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Abstract

Abstract
Wi-Fi networks lack energy consumption management mechanisms. In particular, during nighttime periods, the energy waste may be significant, since all Access Points (APs) are kept switched on even though there is minimum or null traffic demand. The fact that more than 80% of all wireless traffic is originated or terminated indoor, and served by Wi-Fi, has led the scientific community to look into energy saving mechanisms for Wi-Fi networks. State of the art solutions address the problem by switching APs on and off based on manually inserted schedules or by analyzing real-time traffic demand. The first are vendor specific; the second may induce frequent station (STA) handoffs, which has an impact on network performance. The lack of implementability of solutions is also a shortcoming in most works.We propose an algorithm, named Energy Consumption Management Algorithm (ECMA), that learns the daytime and nighttime periods of the Wi-Fi network. ECMA was designed having in mind its implementability over legacy Wi-Fi equipment. At daytime, the radio interfaces of the AP (2.4 GHz and 5 GHz) are switched on and off automatically, according to the traffic demand. At nighttime, clusters of APs, covering the same area, are formed, leaving one AP always switched on for basic coverage and the redundant APs swichted off to maximize energy savings, while avoiding coverage and performance hampering. Simulation results show energy savings of up to 50% are possible using the ECMA algorithm. © 2019 IEEE.

Abstract
The heated 5G network deployment race has already begun with the rapid progress in standardization efforts, backed by the current market availability of 5G-enabled network equipment, ongoing 5G spectrum auctions, early launching of non-standalone 5G network services in a few countries, among others. In this paper, we study current and future wireless networks from the viewpoint of energy efficiency (EE) and sustainability to meet the planned network and service evolution toward, along, and beyond 5G, as also inspired by the findings of the EU Celtic-Plus SooGREEN Project. We highlight the opportunities seized by the project efforts to enable and enrich this green nature of the network as compared to existing technologies. In specific, we present innovative means proposed in SooGREEN to monitor and evaluate EE in 5G networks and beyond. Further solutions are presented to reduce energy consumption and carbon footprint in the different network segments. The latter spans proposed virtualized/cloud architectures, efficient polar coding for fronthauling, mobile network powering via renewable energy and smart grid integration, passive cooling, smart sleeping modes in indoor systems, among others. Finally, we shed light on the open opportunities yet to be investigated and leveraged in future developments.

Abstract
In this paper is presented the work relative to the design of an aid system, for athletes with special needs in terms of vision. The system is based on Radio Frequency Identification (RFID) technology and serves to help visually impaired athletes. Relatively to Paralympic athletics competitions, the main goal is the elimination of current guide runners. The system is prepared to give a stereo audio alert, when a runner deviates from his lane central area. The paper presents the main components, namely, the RFID infrastructure and the mobile parts. Tests to tags, infrastructure setting and positioning functions are also presented. (C) 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND License (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Abstract