716 research outputs found
A MEC-based Extended Virtual Sensing for Automotive Services
Multi-access edge computing (MEC) comes with the promise of enabling low-latency applications and of reducing core network load by offloading traffic to edge service instances. Recent standardization efforts, among which the ETSI MEC, have brought about detailed architectures for the MEC. Leveraging the ETSI model, in this paper we first present a flexible, yet full-fledged, MEC architecture that is compliant with the standard specifications. We then use such architecture, along with the popular OpenAir Interface (OAI), for the support of automotive services with very tight latency requirements. We focus in particular on the Extended Virtual Sensing (EVS) services, which aim at enhancing the sensor measurements aboard vehicles with the data collected by the network infrastructure, and exploit this information to achieve better safety and improved passengers/driver comfort. For the sake of concreteness, we select the intersection control as an EVS service and present its design and implementation within the MEC platform. Experimental measurements obtained through our testbed show the excellent performance of the MEC EVS service against its equivalent cloud-based implementation, proving the need for MEC to support critical automotive services, as well as the benefits of the solution we designed.This work was supported by the European Commission through the H2020 5G-TRANSFORMER project (Project ID 761536). The work of Christian Vitale was also supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 739551 (KIOS CoE) and from the Republic of Cyprus through the Directorate General for Euro-pean Programmes, Coordination, and Development
A MEC-based Extended Virtual Sensing for Automotive Services
Multi-access edge computing (MEC) comes with the promise of enabling low-latency applications and of reducing core network load by offloading traffic to edge service instances. Recent standardization efforts, among which the ETSI MEC, have brought about detailed architectures for the MEC. Leveraging the ETSI model, in this paper we first present a flexible, yet full-fledged, MEC architecture that is compliant with the standard specifications. We then use such architecture, along with the popular OpenAir Interface (OAI), for the support of automotive services with very tight latency requirements. We focus in particular on the Extended Virtual Sensing (EVS) services, which aim at enhancing the sensor measurements aboard vehicles with the data collected by the network infrastructure, and exploit this information to achieve better safety and improved passengers/driver comfort. For the sake of concreteness, we select the intersection control as an EVS service and present its design and implementation within the MEC platform. Experimental measurements obtained through our testbed show the excellent performance of the MEC EVS service against its equivalent cloud-based implementation, proving the need for MEC to support critical automotive services, as well as the benefits of the solution we designed.This work was supported by the European Commission through the H2020 5G-TRANSFORMER project (Project ID 761536). The work of Christian Vitale was also supported by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 739551 (KIOS CoE) and from the Republic of Cyprus through the Directorate General for Euro-pean Programmes, Coordination, and Development
MEC-based Mobility Tracking and Safety Service through IoT
L'abstract è presente nell'allegato / the abstract is in the attachmen
Cooperative Passive Coherent Location: A Promising 5G Service to Support Road Safety
5G promises many new vertical service areas beyond simple communication and
data transfer. We propose CPCL (cooperative passive coherent location), a
distributed MIMO radar service, which can be offered by mobile radio network
operators as a service for public user groups. CPCL comes as an inherent part
of the radio network and takes advantage of the most important key features
proposed for 5G. It extends the well-known idea of passive radar (also known as
passive coherent location, PCL) by introducing cooperative principles. These
range from cooperative, synchronous radio signaling, and MAC up to radar data
fusion on sensor and scenario levels. By using software-defined radio and
network paradigms, as well as real-time mobile edge computing facilities
intended for 5G, CPCL promises to become a ubiquitous radar service which may
be adaptive, reconfigurable, and perhaps cognitive. As CPCL makes double use of
radio resources (both in terms of frequency bands and hardware), it can be
considered a green technology. Although we introduce the CPCL idea from the
viewpoint of vehicle-to-vehicle/infrastructure (V2X) communication, it can
definitely also be applied to many other applications in industry, transport,
logistics, and for safety and security applications
Development and Performance Evaluation of Network Function Virtualization Services in 5G Multi-Access Edge Computing
L'abstract è presente nell'allegato / the abstract is in the attachmen
Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability
Internet-of-Things (IoT) envisions an intelligent infrastructure of networked
smart devices offering task-specific monitoring and control services. The
unique features of IoT include extreme heterogeneity, massive number of
devices, and unpredictable dynamics partially due to human interaction. These
call for foundational innovations in network design and management. Ideally, it
should allow efficient adaptation to changing environments, and low-cost
implementation scalable to massive number of devices, subject to stringent
latency constraints. To this end, the overarching goal of this paper is to
outline a unified framework for online learning and management policies in IoT
through joint advances in communication, networking, learning, and
optimization. From the network architecture vantage point, the unified
framework leverages a promising fog architecture that enables smart devices to
have proximity access to cloud functionalities at the network edge, along the
cloud-to-things continuum. From the algorithmic perspective, key innovations
target online approaches adaptive to different degrees of nonstationarity in
IoT dynamics, and their scalable model-free implementation under limited
feedback that motivates blind or bandit approaches. The proposed framework
aspires to offer a stepping stone that leads to systematic designs and analysis
of task-specific learning and management schemes for IoT, along with a host of
new research directions to build on.Comment: Submitted on June 15 to Proceeding of IEEE Special Issue on Adaptive
and Scalable Communication Network
Slicing on the road: enabling the automotive vertical through 5G network softwarization
The demanding requirements of Vehicle-to-Everything (V2X) applications, such as ultra-low latency, high-bandwidth, highly-reliable communication, intensive computation and near-real time data processing, raise outstanding challenges and opportunities for fifth generation (5G) systems. By allowing an operator to flexibly provide dedicated logical networks with (virtualized) functionalities over a common physical infrastructure, network slicing candidates itself as a prominent solution to support V2X over upcoming programmable and softwarized 5G systems in a business-agile manner. In this paper, a network slicing framework is proposed along with relevant building blocks and mechanisms to support V2X applications by flexibly orchestrating multi-access and edge-dominated 5G network infrastructures, especially with reference to roaming scenarios. Proof of concept experiments using the Mininet emulator showcase the viability and potential benefits of the proposed framework for cooperative driving use cases1812não temMinistério da Ciência, Tecnologia, Inovações e Comunicações - MCTICThe research of Prof. Christian Esteve Rothenberg was partially supported by the H2020 4th
EUBR Collaborative Call, under the grant agreement number 777067 (NECOS - Novel Enablers for Cloud Slicing), funded by the European Commission and the Brazilian Ministry of Science, Technology, Innovation, and Communication (MCTIC) through RNP and CTI
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