1,721,541 research outputs found
Present-day Verticals and Where to Find Them: A Data-driven Study on the Transition to 5G
Full text linkMuch of the research about 5G networks deals with emerging or upcoming applications, e.g., self-driving cars and virtual reality. In this paper, we focus on present-day Internet services and assess which of them can benefit the most integration within 5G, i.e., which of today's service providers are the most likely to become 5G verticals. To this end, we leverage a large-scale, real-world, crowd-sourced dataset representing the data required by thousands of smartphone apps, and study the data rate and sparseness associated with each app. We argue that high-data rate, low-sparseness apps have the most to gain from 5G integration, and find that this category includes not only video streaming, but also peer-to-peer file transfer and mobile gaming applications.This work is supported by the European Commission through the H2020 5G-TRANSFORMER project (Project ID 761536
Energy-efficient Coding and Error Control for Wireless Video-surveillance Networks
No full textIn this paper, we address the design of data processing and error control strategies for a wireless sensor network for video-surveillance applications, so as to optimize its performance in terms of energy consumption, information delivery delay, and information quality. First, we suggest a video coding strategy based on intelligent distributed processing, which yields very low power consumption. Then, we investi- gate the interactions between energy consumption, quality, and delay, and analyze the system performance when ARQ- and FEC-based error-control techniques are applied. As a result, we propose an optimal con- figuration for wireless video-surveillance networks which adapts to the radio channel state by effectively implementing FEC and ARQ techniques
An Analytical Model for Wireless Sensor Networks with Sleeping Nodes
No full textWe consider a wireless sensor network whose nodes may enter the so-called sleep mode, corresponding to low power consumption and reduced operational capabilities. We develop a Markov model of the network representing: 1) the behavior of a single sensor as well as the dynamics of the entire network, 2) the channel contention among sensors, and 3) the data routing through the network. We use this model to evaluate the system performance in terms of energy consumption, network capacity, and data delivery delay. Analytical results present a very good matching with simulation results for a large variety of system scenarios, showing the accuracy of our approac
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