نتایج جستجو برای: network slicing

تعداد نتایج: 675273  

2018
Carla Fabiana Chiasserini Claudio Casetti Pantelis A. Frangoudis Adlen Ksentini

Network Slicing allows to simultaneously support the specific needs of vertical industries with a diverse range of networking and computing requirements. Network Functions Virtualization (NFV) has been defined to deploy multiple network services on a common infrastructure. We extend the NFV concept to vertical services, i.e. services implemented on top of network services and providing the appl...

Journal: :Journal of Information Processing 2017

Journal: :IEEE Open Journal of Vehicular Technology 2020

Journal: :IEEE Access 2021

The Fifth Generation (5G) mobile networking coupled with Internet of Things (IoT) can provide innovative solutions for a wide range uses cases. flexibility virtualized, softwarized and multi-tenant infrastructures the high performance promised by 5G technology are key to cope deployment IoT use cases demanded various vertical businesses. Such incur challenging Quality Service (QoS) requirements...

1996
Ingrid Kirschning Hideto Tomabechi Jun-Ichi Aoe

We developed a method called Time-Slicing [1] for the analysis of the speech signal. It enables a neural network to recognize connected speech as it comes, without having to fit the input signal into a fixed time-format, nor label or segment it phoneme by phoneme. The neural network produces an immediate hypothesis of the recognized phoneme and its size is small enough to run even on a PC. To i...

Journal: :CoRR 2017
Anders Ellersgaard Kalør René Guillaume Jimmy Jessen Nielsen Andreas Mueller Petar Popovski

An important novelty of 5G is its role in transforming the industrial production into Industry 4.0. Specifically, Ultra-Reliable Low Latency Communications (URLLC) will, in many cases, enable replacement of cables with wireless connections and bring freedom in designing and operating interconnected machines, robots, and devices. However, not all industrial links will be of URLLC type; e.g. some...

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