479 research outputs found

    EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

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    The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application

    Smart Grid communications in high traffic environments

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    The establishment of a previously non-existent data class known as the Smart Grid will pose many difficulties on current and future communication infrastructure. It is imperative that the Smart Grid (SG), as the reactionary and monitory arm of the Power Grid (PG), be able to communicate effectively between grid controllers and individual User Equipment (UE). By doing so, the successful implementation of SG applications can occur, including support for higher capacities of Renewable Energy Resources. As the SG matures, the number of UEs required is expected to rise increasing the traffic in an already burdened communications network. This thesis aims to optimally allocate radio resources such that the SG Quality of Service (QoS) requirements are satisfied with minimal effect on pre-existing traffic. To address this resource allocation problem, a Lotka-Volterra (LV) based resource allocation and scheduler was developed due to its ability to easily adapt to the dynamics of a telecommunications environment. Unlike previous resource allocation algorithms, the LV scheme allocated resources to each class as a function of its growth rate. By doing so, the QoS requirements of the SG were satisfied, with minimal effect on pre-existing traffic. Class queue latencies were reduced by intelligent scheduling of periodic traffic and forward allocation of resources. This thesis concludes that the SG will have a large effect on the telecommunications environment if not successfully controlled and monitored. This effect can be minimized by utilizing the proposed LV based resource allocation and scheduler system. Furthermore, it was shown that the allocation of periodic SG radio channels was optimized by continual updates of the LV model. This ensured the QoS requirements of the SG are achieved and provided enhanced performance. Successful integration of SG UEs in a wireless network can pave the way for increased capacity of Renewable and Intermittent Energy Resources operating on the PG

    Application of cognitive radio based sensor network in smart grids for efficient, holistic monitoring and control.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.This thesis is directed towards the application of cognitive radio based sensor network (CRSN) in smart grid (SG) for efficient, holistic monitoring and control. The work involves enabling of sensor network and wireless communication devices for spectra utilization via the capability of Dynamic Spectrum Access (DSA) of a cognitive radio (CR) as well as end to end communication access technology for unified monitoring and control in smart grids. Smart Grid (SG) is a new power grid paradigm that can provide predictive information and recommendations to utilities, including their suppliers, and their customers on how best to manage power delivery and consumption. SG can greatly reduce air pollution from our surrounding by renewable power sources such as wind energy, solar plants and huge hydro stations. SG also reduces electricity blackouts and surges. Communication network is the foundation for modern SG. Implementing an improved communication solution will help in addressing the problems of the existing SG. Hence, this study proposed and implemented improved CRSN model which will help to ultimately evade the inherent problems of communication network in the SG such as: energy inefficiency, interference, spectrum inefficiencies, poor quality of service (QoS), latency and throughput. To overcome these problems, the existing approach which is more predominant is the use of wireless sensor network (WSNs) for communication needs in SG. However, WSNs have low battery power, low computational complexity, low bandwidth support, and high latency or delay due to multihop transmission in existing WSN topology. Consequently, solving these problems by addressing energy efficiency, bandwidth or throughput, and latency have not been fully realized due to the limitations in the WSN and the existing network topology. Therefore, existing approach has not fully addressed the communication needs in SG. SG can be fully realized by integrating communication network technologies infrastructures into the power grid. Cognitive Radio-based Sensor Network (CRSN) is considered a feasible solution to enhance various aspects of the electric power grid such as communication with end and remote devices in real-time manner for efficient monitoring and to realize maximum benefits of a smart grid system. CRSN in SG is aimed at addressing the problem of spectrum inefficiency and interference which wireless sensor network (WSN) could not. However, numerous challenges for CRSNs are due to the harsh environmental wireless condition in a smart grid system. As a result, latency, throughput and reliability become critical issues. To overcome these challenges, lots of approaches can be adopted ranging from integration of CRSNs into SGs; proper implementation design model for SG; reliable communication access devices for SG; key immunity requirements for communication infrastructure in SG; up to communication network protocol optimization and so on. To this end, this study utilized the National Institute of Standard (NIST) framework for SG interoperability in the design of unified communication network architecture including implementation model for guaranteed quality of service (QoS) of smart grid applications. This involves virtualized network in form of multi-homing comprising low power wide area network (LPWAN) devices such as LTE CAT1/LTE-M, and TV white space band device (TVBD). Simulation and analysis show that the performance of the developed modules architecture outperforms the legacy wireless systems in terms of latency, blocking probability, and throughput in SG harsh environmental condition. In addition, the problem of multi correlation fading channels due to multi antenna channels of the sensor nodes in CRSN based SG has been addressed by the performance analysis of a moment generating function (MGF) based M-QAM error probability over Nakagami-q dual correlated fading channels with maximum ratio combiner (MRC) receiver technique which includes derivation and novel algorithmic approach. The results of the MATLAB simulation are provided as a guide for sensor node deployment in order to avoid the problem of multi correlation in CRSN based SGs. SGs application requires reliable and efficient communication with low latency in timely manner as well as adequate topology of sensor nodes deployment for guaranteed QoS. Another important requirement is the need for an optimized protocol/algorithms for energy efficiency and cross layer spectrum aware made possible for opportunistic spectrum access in the CRSN nodes. Consequently, an optimized cross layer interaction of the physical and MAC layer protocols using various novel algorithms and techniques was developed. This includes a novel energy efficient distributed heterogeneous clustered spectrum aware (EDHC- SA) multichannel sensing signal model with novel algorithm called Equilateral triangulation algorithm for guaranteed network connectivity in CRSN based SG. The simulation results further obtained confirm that EDHC-SA CRSN model outperforms conventional ZigBee WSN in terms of bit error rate (BER), end-to-end delay (latency) and energy consumption. This no doubt validates the suitability of the developed model in SG

    Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

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    The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

    Cellular networks for smart grid communication

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    The next-generation electric power system, known as smart grid, relies on a robust and reliable underlying communication infrastructure to improve the efficiency of electricity distribution. Cellular networks, e.g., LTE/LTE-A systems, appear as a promising technology to facilitate the smart grid evolution. Their inherent performance characteristics and well-established ecosystem could potentially unlock unprecedented use cases, enabling real-time and autonomous distribution grid operations. However, cellular technology was not originally intended for smart grid communication, associated with highly-reliable message exchange and massive device connectivity requirements. The fundamental differences between smart grid and human-type communication challenge the classical design of cellular networks and introduce important research questions that have not been sufficiently addressed so far. Motivated by these challenges, this doctoral thesis investigates novel radio access network (RAN) design principles and performance analysis for the seamless integration of smart grid traffic in future cellular networks. Specifically, we focus on addressing the fundamental RAN problems of network scalability in massive smart grid deployments and radio resource management for smart grid and human-type traffic. The main objective of the thesis lies on the design, analysis and performance evaluation of RAN mechanisms that would render cellular networks the key enabler for emerging smart grid applications. The first part of the thesis addresses the radio access limitations in LTE-based networks for reliable and scalable smart grid communication. We first identify the congestion problem in LTE random access that arises in large-scale smart grid deployments. To overcome this, a novel random access mechanism is proposed that can efficiently support real-time distribution automation services with negligible impact on the background traffic. Motivated by the stringent reliability requirements of various smart grid operations, we then develop an analytical model of the LTE random access procedure that allows us to assess the performance of event-based monitoring traffic under various load conditions and network configurations. We further extend our analysis to include the relation between the cell size and the availability of orthogonal random access resources and we identify an additional challenge for reliable smart grid connectivity. To this end, we devise an interference- and load-aware cell planning mechanism that enhances reliability in substation automation services. Finally, we couple the problem of state estimation in wide-area monitoring systems with the reliability challenges in information acquisition. Using our developed analytical framework, we quantify the impact of imperfect communication reliability in the state estimation accuracy and we provide useful insights for the design of reliability-aware state estimators. The second part of the thesis builds on the previous one and focuses on the RAN problem of resource scheduling and sharing for smart grid and human-type traffic. We introduce a novel scheduler that achieves low latency for distribution automation traffic while resource allocation is performed in a way that keeps the degradation of cellular users at a minimum level. In addition, we investigate the benefits of Device-to-Device (D2D) transmission mode for event-based message exchange in substation automation scenarios. We design a joint mode selection and resource allocation mechanism which results in higher data rates with respect to the conventional transmission mode via the base station. An orthogonal resource partition scheme between cellular and D2D links is further proposed to prevent the underutilization of the scarce cellular spectrum. The research findings of this thesis aim to deliver novel solutions to important RAN performance issues that arise when cellular networks support smart grid communication.Las redes celulares, p.e., los sistemas LTE/LTE-A, aparecen como una tecnología prometedora para facilitar la evolución de la próxima generación del sistema eléctrico de potencia, conocido como smart grid (SG). Sin embargo, la tecnología celular no fue pensada originalmente para las comunicaciones en la SG, asociadas con el intercambio fiable de mensajes y con requisitos de conectividad de un número masivo de dispositivos. Las diferencias fundamentales entre las comunicaciones en la SG y la comunicación de tipo humano desafían el diseño clásico de las redes celulares e introducen importantes cuestiones de investigación que hasta ahora no se han abordado suficientemente. Motivada por estos retos, esta tesis doctoral investiga los principios de diseño y analiza el rendimiento de una nueva red de acceso radio (RAN) que permita una integración perfecta del tráfico de la SG en las redes celulares futuras. Nos centramos en los problemas fundamentales de escalabilidad de la RAN en despliegues de SG masivos, y en la gestión de los recursos radio para la integración del tráfico de la SG con el tráfico de tipo humano. El objetivo principal de la tesis consiste en el diseño, el análisis y la evaluación del rendimiento de los mecanismos de las RAN que convertirán a las redes celulares en el elemento clave para las aplicaciones emergentes de las SGs. La primera parte de la tesis aborda las limitaciones del acceso radio en redes LTE para la comunicación fiable y escalable en SGs. En primer lugar, identificamos el problema de congestión en el acceso aleatorio de LTE que aparece en los despliegues de SGs a gran escala. Para superar este problema, se propone un nuevo mecanismo de acceso aleatorio que permite soportar de forma eficiente los servicios de automatización de la distribución eléctrica en tiempo real, con un impacto insignificante en el tráfico de fondo. Motivados por los estrictos requisitos de fiabilidad de las diversas operaciones en la SG, desarrollamos un modelo analítico del procedimiento de acceso aleatorio de LTE que nos permite evaluar el rendimiento del tráfico de monitorización de la red eléctrica basado en eventos bajo diversas condiciones de carga y configuraciones de red. Además, ampliamos nuestro análisis para incluir la relación entre el tamaño de celda y la disponibilidad de recursos de acceso aleatorio ortogonales, e identificamos un reto adicional para la conectividad fiable en la SG. Con este fin, diseñamos un mecanismo de planificación celular que tiene en cuenta las interferencias y la carga de la red, y que mejora la fiabilidad en los servicios de automatización de las subestaciones eléctricas. Finalmente, combinamos el problema de la estimación de estado en sistemas de monitorización de redes eléctricas de área amplia con los retos de fiabilidad en la adquisición de la información. Utilizando el modelo analítico desarrollado, cuantificamos el impacto de la baja fiabilidad en las comunicaciones sobre la precisión de la estimación de estado. La segunda parte de la tesis se centra en el problema de scheduling y compartición de recursos en la RAN para el tráfico de SG y el tráfico de tipo humano. Presentamos un nuevo scheduler que proporciona baja latencia para el tráfico de automatización de la distribución eléctrica, mientras que la asignación de recursos se realiza de un modo que mantiene la degradación de los usuarios celulares en un nivel mínimo. Además, investigamos los beneficios del modo de transmisión Device-to-Device (D2D) en el intercambio de mensajes basados en eventos en escenarios de automatización de subestaciones eléctricas. Diseñamos un mecanismo conjunto de asignación de recursos y selección de modo que da como resultado tasas de datos más elevadas con respecto al modo de transmisión convencional a través de la estación base. Finalmente, se propone un esquema de partición de recursos ortogonales entre enlaces celulares y D2Postprint (published version

    Internet of Things and Sensors Networks in 5G Wireless Communications

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    This book is a printed edition of the Special Issue Internet of Things and Sensors Networks in 5G Wireless Communications that was published in Sensors
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