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Andrea Zanella

Publications and source records attributed to Andrea Zanella.

At least 73 records · Page 4Linked to original sources
arXiv2019

A QUIC Implementation for ns-3

Quick UDP Internet Connections (QUIC) is a recently proposed transport protocol, currently being standardized by the Internet Engineering Task Force (IETF). It aims at overcoming some of the shortcomings of TCP, while maintaining the logic related to flow and congestion control, retransmissions and acknowledgments. It supports multiplexing of multiple application layer streams in the same connection, a more refined selective acknowledgment scheme, and low-latency connection establishment. It also integrates cryptographic functionalities in the protocol design. Moreover, QUIC is deployed at the application layer, and encapsulates its packets in UDP datagrams. Given the widespread interest in the new QUIC features, we believe that it is important to provide to the networking community an implementation in a controllable and isolated environment, i.e., a network simulator such as ns-3, in which it is possible to test QUIC's performance and understand design choices and possible limitations. Therefore, in this paper we present a native implementation of QUIC for ns-3, describing the features we implemented, the main assumptions and differences with respect to the QUIC Internet Drafts, and a set of examples.

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arXiv2019

An Adaptive Broadcasting Strategy for Efficient Dynamic Mapping in Vehicular Networks

In this work, we face the issue of achieving an efficient dynamic mapping in vehicular networking scenarios, i.e., to obtain an accurate estimate of the positions and trajectories of connected vehicles in a certain area. State of the art solutions are based on the periodic broadcasting of the position information of the network nodes, with an inter-transmission period set by a congestion control scheme. However, the movements and maneuvers of vehicles can often be erratic, making transmitted data inaccurate or downright misleading. To address this problem, we propose to adopt a dynamic transmission scheme based on the actual positioning error, sending new data when the estimate passes a preset error threshold. Furthermore, the proposed method adapts the error threshold to the operational context according to a congestion control algorithm that limits the collision probability among broadcast packet transmissions. This threshold-based strategy can reduce the network load by avoiding the transmission of redundant messages, and is shown to improve the overall positioning accuracy by more than 20% in realistic urban scenarios.

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arXiv2019

A Survey on Recent Advances in Transport Layer Protocols

Over the years, the Internet has been enriched with new available communication technologies, for both fixed and mobile networks and devices, exhibiting an impressive growth in terms of performance, with steadily increasing available data rates. The Internet research community has kept trying to evolve the transport layer protocols to match the capabilities of modern networks, in order to fully reap the benefits of the new communication technologies. This paper surveys the main novelties related to transport protocols that have been recently proposed, identifying three main research trends: (i) the evolution of congestion control algorithms, to target optimal performance in challenging scenarios, possibly with the application of machine learning techniques; (ii) the proposal of brand new transport protocols, alternative to TCP and implemented in the user-space; and (iii) the introduction of multi-path capabilities at the transport layer.

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arXiv2019

Investigating Value of Information in Future Vehicular Communications

The next generations of vehicles are expected to be equipped with sophisticated sensors to support advanced automotive services. The large volume of data generated by such applications will likely put a strain on the vehicular communication technologies, which may be unable to guarantee the required quality of service. In this scenario, it is fundamental to assess the value of information (VoI) provided by each data source, to prioritize the transmissions that have greatest importance for the target applications. In this paper, we characterize VoI in future vehicular networks, and investigate efficient data dissemination methods to tackle capacity issues. Through a simulation study, we show how analytic hierarchy multicriteria decision processes can be exploited to determine the value of sensory observations as a function of space, time, and quality criteria.

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arXiv2019

Path Loss Models for V2V mmWave Communication: Performance Evaluation and Open Challenges

Recently, millimeter wave (mmWave) bands have been investigated as a means to enhance automated driving and address the challenging data rate and latency demands of emerging automotive applications. For the development of those systems to operate in bands above 6 GHz, there is a need to have accurate channel models able to predict the peculiarities of the vehicular propagation at these bands, especially as far as Vehicle-to-Vehicle (V2V) communications are concerned. In this paper, we validate the channel model that the 3GPP has proposed for NR-V2X systems, which (i) supports deployment scenarios for urban/highway propagation, and (ii) incorporates the effects of path loss, shadowing, line of sight probability, and static/dynamic blockage attenuation. We also exemplify the impact of several automotive-specific parameters on the overall network performance considering realistic system-level simulation assumptions for typical scenarios. Finally, we highlight potential inconsistencies of the model and provide recommendations for future measurement campaigns in vehicular environments.

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arXiv2019

A Thorough Study of LoRaWAN Performance Under Different Parameter Settings

LoRaWAN is an emerging Low-Power Wide Area Network (LPWAN) technology, which is gaining momentum thanks to its flexibility and ease of deployment. Conversely to other LPWAN solutions, LoRaWAN indeed permits the configuration of several network parameters that affect different network performance indexes, such as energy efficiency, fairness, and capacity, in principle making it possible to adapt the network behavior to the specific requirements of the application scenario. Unfortunately, the complex and sometimes elusive interactions among the different network components make it rather difficult to predict the actual effect of a certain parameters setting, so that flexibility can turn into a stumbling block if not deeply understood. In this paper we shed light on such complex interactions, by observing and explaining the effect of different parameters settings in some illustrative scenarios. The simulation-based analysis reveals various trade-offs and highlights some inefficiencies in the design of the LoRaWAN standard. Furthermore, we show how significant performance gains can be obtained by wisely setting the system parameters, possibly in combination with some novel network management policies.

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arXiv2019

A Framework to Assess Value of Information in Future Vehicular Networks

Vehicles are becoming increasingly intelligent and connected, incorporating more and more sensors to support safer and more efficient driving. The large volume of data generated by such sensors, however, will likely saturate the capacity of vehicular communication technologies, making it challenging to guarantee the required quality of service. In this perspective, it is essential to assess the value of information (VoI) provided by each data source, to prioritize the transmissions that have the greatest importance for the target applications. In this paper, we propose and evaluate a framework that uses analytic hierarchy multicriteria decision processes to predict VoI based on space, time, and quality attributes. Our results shed light on the impact of the propagation scenario, the sensor resolution, the type of observation, and the communication distance on the value assessment performance. In particular, we show that VoI evolves at different rates as a function of the target application's characteristics.

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arXiv2019

Quality-Aware Broadcasting Strategies for Position Estimation in VANETs

The dissemination of vehicle position data all over the network is a fundamental task in Vehicular Ad Hoc Network (VANET) operations, as applications often need to know the position of other vehicles over a large area. In such cases, inter-vehicular communications should be exploited to satisfy application requirements, although congestion control mechanisms are required to minimize the packet collision probability. In this work, we face the issue of achieving accurate vehicle position estimation and prediction in a VANET scenario. State of the art solutions to the problem try to broadcast the positioning information periodically, so that vehicles can ensure that the information their neighbors have about them is never older than the inter-transmission period. However, the rate of decay of the information is not deterministic in complex urban scenarios: the movements and maneuvers of vehicles can often be erratic and unpredictable, making old positioning information inaccurate or downright misleading. To address this problem, we propose to use the Quality of Information (QoI) as the decision factor for broadcasting. We implement a threshold-based strategy to distribute position information whenever the positioning error passes a reference value, thereby shifting the objective of the network to limiting the actual positioning error and guaranteeing quality across the VANET. The threshold-based strategy can reduce the network load by avoiding the transmission of redundant messages, as well as improving the overall positioning accuracy by more than 20% in realistic urban scenarios.

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arXiv2019

LTE and Millimeter Waves for V2I Communications: an End-to-End Performance Comparison

The Long Term Evolution (LTE) standard enables, besides cellular connectivity, basic automotive services to promote road safety through vehicle-to-infrastructure (V2I) communications. Nevertheless, stakeholders and research institutions, driven by the ambitious technological advances expected from fully autonomous and intelligent transportation systems, have recently investigated new radio technologies as a means to support vehicular applications. In particular, the millimeter wave (mmWave) spectrum holds great promise because of the large available bandwidth that may provide the required link capacity. Communications at high frequencies, however, suffer from severe propagation and absorption loss, which may cause communication disconnections especially considering high mobility scenarios. It is therefore important to validate, through simulations, the actual feasibility of establishing V2I communications in the above-6 GHz bands. Following this rationale, in this paper we provide the first comparative end-to-end evaluation of the performance of the LTE and mmWave technologies in a vehicular scenario. The simulation framework includes detailed measurement-based channel models as well as the full details of MAC, RLC and transport protocols. Our results show that, although LTE still represents a promising access solution to guarantee robust and fair connections, mmWaves satisfy the foreseen extreme throughput demands of most emerging automotive applications.

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arXiv2018

Classification of grasping tasks based on EEG-EMG coherence

This work presents an innovative application of the well-known concept of cortico-muscular coherence for the classification of various motor tasks, i.e., grasps of different kinds of objects. Our approach can classify objects with different weights (motor-related features) and different surface frictions (haptics-related features) with high accuracy (over 0:8). The outcomes presented here provide information about the synchronization existing between the brain and the muscles during specific activities; thus, this may represent a new effective way to perform activity recognition.

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arXiv2018

On the Feasibility of Integrating mmWave and IEEE 802.11p for V2V Communications

Recently, the millimeter wave (mmWave) band has been investigated as a means to support the foreseen extreme data rate demands of emerging automotive applications, which go beyond the capabilities of existing technologies for vehicular communications. However, this potential is hindered by the severe isotropic path loss and the harsh propagation of high-frequency channels. Moreover, mmWave signals are typically directional, to benefit from beamforming gain, and require frequent realignment of the beams to maintain connectivity. These limitations are particularly challenging when considering vehicle-to-vehicle (V2V) transmissions, because of the highly mobile nature of the vehicular scenarios, and pose new challenges for proper vehicular communication design. In this paper, we conduct simulations to compare the performance of IEEE 802.11p and the mmWave technology to support V2V networking, aiming at providing insights on how both technologies can complement each other to meet the requirements of future automotive services. The results show that mmWave-based strategies support ultra-high transmission speeds, and IEEE 802.11p systems have the ability to guarantee reliable and robust communications.

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arXiv2018

Performance Study of LTE and mmWave in Vehicle-to-Network Communications

A key enabler for the emerging autonomous and cooperative driving services is high-throughput and reliable Vehicle-to-Network (V2N) communication. In this respect, the millimeter wave (mmWave) frequencies hold great promises because of the large available bandwidth which may provide the required link capacity. However, this potential is hindered by the challenging propagation characteristics of high-frequency channels and the dynamic topology of the vehicular scenarios, which affect the reliability of the connection. Moreover, mmWave transmissions typically leverage beamforming gain to compensate for the increased path loss experienced at high frequencies. This, however, requires fine alignment of the transmitting and receiving beams, which may be difficult in vehicular scenarios. Those limitations may undermine the performance of V2N communications and pose new challenges for proper vehicular communication design. In this paper, we study by simulation the practical feasibility of some mmWave-aware strategies to support V2N, in comparison to the traditional LTE connectivity below 6 GHz. The results show that the orchestration among different radios represents a viable solution to enable both high-capacity and robust V2N communications.

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arXiv2018

Coverage and Connectivity Analysis of Millimeter Wave Vehicular Networks

The next generations of vehicles will require data transmission rates in the order of terabytes per driving hour, to support advanced automotive services. This unprecedented amount of data to be exchanged goes beyond the capabilities of existing communication technologies for vehicular communication and calls for new solutions. A possible answer to this growing demand for ultra-high transmission speeds can be found in the millimeter-wave (mmWave) bands which, however, are subject to high signal attenuation and challenging propagation characteristics. In particular, mmWave links are typically directional, to benefit from the resulting beamforming gain, and require precise alignment of the transmitter and the receiver beams, an operation which may increase the latency of the communication and lead to deafness due to beam misalignment. In this paper, we propose a stochastic model for characterizing the beam coverage and connectivity probability in mmWave automotive networks. The purpose is to exemplify some of the complex and interesting tradeoffs that have to be considered when designing solutions for vehicular scenarios based on mmWave links. The results show that the performance of the automotive nodes in highly mobile mmWave systems strictly depends on the specific environment in which the vehicles are deployed, and must account for several automotive-specific features such as the nodes speed, the beam alignment periodicity, the base stations density and the antenna geometry.

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arXiv2017

Uncoordinated access schemes for the IoT: approaches, regulations, and performance

Internet of Things (IoT) devices communicate using a variety of protocols, differing in many aspects, with the channel access method being one of the most important. Most of the transmission technologies explicitly designed for IoT and Machine-to-Machine (M2M) communication use either an ALOHA-based channel access or some type of Listen Before Talk (LBT) strategy, based on carrier sensing. In this paper, we provide a comparative overview of the uncoordinated channel access methods for IoT technologies, namely ALOHA-based and LBT schemes, in relation with the ETSI and FCC regulatory frameworks. Furthermore, we provide a performance comparison of these access schemes, both in terms of successful transmissions and energy efficiency, in a typical IoT deployment. Results show that LBT is effective in reducing inter-node interference even for long-range transmissions, though the energy efficiency can be lower than that provided by ALOHA methods. The adoption of rate-adaptation schemes, furthermore, lowers the energy consumption while improving the fairness among nodes at different distances from the receiver. Coexistence issues are also investigated, showing that in massive deployments LBT is severely affected by the presence of ALOHA devices in the same area.

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arXiv2017

Complex Systems Science meets 5G and IoT

We propose a new paradigm for telecommunications, and develop a framework drawing on concepts from information (i.e., different metrics of complexity) and computational (i.e., agent based modeling) theory, adapted from complex system science. We proceed in a systematic fashion by dividing network complexity understanding and analysis into different layers. Modelling layer forms the foundation of the proposed framework, supporting analysis and tuning layers. The modelling layer aims at capturing the significant attributes of networks and the interactions that shape them, through the application of tools such as agent-based modelling and graph theoretical abstractions, to derive new metrics that holistically describe a network. The analysis phase completes the core functionality of the framework by linking our new metrics to the overall network performance. The tuning layer augments this core with algorithms that aim at automatically guiding networks toward desired conditions. In order to maximize the impact of our ideas, the proposed approach is rooted in relevant, near-future architectures and use cases in 5G networks, i.e., Internet of Things (IoT) and self-organizing cellular networks.

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arXiv2017

Data Aggregation and Packet Bundling of Uplink Small Packets for Monitoring Applications in LTE

In cellular massive Machine-Type Communications (MTC), a device can transmit directly to the base station (BS) or through an aggregator (intermediate node). While direct device-BS communication has recently been in the focus of 5G/3GPP research and standardization efforts, the use of aggregators remains a less explored topic. In this paper we analyze the deployment scenarios in which aggregators can perform cellular access on behalf of multiple MTC devices. We study the effect of packet bundling at the aggregator, which alleviates overhead and resource waste when sending small packets. The aggregators give rise to a tradeoff between access congestion and resource starvation and we show that packet bundling can minimize resource starvation, especially for smaller numbers of aggregators. Under the limitations of the considered model, we investigate the optimal settings of the network parameters, in terms of number of aggregators and packet-bundle size. Our results show that, in general, data aggregation can benefit the uplink massive MTC in LTE, by reducing the signalling overhead.

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arXiv2017

X-TCP: A Cross Layer Approach for TCP Uplink Flows in mmWave Networks

Millimeter wave frequencies will likely be part of the fifth generation of mobile networks and of the 3GPP New Radio (NR) standard. MmWave communication indeed provides a very large bandwidth, thus an increased cell throughput, but how to exploit these resources at the higher layers is still an open research question. A very relevant issue is the high variability of the channel, caused by the blockage from obstacles and the human body. This affects the design of congestion control mechanisms at the transport layer, and state-of-the-art TCP schemes such as TCP CUBIC present suboptimal performance. In this paper, we present a cross layer approach for uplink flows that adjusts the congestion window of TCP at the mobile equipment side using an estimation of the available data rate at the mmWave physical layer, based on the actual resource allocation and on the Signal to Interference plus Noise Ratio. We show that this approach reduces the latency, avoiding to fill the buffers in the cellular stack, and has a quicker recovery time after RTO events than several other TCP congestion control algorithms.

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