12 research outputs found
A Survey Study of the Current Challenges and Opportunities of Deploying the ECG Biometric Authentication Method in IoT and 5G Environments
The environment prototype of the Internet of Things (IoT) has opened the horizon for researchers to utilize such environments in deploying useful new techniques and methods in different fields and areas. The deployment process takes place when numerous IoT devices are utilized in the implementation phase for new techniques and methods. With the wide use of IoT devices in our daily lives in many fields, personal identification is becoming increasingly important for our society. This survey aims to demonstrate various aspects related to the implementation of biometric authentication in healthcare monitoring systems based on acquiring vital ECG signals via designated wearable devices that are compatible with 5G technology. The nature of ECG signals and current ongoing research related to ECG authentication are investigated in this survey along with the factors that may affect the signal acquisition process. In addition, the survey addresses the psycho-physiological factors that pose a challenge to the usage of ECG signals as a biometric trait in biometric authentication systems along with other challenges that must be addressed and resolved in any future related research.
Mécanismes de réduction de la consommation d'énergie dans les réseaux mobiles
La consommation en Ă©nergie des rĂ©seaux de tĂ©lĂ©communications a suscitĂ© un intĂ©rĂȘt grandissant au cours des derniĂšres annĂ©es et les opĂ©rateurs mobiles cherchent des solutions innovantes pour optimiser lâefficacitĂ© Ă©nergĂ©tique. Dans cette thĂšse, nous nous focaliserons sur les schĂ©mas dâoptimisation de la consommation dâĂ©nergie des rĂ©seaux dâaccĂšs mobiles. Nous commençons par Ă©tudier la stratĂ©gie de partage de charge qui minimise la consommation dâĂ©nergie dans la cellule tout en limitant lâimpact sur la QualitĂ© de Service. Le gain obtenu par ces algorithmes de gestion des ressources radio reste cependant limitĂ©; ceci est dĂ» au fait que la consommation dâĂ©nergie ne dĂ©pend pas que de la charge, mais comporte une importante partie constante. Pour obtenir un gain plus important, nous proposons la mise en veille de certaines ressources du rĂ©seaux aux heures creuses oĂč le trafic est faible, ce qui mĂšne Ă des gains substantiels. Nous proposons ensuite un contrĂŽleur de gestion de la mise en veille qui choisit lâaction optimale en fonction de lâĂ©tat du rĂ©seau. En effet, lâactivation dâune nouvelle ressource nâest pas instantanĂ©e et un effet ping-pong peut apparaitre suite aux commandes simultanĂ©es dâactivation/dĂ©sactivation des ressources. Nous adaptons nos contrĂŽleurs afin de prendre en compte ces imperfections, et nous montrons comment dĂ©duire la politique optimale. Nous Ă©tudions ensuite le cas de dĂ©ploiement de petites cellules dans des rĂ©seaux hĂ©tĂ©rogĂšnes et montrons que leur efficacitĂ© Ă©nergĂ©tique est amĂ©liorĂ©e par rapport au rĂ©seau purement macro-cellulaire, pourvu que la consommation dâĂ©nergie de petites cellules reste faible. Nous proposons ensuite un contrĂŽleur optimal qui active/dĂ©sactive les petites cellules en se basant sur des informations de trafic et de localisation des usagers. Nous considĂ©rons diffĂ©rents cas de figure avec une information complĂšte, partielle ou retardĂ©e et montrons que ces schĂ©mas de mise en veille permettent dâatteindre dâimportants gains de consommation dâĂ©nergieIn the recent years, more importance has been given to the energy consumption issue in telecommunication networks and mobile operators are rethinking their network design for optimizing its energy efficiency. In this thesis, we propose schemes for optimizing the energy consumption of mobile access networks. We begin by proposing energy-aware Radio Resource Management (RRM) schemes and show that a load balancing between available resources gives some energy savings. However, these gains remain small as a large part of the energy consumption is load-independent. We thus propose sleep mode schemes of resources in the network (cells or carriers) and show that they give a large gain when traffic is low. We then propose optimal sleep mode controllers that give, for each traffic scenario, the best actions to take in each state of the network. We make two observations: the first is that activating a new resource is not instantaneous, leading to QoS degradation if a conservative policy is not considered, and the second is that a ping-pong effect may appear at the frontier between two capacity regions. We adapt our controllers to take into account these imperfections, and show how to derive the optimal policy using Markov decision theory. We then extend our works to the case of small cell deployment in heterogeneous networks, composed of macro and small cells base stations. We study the capacity and power consumption of these networks and show that the energy efficiency is increased for some deployment strategies when the power consumption of small cells is low. We then propose sleep mode for small cells and develop optimal sleep/wakeup schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. We show that these sleep mode schemes achieve large energy consumption gain
Minimizing energy consumption via sleep mode in green base station
International audienceIn this paper, we develop new energy-efficient, radio resource management schemes for green wireless networks. Our goal is to optimize energy consumption at the network scale while preserving the Quality of Service (QoS) perceived by users. We specifically propose two new sleep mechanisms for base station where a number of resources in system can be shut down for some traffic scenarios in one of two ways: a dynamic way where resources are activated/deactivated in real-time as a function of the instantaneous load of the system, and a semi-static one where resources are kept unchanged during longer time intervals, in the order of one hour. We apply the proposed schemes to 2G and HSPA (High Speed Packet Access) systems and show that the dynamic one achieves larger energy reductions while the semistatic one has an acceptable performance with low complexit
How femtocells impact the capacity and the energy efficiency of LTE-Advanced networks
International audienceIn this paper, we show the impact of femtocells deployment on the capacity of LTE-Advanced networks. We analyze the Erlang-like capacity of a network composed of macro networks only and study the impact of introducing femtocells. We study the ability of open and closed access femtocells to offload traffic from the macro network and draw the capacity gains that are expected from this offload. Knowing that femtocells are not managed by the operator, but installed by clients, we take into account the random nature of the resulting deployment in the capacity analysis. Our results quantify the gains thus achieved, in terms of user QoS and cell load, as well as energy efficiency, as compared to a pure macro networ
Optimal control for base station sleep mode in energy efficient radio access networks
International audienceIn this paper, we investigate network sleep mode for reducing energy consumption of radio access networks. We propose an offline-optimized controller that associates to each traffic an activation/deactivation policy that maximizes a multiple objective function of the Quality of Service (QoS) and the energy consumption. We focus on practical implementation issues that may affect the QoS and the stability of the system. We namely consider the activation time issue that results in the degradation of the throughput and the ping-pong effect that results in unnecessary ON/OFF oscillations. We illustrate our results numerically in beyond 3G network
Optimal control of wake up mechanisms of femtocells in heterogeneous networks
International audienceWe study, in this work, optimal sleep/wake up schemes for the base stations of network-operated femto cells deployed within macro cells for the purpose of offloading part of its traffic. Our aim is to minimize the energy consumption of the overall heterogeneous network while preserving the Quality of Service (QoS) experienced by users. We model such a system at the flow level, considering a dynamic user configuration, and derive, using Markov Decision Processes (MDPs), optimal sleep/wake up schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. Our results quantify the energy consumption and QoS perceived by the users in each of these cases and identify the tradeoffs between those two quantities. We also illustrate numerically the optimal policies in different traffic scenario
Capacity and energy efficiency of picocell deployment in LTE-A networks
International audienceIn this paper, we show the impact of deploying picocells on the capacity and energy efficiency of LTE-A networks. We analyze the Erlang-like capacity of a network composed of macro networks only and study the impact of introducing a number of picocells per site. Knowing that the capacity is not the only factor that will drive the evolution of the network, we also consider the energy efficiency as a Key Performance Indicator (KPI). Our results show that, in some scenarios, introducing picocells is a good network densification method as they achieve a higher network capacity with good energy efficienc
Optimal online control for sleep mode in green base stations
International audienceIn this paper, we investigate network sleep mode schemes for reducing energy consumption of radio access networks. We first propose, using Markov Decision Processes (MDPs), an optimal controller that associates to each traffic an activation/deactivation policy that maximizes a multiple objective function of the Quality of Service (QoS) and the energy consumption. We focus on a practical implementation issue, namely ping-pong effect resulting in unnecessary ON/OFF oscillations, that may affect the stability of the system. We illustrate our results numerically using theoretical models of the radio access network, and apply the developed mechanisms on a large-scale network simulator. Knowing that an offline optimization is not suitable for a large-scale network nor does it fit all traffic configurations, we propose, using an online controller that derives dynamically the optimal policy based on the dynamics of users in the cell. The design of our online controller is based on a simple â-greedy algorithm and learns the optimal threshold policy for activation/deactivation of network resources
Realistic Energy Saving Potential of Sleep Mode for Existing and Future Mobile Networks
AbstractâThis paper presents an extensive overview on an energy saving feature referred to as âsite sleep modeâ, designed for existing and future mobile broadband networks. In addition to providing a detailed understanding of the main concept, the paper also provides various studies and results to highlight potential savings, and emphasize some of the expected limitations. Since site measurements show that the energy consumption of base station sites is largely load-independent, this makes such a feature highly effective for reducing the energy consumption of mobile networks during hours of low traffic. After going through a number of different alternatives of the feature, this is applied to different network topologies, macro-only based networks, and a set of heterogeneous networks that employ the use of small cells in traffic hotspots. Results obtained through detailed case studies show that sleep mode can reduce the average daily energy consumption of a network by around 30%. This can be achieved while maintaining a predefined level of performance, used as a measure of comparing different scenarios. Index Termsâsleep mode, energy efficiency, case study, HSPA, LTE, base station, energy model, power model, heterogeneous network, femtocells, picocells I