| 1. |
- Behravesh, Rasaoul, et al.
(author)
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Machine Learning at the Mobile Edge : The Case of Dynamic Adaptive Streaming over HTTP (DASH)
- 2022
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In: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers Inc.. - 1932-4537. ; 19:4, s. 4779-4793
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Journal article (peer-reviewed)abstract
- Dynamic Adaptive Streaming over HTTP (DASH) is a standard for delivering video in segments and adapting each segment’s bitrate (quality), to adjust to changing and limited network bandwidth. We study segment prefetching, informed by machine learning predictions of bitrates of client segment requests, implemented at the network edge. We formulate this client segment request prediction problem as a supervised learning problem of predicting the bitrate of a client’s next segment request, in order to prefetch it at the mobile edge, with the objective of jointly improving the video streaming experience for the users and network bandwidth utilization for the service provider. The results of extensive evaluations showed a segment request prediction accuracy of close to 90% and reduced video segment access delay with a cache hit ratio of 58%, and reduced transport network load by lowering the backhaul link utilization by 60.91%.
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| 2. |
- Behravesh, Rasoul, et al.
(author)
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ML-Driven DASH Content Pre-Fetching in MEC-Enabled Mobile Networks
- 2020
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In: 16th International Conference on Network and Service Management, CNSM 2020, 2nd International Workshop on Analytics for Service and Application Management, AnServApp 2020 and 1st International Workshop on the Future Evolution of Internet Protocols, IPFuture 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9783903176317
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Conference paper (peer-reviewed)abstract
- Streaming high-quality video over dynamic radio networks is challenging. Dynamic adaptive streaming over HTTP (DASH) is a standard for delivering video in segments, and adapting its quality to adjust to a changing and limited network bandwidth. We present a machine learning-based predictive pre-fetching and caching approach for DASH video streaming, implemented at the multi-access edge computing server. We use ensemble methods for machine learning (ML) based segment request prediction and an integer linear programming (ILP) technique for pre-fetching decisions. Our approach reduces video segment access delay with a cache-hit ratio of 60% and alleviates transport network load by reducing the backhaul link utilization by 69%. We validate the ML model and the pre-fetching algorithm, and present the trade-offs involved in pre-fetching and caching for resource-constrained scenarios.
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| 3. |
- Behravesh, Rasoul, et al.
(author)
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Time-Sensitive Mobile User Association and SFC Placement in MEC-Enabled 5G Networks
- 2021
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In: IEEE Transactions on Network and Service Management. - 1932-4537. ; 18:3, s. 3006-3020
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Journal article (peer-reviewed)abstract
- The ongoing roll-out of 5G networks paves the way for many fascinating applications such as virtual reality (VR), augmented reality (AR), and autonomous driving. Moreover, 5G enables billions of devices to transfer an unprecedented amount of data at the same time. This transformation calls for novel technologies like multi-access edge computing (MEC) to satisfy the stringent latency and bitrate requirements of the mentioned applications. The main challenge pertaining to MEC is that the edge MEC nodes are usually characterized by scarce computational resources compared to the core or cloud, arising the challenge of efficiently utilizing the edge resources while ensuring that the service requirements are satisfied. When considered with the users’ mobility, this poses another challenge, which lies in minimization of the service interruption for the users whose service requests are represented as service function chains (SFCs) composed of virtualized network functions (VNFs) instantiated on the MEC nodes or on the cloud. In this paper, we study the problem of joint user association, SFC placement, and resource allocation, employing mixed-integer linear programming (MILP) techniques. The objective function of this MILP-based problem formulation are to minimize (i) the service provisioning cost, (ii) the transport network utilization, and (iii) the service interruption. Moreover, a heuristic algorithm is proposed to tackle the scalability issue of the MILP-based algorithms. Finally, comprehensive experiments are performed to draw a comparison between these approaches.
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| 4. |
- Brito, Flavio, et al.
(author)
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A network architecture for scalable end-to-end management of reusable AI-based applications
- 2023
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In: Proceedings of the 14th International Conference on Network of the Future, NoF 2023. - 9798350338072 ; , s. 98-102
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Conference paper (peer-reviewed)abstract
- Artificial intelligence (AI) is a key enabler for future 6G networks. Currently, related architecture works propose AI-based applications and network services that are dedicated to specific tasks (e.g., improving the performance of RAN with AI). These proposed architectures offer a unique way to collect data, process it, and extract features from data for each AI-based application. However, this dedicated approach creates AI-silos that hinder the integration of AI in the networks. In other words, such AI-silos create a set of AI-models and data for AI-based applications that only work within a single dedicated task. This single-task approach limits the end-to-end integration of AI in the networks. In this work, we propose a network architecture to deploy AI-based applications, at different network domains, that prevents AI-silos by offering reusable data and models to ensure scalable deployments. We describe the architecture, provide workflows for the end-to-end management of AI-based applications, and show the viability of the architecture through multiple use cases.
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| 5. |
- Coronado, Estefania, et al.
(author)
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AI-Empowered Software-Defined WLANs
- 2021
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In: IEEE Communications Magazine. - : Institute of Electrical and Electronics Engineers Inc.. - 0163-6804 .- 1558-1896. ; 59:3, s. 54-60
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Journal article (peer-reviewed)abstract
- The complexity of wireless and mobile networks is growing at an unprecedented pace. This trend is proving current network control and management techniques based on analytical models and simulations to be impractical, especially if combined with the data deluge expected from future applications such as augmented reality. This is particularly true for software-defined wireless local area networks (SO-WLANs). It is our belief that to battle this growing complexity, future SO-WLANs must follow an artificial intelligence (AI) -native approach. In this article, we introduce aiOS, which is an AI-based platform that builds toward the autonomous management of SD-WLANs. Our proposal is aligned with the most recent trends in in-network AI promoted by the ITU Telecommunication Standardization Sector (ITU-T) and with the architecture for disaggregated radio access networks promoted by the Open Radio Access Network Alliance. We validate aiOS in a practical use case, namely frame size optimization in SD-WLANs, and we consider the long-term evolution, challenges, and scenarios for AI-assisted network automation in the wireless and mobile networking domain
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| 6. |
- Coronado, Estefania, et al.
(author)
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ONIX : Open Radio Network Information eXchange
- 2021
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In: IEEE Communications Magazine. - : Institute of Electrical and Electronics Engineers Inc.. - 0163-6804 .- 1558-1896. ; 59:10, s. 14-20
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Journal article (peer-reviewed)abstract
- While video-on-demand still takes up the lion's share of Internet traffic, we are witnessing a significant increase in the adoption of mobile applications defined by tight bit rate and latency requirements (e.g., augmented/virtual reality). Supporting such applications over a mobile network is very challenging due to the unsteady nature of the network and the long distance between the users and the application back-end, which usually sits in the cloud. To address these and other challenges, like security, reliability, and scalability, a new paradigm termed multi-access edge computing (MEC) has emerged. MEC places computational resources closer to the end users, thus reducing the overall end-to-end latency and the utilization of the network backhaul. However, to adapt to the volatile nature of a mobile network, MEC applications need real-time information about the status of the radio channel. The ETSI-defined radio network information service (RNIS) is in charge of providing MEC applications with up-to-date information about the radio network. In this article, we first discuss three use cases that can benefit from the RNIS (collision avoidance, media streaming, and Industrial Internet of Things). Then we analyze the requirements and challenges underpinning the design of a scalable RNIS platform, and report on a prototype implementation and its evaluation. Finally, we provide a roadmap of future research challenges.
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| 7. |
- Coronado, Estefanía, et al.
(author)
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Zero Touch Management : A Survey of Network Automation Solutions for 5G and 6G Networks
- 2022
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In: IEEE Communications Surveys & Tutorials. - : Institute of Electrical and Electronics Engineers (IEEE). - 1553-877X .- 2373-745X. ; 24:4, s. 2535-2578
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Journal article (peer-reviewed)abstract
- Mobile networks are facing an unprecedented demand for high-speed connectivity originating from novel mobile applications and services and, in general, from the adoption curve of mobile devices. However, coping with the service requirements imposed by current and future applications and services is very difficult since mobile networks are becoming progressively more heterogeneous and more complex. In this context, a promising approach is the adoption of novel network automation solutions and, in particular, of zero-touch management techniques. In this work, we refer to zero-touch management as a fully autonomous network management solution with human oversight. This survey sits at the crossroad between zero-touch management and mobile and wireless network research, effectively bridging a gap in terms of literature review between the two domains. In this paper, we first provide a taxonomy of network management solutions. We then discuss the relevant state-of-the-art on autonomous mobile networks. The concept of zero-touch management and the associated standardization efforts are then introduced. The survey continues with a review of the most important technological enablers for zero-touch management. The network automation solutions from the RAN to the core network, including end-to-end aspects such as security, are then surveyed. Finally, we close this article with the current challenges and research directions.
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| 8. |
- Facca, Federico, et al.
(author)
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NetIDE: First steps towards an integrated development environment for portable network apps
- 2013
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In: Proceedings of the 2nd European Workshop on Software Defined Networks (EWSDN). - : IEEE conference proceedings. ; , s. 105-110
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Conference paper (peer-reviewed)abstract
- Nowadays, while most of the programmable network apparatus vendors support OpenFlow, a number of fragmented control plane solutions exist for proprietary Software–Defined Networks. Thus, network applications developers are forced to re-implement their solutions every time they encounter a new network controller. Moreover, different network developers adopt different solutions as control plane programming language (e.g. Frenetic, Procera), severely limiting code sharing and reuse. Despite having OpenFlow as candidate standard interface between the controller and the network infrastructure, interoperability between different controllers and network devices is hindered and closed ecosystems are emerging. In this paper we present the roadmap toward NetIDE, an integrated development environment which aims at supporting the whole development lifecycle of vendor–agnostic network applications.
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| 9. |
- Gómez, Blas, et al.
(author)
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WiMCA : multi-indicator client association in software-defined Wi-Fi networks
- 2021
-
In: Wireless networks. - : Springer. - 1022-0038 .- 1572-8196. ; 27, s. 3109-
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Journal article (peer-reviewed)abstract
- In a world with increasing traffic demands, wireless technologies aim to meet them by means of new Radio Access Technologies that provide faster connectivity. Such is the case of 4G and 5G. However, in indoor scenarios, where the capabilities of these technologies are significantly affected by the distance to the base station and the materials used in the construction of buildings, Wi-Fi is still the technology of reference thanks to its low cost and easy deployment. In this context, it is usual to find multi-AP Wi-Fi networks whose deployment has been carefully planned. However, the user-AP association decision procedure is not defined by the IEEE 802.11 standard. As a result, vendors choose selfish approaches based on signal strength. This leads to uneven user distributions and nonoptimal resource utilization. To deal with this, densification has been used over the years, but this is expensive as it needs more infrastructure. Moreover, this results in more APs in the same collision domain. To avoid the need for densification, in this paper we introduce WiMCA, a joint SDN-based user association and channel assignment solution for Wi-Fi networks that considers signal strength, channel occupancy and AP load to make better association decisions. Experimental results have demonstrated that, in terms of aggregated goodput, WiMCA outperforms approaches based on signal strength by 55%, providing better user level fairness and accommodating more users and traffic before reaching the point at which densification is needed. © 2021, The Author(s)
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| 10. |
- Gomez, Karina, et al.
(author)
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Measurement-based modelling of power consumption at wireless access network gateways
- 2012
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In: Computer Networks. - : Elsevier. - 1389-1286 .- 1872-7069. ; 56:10, s. 2506-2521
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Journal article (peer-reviewed)abstract
- Improving the energy efficiency of the ICT sector is becoming an ambitious challenge for industries and research communities alike. Understanding how the energy is consumed in each part of an ICT system becomes fundamental in order to minimize the overall energy consumed by the system itself. In this paper, we propose an experimentally-driven approach to (i) characterize typical wireless access network gateways from an energy consumption standpoint and (ii) develop simple and accurate power consumption models for such gateways. In this work we focused our attention on the monitoring, measurement and analysis of the energy consumption patterns of WiFi and WiMAX gateways. Our measurements show that the power consumption of such gateways exhibits a linear dependence on the traffic until a saturation point is reached.
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