IMDEA Networks Institute Digital Repository
Not a member yet
1915 research outputs found
Sort by
Achieving Per-Flow Satisfaction with Multi-Path D2D
Get PDFDevice-to-Device (D2D) communication allows for users placed in a cell to establish direct connections with each other using several connection modes. In this paper, we propose Multi-Path D2D (MPD2D), a mathematical optimization framework that accounts for the availability of D2D modes under the requirements dictated by a process of flow requests. MPD2D selects the combination of cellular and D2D links that boosts network performance as much as possible. We consider Underlay and Overlay as Inband D2D modes reusing cellular frequencies with scheduled resources and the Outband D2D mode exploiting WLAN frequencies and the 802.11 random access scheme to complement cellular resources. We model throughput, energy consumption, interference, and per-flow network requirements, so to define a network utility function that accounts for throughput and power efficiency. Moreover, we formulate a user satisfaction metric that accounts for the history of users within the cell. Integrating such a metric in a throughput optimization problem is lightweight yet very effective to drive towards almost complete fairness. Our optimization scheme is formulated as a Binary Non-Linear Program, which results in higher throughput performance in comparison to other state-of-the-art solutions we have tested. Finally, we propose two effective heuristics, whose performance is near-optimal, whereas their complexity scales polynomially with the number of users.pu
AZTEC: Anticipatory Capacity Allocation for Zero-Touch Network Slicing
Get PDFThe combination of network softwarization with network slicing enables the provisioning of very diverse services over the same network infrastructure. However, it also creates a complex environment where the orchestration of network resources cannot be guided by traditional, human-in-the-loop network management approaches. New solutions that perform these tasks automatically and in advance are needed, paving the way to zero-touch network slicing. In this paper, we propose AZTEC, a data- driven framework that effectively allocates capacity to individual slices by adopting an original multi-timescale forecasting model. Hinging on a combination of Deep Learning architectures and a traditional optimization algorithm, AZTEC anticipates resource assignments that minimize the comprehensive management costs induced by resource overprovisioning, instantiation and reconfiguration, as well as by denied traffic demands. Experiments with real-world mobile data traffic show that AZTEC dynamically adapts to traffic fluctuations, and largely outperforms state-of-the-art solutions for network resource orchestration.TRUEpu
Event-based Vision: Understanding Network Traffic Characteristics
Get PDFEvent-based vision fosters a new way of sensing reality. Event-based cameras work radically differently compared to legacy frame-based cameras because they continuously measure brightness changes at a per-pixel granularity (i.e., events) rather than snapshots of intensity measurements (i.e., frames). Event-based cameras are applied in robotics and augmented and virtual reality applications due to their properties of low-latency, high temporal resolution and dynamic range. For example, they greatly improve unmanned aerial vehicle (UAV) navigation and collision avoidance. While event-based vision is currently restricted to local devices, in the near future applications involving distributed systems will gain momentum, such as the coordination of swarms of UAVs or robots. However, the network traffic characteristics of event-based vision systems are largely unexplored. In this paper, we aim to fill this gap by providing the first study of network traffic generated by event-based cameras. To this end, we employ publicly available data sets and experimentally study properties like the impact of packet/event losses on typical computer vision operations like tracking, and the implications of medium access under contention. We find that complex scenes that incur a high event generation rate are more robust against packet loss due to transmission errors or wireless contention. Conversely, packet loss or delay are more harmful to tracking and visualization operations when the event generation rate is small.TRUEpu
Platooning on the Edge
Get PDFlatooning of cars or trucks is one of the most relevant applica- tions of autonomous driving, since it has the potential to greatly improve efficiency in road utilization and fuel consumption. Tradi- tional proposals of vehicle platooning were based on distributed architectures with computation on board platoon vehicles and di- rect vehicle-to-vehicle (V2V) communications (or Dedicated Short Range Communication - DSRC), possibly with the support of road- side units. However, with the introduction of the 5G technology and of computing elements at the edge of the network, according to the multi-access edge computing (MEC) paradigm, the possibility emerges of a centralized control of platoons through MEC, with several significant advantages with respect to the V2V approach. For this reason, in this paper we investigate the feasibility of vehicle platooning in a centralized scenario where the control of vehicle speed and acceleration is managed by the network through its MEC facilities, possibly with a platooning-as-a-service (PaaS) paradigm. Using a detailed simulator, we show that, with realistic values of latency and packet loss probability, large platoons can be effectively controlled by MEC hosts.TRUEpu
OSM PoC 10 Automated Deployment of an IP Telephony Service on UAVs using OSM
No full textPoC Key Takeaways
- The PoC demonstrates the practical feasibility of automating the deployment of telecommunication services over resource-constrained devices, particularly UAVs.
- OSM is intended to support the orchestration of network services over the resource-constrained UAVs.
- The procedure details the different steps to build a functional NFV environment, based on resource-constrained platforms, and deploys a funcional IP telephony service.
- Single board computers (Raspberry Pi model 3B+) are onboarded on small-size drones, serving as compute nodes.
- The PoC is based on open-source technologies (OSM and OpenStack).
- Scripts to support the pre-configuration of the resource-constrained platforms are made available to facilitate the reproducibility of the experiment.
- The detailed procedure could potentially be adapted and used in other environments in which resource-constrained devices might be available.
- The PoC includes a flight procedure. If this is reproduced, the experimenter should be sure to follow the appropriate security measures and the corresponding regulatory statements.
ETSI awarded the best Proof of Concept (PoC) demonstration of OpenSourceMANO (OSM, a system that is standardized by ETSI) during the Release EIGHT cycle with OSM PoC#10 Automated Deployment of an IP Telephony Service on Unmanned Aerial Vehicles using OSM to a group of researchers from University Carlos III of Madrid and IMDEA Networks.The Network Function Virtualization (NFV) paradigm is one of the key-enabling technologies in the development of the 5th generation of mobile networks. This technology aims at lessening the dependence on hardware in the provision of network functions and services by using virtualization techniques that allow the softwarization of those functionalities over an abstraction layer. In this context, there is increasing interest in exploring the potential of unmanned aerial vehicles (UAVs) to offer a flexible platform capable of enabling cost-effective NFV operations over delimited geographic areas.
To demonstrate the practical feasibility of utilizing NFV technologies in UAV platforms, the PoC presents a functional NFV environment based on open source technologies, in which a set of small UAVs onboard the computational resources that support the deployment of moderately complex network services. In particular, the PoC showcases the automatic deployment of an IP telephony service through OSM over a network of interconnected UAVs, leveraging the capacities of the configured NFV environment.TRUEpu
Non-linearity of LEDs for VLC IoT applications
Get PDFVisible light communication (VLC) is a promising technology to satisfy the increasing demand of wireless communication services. The generalized idea of modulating the signal within the light-emitting diode (LED) linear region is considered the de-facto approach for high-speed communication. This paper shows that this is not the most appropriate choice for the Internet of Things (IoT) applications, where the communication range is of greater importance once a sufficient communication rate is reached. In order to improve the communication range, we propose to exploit the full non-linear region of an LED transceiver while maintaining constant illumination. We show that working in the full LED region can provide received electrical power gains in the mobile IoT tag of around 15 dB.We achieve this without affecting the communication rate for IoT applications, and at the penalty of about 10% increase in the total energy consumption of LEDs.We further demonstrate that exploiting the non-linear region of LEDs is beneficial for mobile tags that employ a solar cell for receiving data at high data rates.TRUEpu
Identifying Common Periodicities in Mobile Service Demands with Spectral Analysis
Get PDFIn this paper, we investigate the existence and prevalence of comparable dynamics in the temporal fluctuations for the traffic demands generated by mobile applications. To this end, we hinge upon a spectral analysis framework, by computing Discrete Fourier Transforms of the typical demands for tens of popular mobile services observed in an operational metropolitan-scale network. We filter, cluster, and analyse hundreds of frequency components, and identify a substantial set of regular patterns that are common across most service demands. We also unveil how several mobile services defy classification, and have instead highly distinguishing temporal dynamics.TRUEpu
Electrosense+: Crowdsourcing Radio Spectrum Decoding using IoT Receivers
Get PDFWeb spectrum monitoring systems based on crowdsourcing have recently gained popularity. These systems are however limited to applications of interest for governamental organizations or telecom providers, and only provide aggregated information about spectrum statistics. The result is that there is a lack of interest for layman users to participate, which limits its widespread deployment. We present Electrosense+ which addresses this challenge and creates a general-purpose and open platform for spectrum monitoring using low-cost, embedded, and software-defined spectrum IoT sensors. Electrosense+ allows users to remotely decode specific parts of the radio spectrum. It builds on the centralized architecture of its predecessor, Electrosense, for controlling and monitoring the spectrum IoT sensors, but implements a real-time and peer-to-peer communication system for scalable spectrum data decoding. We propose different mechanisms to incentivize the participation of users for deploying new sensors and keep them operational in the Electrosense network. As a reward for the user, we propose an incentive accounting system based on virtual tokens to encourage the participants to host IoT sensors. We present
the new Electrosense+ system architecture and evaluate its performance at decoding various wireless signals, including FM radio, AM radio, ADS-B, AIS, LTE, and ACARS.pu
Constrained Network Slicing Games: Achieving service guarantees and network efficiency
Get PDFNetwork slicing is a key capability for next generation mobile networks. It enables one to cost effectively customize logical networks over a shared infrastructure. A critical component of network slicing is resource allocation, which needs to ensure that slices receive the resources needed to support their services while optimizing network efficiency. In this paper, we propose a novel approach to slice-based resource allocation named Guaranteed seRvice Efficient nETwork slicing (GREET). The underlying concept is to set up a constrained resource allocation game, where (i) slices unilaterally optimize their allocations to best meet their (dynamic)customer loads, while (ii) constraints are imposed to guarantee that, if they wish so, slices receive a pre-agreed share of the network resources. The resulting game is a variation of the well-known Fisher market, where slices are provided a budget to contend for network resources (as in a traditional Fisher market), but (unlike a Fisher market) prices are constrained for some resources to provide the desired guarantees. In this way, GREET combines the advantages of a share-based approach (high efficiency by flexible sharing) and reservation-based ones (which provide guarantees by assigning a fixed amount of resources). We characterize the Nash equilibrium, best response dynamics, and propose a practical slice strategy with provable convergence properties. Extensive simulations exhibit substantial improvements over network slicing state-of-the-art benchmarks.TRUEpu
Processing ANN Traffic Predictions for RAN Energy Efficiency
Get PDFThe field of networking, like many others, is experiencing a peak
of interest in the use of Machine Learning (ML) algorithms. In
this paper, we focus on the application of ML tools to resource
management in a portion of a Radio Access Network (RAN) and, in
particular, to Base Station (BS) activation and deactivation, aiming at reducing energy consumption while providing enough capacity to satisfy the variable traffic demand generated by end users. In order to properly decide on BS (de)activation, traffic predictions are needed, and Artificial Neural Networks (ANN) are used for this purpose. Since critical BS (de)activation decisions are not taken in proximity of minima and maxima of the traffic patterns, high accuracy in the traffic estimation is not required at those times, but only close to the times when a decision is taken. This calls for careful processing of the ANN traffic predictions to increase the probability of correct decision. Numerical performance results in terms of energy saving and traffic lost due to incorrect BS deactivations are obtained by simulating algorithms for traffic predictions processing, using real traffic as input. Results suggest that good performance trade-offs can be achieved even in presence of non-negligible traffic prediction errors, if these forecasts are properly processed.TRUEpu