IMDEA Networks Institute Digital Repository
Not a member yet
1915 research outputs found
Sort by
Analysis of scaling policies for NFV providing 5G/6G reliability levels with fallible servers
Get PDFThe softwarization of mobile networks enables an efficient use of resources, by dynamically scaling and re-assigning them following variations in demand. Given that the activation of additional servers is not immediate, scaling up resources should anticipate traffic demands to prevent service disruption. At the same time, the activation of more servers than strictly necessary results in a waste of resources, and thus should be avoided. Given the stringent reliability requirements of 5G applications (up to 6 nines) and the fallible nature of servers, finding the right trade-off between efficiency and service disruption is particularly critical. In this paper, we analyze a generic auto-scaling mechanism for communication services, used to de(activate) servers in a cluster, based on occupation thresholds. We model the impact of the activation delay and the finite lifetime of the servers on performance, in terms of power consumption and failure probability. Based on this model, we derive an algorithm to optimally configure the thresholds. Simulation results confirm the accuracy of the model both under synthetic and realistic traffic patterns as well as the effectiveness of the configuration algorithm. We also provide some insights on the best strategy to support an energy-efficient highly-reliable service: deploying a few powerful and reliable machines versus deploying many machines, but less powerful and reliable.TRUEpu
Asymptotically achieving centralized rate on the decentralized Network MISO Channel
Get PDFIn this paper, we analyze the high-SNR regime of the MxK Network MISO channel in which each transmitter has access to a different channel estimate, possibly with different precision. It has been recently shown that, for some regimes, this setting attains the same Degrees-of-Freedom as the ideal centralized setting with perfect Channel State Information (CSI) sharing, in which all the transmitters are endowed with the best estimate available at any transmitter. This result is restricted by the limitations of the Degrees-of-Freedom metric, as it only provides information about the slope of growth of the capacity as a function of the SNR, without any insight about the possible performance at a given SNR. In order to overcome this limitation, we analyze the affine approximation of the rate on the high-SNR regime for this decentralized Network MISO setting for the antenna configurations in which it achieves the Degrees-of-Freedom of the centralized setting. We show that, for a regime of antenna configurations, it is possible to asymptotically attain the same achievable rate as in the ideal centralized scenario. Consequently, it is possible to achieve the beamforming gain of the ideal perfect-CSI-sharing setting even if only a subset of transmitters is endowed with precise CSI, which can be exploited in scenarios such as distributed massive MIMO where the number of transmit antennas is much bigger than the number of served users. This outcome is a consequence of the synergistic compromise between CSI precision at the transmitters and consistency between the locally-computed precoders, which is an inherent trade-off of decentralized settings that does not exist in the centralized CSI configuration. We propose a precoding scheme achieving the previous result, which is built on an uneven structure in which some transmitters reduce the precision of their own precoding vector for the sake of using transmission parameters that can be more easily predicted by the other transmitters.TRUEpu
A Migration Path Toward Green Edge Gaming
Get PDF5G and beyond 5G networks will allow novel use cases by placing constrained computing nodes at the edge, following the Multi-access Edge Computing (MEC) paradigm. Edge nodes could be partially powered by intermittent renewable energies, leading to the possibility of having time-varying computing capacities. In this scenario, we tackle the problem of how to support gaming at the edge of the cellular network. Moving
cloud-based games to the edge could be a premium service for end-users, thanks to reduced latency and higher bandwidth. The goal of our paper is to design a scheme that maximizes the utility of a service/infrastructure provider in a MEC scenario, with time-varying MEC nodes capacities powered by intermittent renewable energies. We formulate a multi-dimensional integer linear programming problem, proving that it is NP Hard in the strong sense. We prove that our problem is sub-modular and propose an efficient heuristic, GREENING, which considers the allocation of gaming sessions and their migration. Through simulations, we show that our heuristic achieves performance close to what achievable by a solver, except with extremely lower complexity, and performs near-optimally, 20% better than stateof-the-art algorithms in terms of system utility. We also show that our scheme is compliant with currently adopted standards by ETSI and meant to support novel networking principles like network slicing.TRUEpu
Situational Collective Perception: Adaptive and Efficient Collective Perception in Future Vehicular Systems
Get PDFWith the emergence of Vehicle-to-everything (V2X) communication, vehicles and other road users can perform Collective Perception (CP), whereby they exchange their individually detected environment to increase the collective awareness of the surrounding environment. To detect and classify the surrounding
environmental objects, preprocessed sensor data (e.g., point-cloud data generated by a Lidar) in each
vehicle is fed and classified by onboard Deep Neural Networks (DNNs). The main weakness of these
DNNs is that they are commonly statically trained with context-agnostic data sets, limiting their adaptability to specific environments. This may eventually prevent the detection of objects, causing safety disasters. Inspired by the Federated Learning (FL) approach, in this work we tailor a collective perception architecture, introducing Situational Collective Perception (SCP) based on dynamically trained
and situational DNNs, and enabling adaptive and efficient collective perception in future vehicular networks.TRUEpu
Vector Coded Caching Greatly Enhances Massive MIMO
Get PDFThe use of vector coded caching has been shown to provide important gains and, more importantly, to alleviate the impact of the file-size constraint, which prevents coded caching from obtaining its ideal gains in practical settings. In this work, we analyze the performance of vector coded caching in the massive MIMO regime, aiming at understanding the benefits that allowing users to cache a practical amount of data could bring to realistic settings in such massive MIMO regime. In particular, we separately consider two linear precoding schemes and analyze the corresponding throughput, for which we derive simple but precise upper and lower bounds. These bounds enable us to characterize the delivery speed-up gain over the uncoded caching setting when the CSI acquisition costs are taken into account. Numerical results demonstrate the tightness of the derived bounds and show a significant boost over uncoded caching and the standard cacheless setting.Comunidad de Madrid - Atracción de talentoTRUEpu
Impact of Later-Stages COVID-19 Response Measures on Spatiotemporal Mobile Service Usage
Get PDFThe COVID-19 pandemic has affected our lives and how we use network infrastructures in an unprecedented way. While early studies have started shedding light on the link between COVID-19 containment measures and mobile network traffic, we presently lack a clear understanding of the implications of the virus outbreak, and of our reaction to it, on the usage of mobile apps. We contribute to closing this gap, by investigating how the spatiotemporal usage of mobile services has evolved through different response measures enacted in France during a continued seven-month period in 2020 and 2021. Our work complements previous studies in several ways: (i) it delves into individual service dynamics, whereas previous studies have not gone beyond broad service categories; (ii) it encompasses different types of containment strategies, allowing to observe their diverse effects on mobile traffic; (iii) it covers both spatial and temporal behaviors, providing a comprehensive view on the phenomenon. These elements of novelty let us lay new insights on how the demands for hundreds of different mobile services are reacting to the new environment set forth by the pandemics.TRUEpu
Vector Coded Caching Multiplicatively Increases the Throughput of Realistic Downlink Systems
Get PDFThe recent introduction of vector coded caching has revealed that multi-rank transmissions in the presence of receiver-side cache content can dramatically ameliorate the file-size bottleneck of coded caching and substantially boost performance in error-free wire-like channels. In this work, we employ large-matrix analysis to explore the effect of vector coded caching in realistic wireless multi-antenna downlink systems. For a given downlink MISO system already optimized to exploit both multiplexing and beamforming gains, and for a fixed set of antenna and SNR resources, our analysis answers a simple question: What is the multiplicative throughput boost obtained from introducing reasonably sized receiver-side caches that can pre-store information content? The derived closed-form expressions capture various linear precoders, and a variety of practical considerations such as power dissemination across signals, realistic SNR values, as well as feedback costs. The schemes are very simple (we simply collapse precoding vectors into a single vector), and the recorded gains are notable. For example, for 32 transmit antennas, a received SNR of 20 dB, a coherence bandwidth of 300 kHz, a coherence period of 40 ms, and under realistic file-size and cache-size constraints, vector coded caching is here shown to offer a multiplicative throughput boost of about 310% with ZF/RZF precoding and a 430% boost in the performance of already optimized MF-based (cacheless) systems. Interestingly, vector coded caching also accelerates channel hardening to the benefit of feedback acquisition, often surpassing 540% gains over traditional hardening-constrained cacheless downlink systems.Comunidad de Madrid - Atracción de talentoTRUEpu
Energy Efficient Sampling Policies for Edge Computing Feedback Systems
Get PDFWe study the problem of finding efficient sampling policies in an edge-based feedback system, where sensor samples are
offloaded to a back-end server that processes them and generates feedback to a user. Sampling the system at maximum frequency
results in the detection of events of interest with minimum delay but incurs higher energy costs due to the communication and
processing of redundant samples. On the other hand, lower sampling frequency results in higher delay in detecting the event, thus
increasing the idle energy usage and degrading the quality of experience. We quantify this trade-off as a weighted function between
the number of samples and the sampling interval. We solve the minimisation problem for exponential and Rayleigh distributions, for the
random time to the event of interest. We prove the convexity of the objective functions by using novel techniques, which can be of
independent interest elsewhere. We argue that adding an initial offset to the periodic sampling can further reduce the energy
consumption and jointly compute the optimum offset and sampling interval. We apply our framework to two practically relevant
applications and show energy savings of up to 36% when compared to an existing periodic scheme.TRUEpu
Leakage of Sensitive Information to Third-Party Voice Applications
Get PDFIn this paper we investigate the issue of sensitive information leak- age to third-party voice applications in voice assistant ecosystems. We focus specifically on leakage of sensitive information via the conversational interface. We use a bespoke testing infrastructure to investigate leakage of sensitive information via the conversational interface of Google Actions and Alexa Skills. Our work augments prior work in this area to consider not only specific categories of personal data, but also other types of potentially sensitive in- formation that may be disclosed in voice-based interactions with third-party voice applications. Our findings indicate that current privacy and security measures for third-party voice applications are not sufficient to prevent leakage of all types of sensitive information via the conversational interface. We make key recommendations for the redesign of voice assistant architectures to better prevent leakage of sensitive information via the conversational interface of third-party voice applications in the future.RYC-2020-029401-ITRUEpu
Edge-based Platoon Control
Get PDFPlatooning of cars or trucks is one of the most relevant applications of autonomous driving, since it has the potential to greatly improve efficiency in road utilization and fuel consumption. Traditional proposals of vehicle platoon- ing were based on distributed architectures with computation on board platoon vehicles and direct vehicle-to-vehicle (V2V) communications (or Dedicated Short Range Communication - DSRC), possibly with the support of roadside 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 com- puting (MEC) paradigm, the possibility emerges of placing control of platoons on MEC, with several significant advantages with respect to the V2V approach. For this reason, in this article we investigate the feasibility of vehicle platooning in an edge-based 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, as well as of engines and inertia of vehicles, large platoons can be effectively controlled by MEC hosts. On the one hand, we unveil that platooning on the edge is a viable and robust solution. On the other hand, we also shed light on the necessity to consider realistic characteristics of vehicles and speed profiles, since they can yield severe, yet not critical, performance degradation with respect to simple models.Ramon y Cajal grant RYC-2014-16285 from the Spanish Ministry of Economy and CompetitivenessThe work was supported by the Spanish Ministry of Science and Innovation grant PID2019-109805RB-I00 (ECID).TRUEpu