiber cuts. Extensive simulations verify that the eDC/cDC selection obtained by our models improves network resilience to link cut attacks without adversely affecting the user‐to‐content distances or the core network traffic mitigation benefits.
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