Optimized LTE Data Transmission Procedures for IoT: Device Side Energy Consumption Analysis

The efficient deployment of Internet of Things (IoT) over cellular networks, such as Long Term Evolution (LTE) or the next generation 5G, entails several challenges. For massive IoT, reducing the energy consumption on the device side becomes essential. One of the main characteristics of massive IoT is small data transmissions. To improve the support of them, the 3GPP has included two novel optimizations in LTE: one of them based on the Control Plane (CP), and the other on the User Plane (UP). In this paper, we analyze the average energy consumption per data packet using these two optimizations compared to conventional LTE Service Request procedure. We propose an analytical model to calculate the energy consumption for each procedure based on a Markov chain. In the considered scenario, for large and small Inter-Arrival Times (IATs), the results of the three procedures are similar. While for medium IATs CP reduces the energy consumption per packet up to 87% due to its connection release optimization

Analytic Analysis of Narrowband IoT Coverage Enhancement Approaches

The introduction of Narrowband Internet of Things (NB-IoT) as a cellular IoT technology aims to support massive Machine-Type Communications applications. These applications are characterized by massive connections from a large number of low-complexity and low-power devices. One of the goals of NB-IoT is to improve coverage extension beyond existing cellular technologies. In order to do that, NB-IoT introduces transmission repetitions and different bandwidth allocation configurations in uplink. These new transmission approaches yield many transmission options in uplink. In this paper, we propose analytical expressions that describe the influence of these new approaches in the transmission. Our analysis is based on the Shannon theorem. The transmission is studied in terms of the required Signal to Noise Ratio, bandwidth utilization, and energy per transmitted bit. Additionally, we propose an uplink link adaptation algorithm that contemplates these new transmission approaches. The conducted evaluation summarizes the influence of these approaches. Furthermore, we present the resulting uplink link adaptation from our proposed algorithm sweeping the device's coverage.Comment: Accepted in the 2018 Global IoT Summit (GIoTS) conferenc

Servicio centralizado de proyección de material docente

[ES] En los últimos años las tecnologías TIC se han ido incorporando en los diferentes ámbitos de la enseñanza, desde las pizarras electrónicas para las clases magistrales hasta el uso de tabletas para la visualización de libros docentes en formato electrónico. De hecho, resulta cada vez más frecuente que los docentes empleen sus portátiles para presentar su material en formato de transparencias. No obstante, esto implica que los profesores deben llevar sus portátiles al aula y conectarlos a través de un cable, sea VGA o HDMI, al proyector. Esto resta movilidad al profesor, anclado a través del cable al proyector, además de requerir que disponga de un portátil que ha de llevar al aula. Dado que, en la actualidad, casi la totalidad de la población dispone de móviles inteligentes, este artículo presenta la solución propuesta en un proyecto de innovación docente desarrollado (PID 14-61) en la Universidad de Granada. En éste, se propone una solución en la que el profesor sólo deberá llevar su móvil (o alternativamente una tableta o un portátil) al aula. El material docente será subido a un servidor central desde su despacho, y la visualización en el proyector será controlada a través del móvil usando una interfaz muy amigable y sencillo.El presente trabajo ha sido financiado a traves del Programa de Innovacion y Buenas Prácticas Docentes del Secretariado de Innovacion Docente de la Universidad de Granada, Proyecto de Innovacion Docente 14-61 ”Servicio de Proyeccion de Material Docente”, dentro de la acción 1 (innovacion en la gestión on-line de los procesos de ensenanza-aprendizaje). Parte del presente trabajo ha sido ˜ desarrollado por los alumnos D. Juan Ramon Gutiérrez Martínez, D. Daniel Alvarez González y D. David Gallardo Jimenez, siendo estos dos últimos becarios del citado PID.Navarro Ortiz, J.; Sendra, S.; Ameigeiras, P.; Torre, ADL.; Garcia, L.; Gomez, A.; Lopez-Soler, J.... (2018). Servicio centralizado de proyección de material docente. En XIII Jornadas de Ingeniería telemática (JITEL 2017). Libro de actas. Editorial Universitat Politècnica de València. 330-336. https://doi.org/10.4995/JITEL2017.2017.6508OCS33033

Asynchronous time-sensitive networking for 5G backhauling

Abstract Fifth Generation (5G) phase 2 rollouts are around the corner to make mobile ultra-reliable and low-latency services a reality. However, to realize that scenario, besides the new 5G built-in Ultra-Reliable Low-Latency Communication (URLLC) capabilities, it is required to provide a substrate network with deterministic Qual-ity-of-Service support for interconnecting the different 5G network functions and services. Time-Sensitive Networking (TSN) appears as an appealing network technology to meet the 5G connectivity needs in many scenarios involving critical services and their coexistence with Mobile Broadband traffic. In this article, we delve into the adoption of asynchronous TSN for 5G backhauling and some of the relevant related aspects. We start motivating TSN and introducing its mainstays. Then, we provide a comprehensive overview of the architecture and operation of the Asynchronous Traffic Shaper (ATS), the building block of asynchronous TSN. Next, a management framework based on ETSI Zero-touch network and Service Management (ZSM) and Abstraction and Control of Traffic Engineered Networks (ACTN) reference models is presented for enabling the TSN transport network slicing and its interworking with Fifth Generation (5G) for backhauling. Then we cover the flow allocation problem in asynchronous TSNs and the importance of Machine Learning techniques for assisting it. Last, we present a simulation-based proof-of-concept (PoC) to assess the capacity of ATS-based forwarding planes for accommodating 5G data flows

Optimization of Flow Allocation in Asynchronous Deterministic 5G Transport Networks by Leveraging Data Analytics

| openaire: EC/H2020/723172/EU//5GPagodaTime-Sensitive Networking (TSN) and Deterministic Networking (DetNet) technologies are increasingly recognized as key levers of the future 5G transport networks (TNs) due to their capabilities for providing deterministic Quality-ofService and enabling the coexistence of critical and best-effort services. Additionally, they rely on programmable and costeffective Ethernet-based forwarding planes. In this article, we address the flow allocation problem in 5G backhaul networks realized as asynchronous TSN networks, whose building block is the Asynchronous Traffic Shaper. We propose an offline solution, dubbed Next Generation Transport Network Optimizer (NEPTUNO), that combines exact optimization methods and heuristic techniques and leverages data analytics to solve the flow allocation problem. NEPTUNO aims to maximize the flow acceptance ratio while guaranteeing the deterministic Qualityof-service requirements of the critical flows. We carried out a performance evaluation of NEPTUNO in terms of the degree of optimality, execution time, and flow rejection ratio. Furthermore, we compare NEPTUNO with two online baseline solutions. Online methods compute the flows allocation configuration right after the flow arrives at the network, whereas offline solutions like NEPTUNO compute a long-term configuration allocation for the whole network. Our results highlight the potential of the data analytics for the self-optimization of the future 5G TNs.Peer reviewe

A Queuing based Dynamic Auto Scaling Algorithm for the LTE EPC Control Plane

| openaire: EC/H2020/723172/EU//5GPagodaNetwork softwarization paradigm, whose main enabler is Network Functions Virtualization (NFV), facilitates the automation of the management operations and orchestration of the future networks, thus reducing the operational expenditures of the network. The envisioned management practices include the introduction of automation in the scaling of network services. This may enable operators to handle workload fluctuations to keep the desired performance with great agility and reduced costs. This procedure introduces a non-negligible delay in allocating or releasing virtual resources. Therefore, waiting until the system is overloaded or underutilized so as to scale resources up or down could negatively impact user Quality of Experience, or lead to inefficient resource utilization. In this vein, this paper proposes a novel and agile Dynamic Auto Scaling Algorithm for the Long Term Evolution (LTE) virtualized Evolved Packet Core (vEPC) Control Plane (CP). The resources dimensioning stage of the algorithm is based on an original queuing model for the LTE CP. To model the LTE CP, we use an open network of G/G/m queues. We also provide expressions to derive the steady state transition probabilities of the queuing network. Finally, we validate the proper operation of our solution using accurate simulation tools.Peer reviewe

Energy and Delay aware Physical Collision Avoidance in Unmanned Aerial Vehicles

Several solutions have been proposed in the literature to address the Unmanned Aerial Vehicles (UAVs) collision avoidance problem. Most of these solutions consider that the ground controller system (GCS) determines the path of a UAV before starting a particular mission at hand. Furthermore, these solutions expect the occurrence of collisions based only on the GPS localization of UAVs as well as via object-detecting sensors placed on board UAVs. The sensors' sensitivity to environmental disturbances and the UAVs' influence on their accuracy impact negatively the efficiency of these solutions. In this vein, this paper proposes a new energy- and delay-aware physical collision avoidance solution for UAVs. The solution is dubbed EDCUAV. The primary goal of EDC-UAV is to build in-flight safe UAVs trajectories while minimizing the energy consumption and response time. We assume that each UAV is equipped with a global positioning system (GPS) sensor to identify its position. Moreover, we take into account the margin error of the GPS to provide the position of a given UAV. The location of each UAV is gathered by a cluster head, which is the UAV that has either the highest autonomy or the greatest computational capacity. The cluster head runs the EDC-UAV algorithm to control the rest of the UAVs, thus guaranteeing a collision free mission and minimizing the energy consumption to achieve different purposes. The proper operation of our solution is validated through simulations. The obtained results demonstrate the efficiency of EDC-UAV in achieving its design goals.Peer reviewe

A Fuzzy Logic-based Mechanism for An Efficient Cloud Resource Planning

| openaire: EC/H2020/723172/EU//5GPagoda | openaire: EC/H2020/761898/EU//MATILDAThe key concept beneath Multi-Access Edge Computing (MECs) is to place cloud resources in closer proximity to end-users, through the installation of small-scale cloud infrastructures at the network edge. In MEC environments, we identify two issues: 1) data about users' activities are not always available, and 2) the available virtual resource planning mechanisms (i.e., algorithms for the placement of Virtual Network Functions - VNFs) are not efficient enough to fulfill the QoS requirements and deployment costs. In this vein, we design a layered framework to define the presence of Mobile BroadBand User Equipments (UEs) and automate the underlying virtual resource placement and management based on the Fuzzy Logic Controller paradigm (FLC). Experimentation results show that our framework, compared to baseline solutions, achieves good performance results; the end-to-end delay is enhanced by 25%, the resource consumption is reduced by 30%, and the environmental impact, reflected by the carbon footprint that depends on the amount of deployed Virtual Machines (VMs), is reduced by 50%.Peer reviewe