scispace - formally typeset
Search or ask a question

Showing papers in "IEEE Access in 2015"


Journal ArticleDOI
TL;DR: An intelligent collaborative security model to minimize security risk is proposed; how different innovations such as big data, ambient intelligence, and wearables can be leveraged in a health care context is discussed; and various IoT and eHealth policies and regulations are addressed to determine how they can facilitate economies and societies in terms of sustainable development.
Abstract: The Internet of Things (IoT) makes smart objects the ultimate building blocks in the development of cyber-physical smart pervasive frameworks. The IoT has a variety of application domains, including health care. The IoT revolution is redesigning modern health care with promising technological, economic, and social prospects. This paper surveys advances in IoT-based health care technologies and reviews the state-of-the-art network architectures/platforms, applications, and industrial trends in IoT-based health care solutions. In addition, this paper analyzes distinct IoT security and privacy features, including security requirements, threat models, and attack taxonomies from the health care perspective. Further, this paper proposes an intelligent collaborative security model to minimize security risk; discusses how different innovations such as big data, ambient intelligence, and wearables can be leveraged in a health care context; addresses various IoT and eHealth policies and regulations across the world to determine how they can facilitate economies and societies in terms of sustainable development; and provides some avenues for future research on IoT-based health care based on a set of open issues and challenges.

2,190 citations


Journal ArticleDOI
TL;DR: A general probable 5G cellular network architecture is proposed, which shows that D2D, small cell access points, network cloud, and the Internet of Things can be a part of 5G Cellular network architecture.
Abstract: In the near future, i.e., beyond 4G, some of the prime objectives or demands that need to be addressed are increased capacity, improved data rate, decreased latency, and better quality of service. To meet these demands, drastic improvements need to be made in cellular network architecture. This paper presents the results of a detailed survey on the fifth generation (5G) cellular network architecture and some of the key emerging technologies that are helpful in improving the architecture and meeting the demands of users. In this detailed survey, the prime focus is on the 5G cellular network architecture, massive multiple input multiple output technology, and device-to-device communication (D2D). Along with this, some of the emerging technologies that are addressed in this paper include interference management, spectrum sharing with cognitive radio, ultra-dense networks, multi-radio access technology association, full duplex radios, millimeter wave solutions for 5G cellular networks, and cloud technologies for 5G radio access networks and software defined networks. In this paper, a general probable 5G cellular network architecture is proposed, which shows that D2D, small cell access points, network cloud, and the Internet of Things can be a part of 5G cellular network architecture. A detailed survey is included regarding current research projects being conducted in different countries by research groups and institutions that are working on 5G technologies.

1,899 citations


Journal ArticleDOI
TL;DR: A comprehensive overview of sparse representation is provided and an experimentally comparative study of these sparse representation algorithms was presented, which could sufficiently reveal the potential nature of the sparse representation theory.
Abstract: Sparse representation has attracted much attention from researchers in fields of signal processing, image processing, computer vision, and pattern recognition. Sparse representation also has a good reputation in both theoretical research and practical applications. Many different algorithms have been proposed for sparse representation. The main purpose of this paper is to provide a comprehensive study and an updated review on sparse representation and to supply guidance for researchers. The taxonomy of sparse representation methods can be studied from various viewpoints. For example, in terms of different norm minimizations used in sparsity constraints, the methods can be roughly categorized into five groups: 1) sparse representation with $l_{0}$ -norm minimization; 2) sparse representation with $l_{p}$ -norm ( $0 ) minimization; 3) sparse representation with $l_{1}$ -norm minimization; 4) sparse representation with $l_{2,1}$ -norm minimization; and 5) sparse representation with $l_{2}$ -norm minimization. In this paper, a comprehensive overview of sparse representation is provided. The available sparse representation algorithms can also be empirically categorized into four groups: 1) greedy strategy approximation; 2) constrained optimization; 3) proximity algorithm-based optimization; and 4) homotopy algorithm-based sparse representation. The rationales of different algorithms in each category are analyzed and a wide range of sparse representation applications are summarized, which could sufficiently reveal the potential nature of the sparse representation theory. In particular, an experimentally comparative study of these sparse representation algorithms was presented.

925 citations


Journal ArticleDOI
TL;DR: This paper presents a review of issues concerning microgrid issues and provides an account of research in areas related to microgrids, including distributed generation, microgrid value propositions, applications of power electronics, economic issues, micro grid operation and control, micro grids clusters, and protection and communications issues.
Abstract: The significant benefits associated with microgrids have led to vast efforts to expand their penetration in electric power systems. Although their deployment is rapidly growing, there are still many challenges to efficiently design, control, and operate microgrids when connected to the grid, and also when in islanded mode, where extensive research activities are underway to tackle these issues. It is necessary to have an across-the-board view of the microgrid integration in power systems. This paper presents a review of issues concerning microgrids and provides an account of research in areas related to microgrids, including distributed generation, microgrid value propositions, applications of power electronics, economic issues, microgrid operation and control, microgrid clusters, and protection and communications issues.

875 citations


Journal ArticleDOI
TL;DR: The results show that novel large-scale path loss models provided here are simpler and more physically based compared to previous 3GPP and ITU indoor propagation models that require more model parameters and offer very little additional accuracy and lack a physical basis.
Abstract: Ultra-wideband millimeter-wave (mmWave) propagation measurements were conducted in the 28- and 73-GHz frequency bands in a typical indoor office environment in downtown Brooklyn, New York, on the campus of New York University. The measurements provide large-scale path loss and temporal statistics that will be useful for ultra-dense indoor wireless networks for future mmWave bands. This paper presents the details of measurements that employed a 400 Megachips-per-second broadband sliding correlator channel sounder, using rotatable highly directional horn antennas for both co-polarized and crosspolarized antenna configurations. The measurement environment was a closed-plan in-building scenario that included a line-of-sight and non-line-of-sight corridor, a hallway, a cubicle farm, and adjacent-room communication links. Well-known and new single-frequency and multi-frequency directional and omnidirectional large-scale path loss models are presented and evaluated based on more than 14 000 directional power delay profiles acquired from unique transmitter and receiver antenna pointing angle combinations. Omnidirectional path loss models, synthesized from the directional measurements, are provided for the case of arbitrary polarization coupling, aswell as for the specific cases of co-polarized and cross-polarized antenna orientations. The results show that novel large-scale path loss models provided here are simpler and more physically based compared to previous 3GPP and ITU indoor propagation models that require more model parameters and offer very little additional accuracy and lack a physical basis. Multipath time dispersion statistics formmWave systems using directional antennas are presented for co-polarization, crosspolarization, and combined-polarization scenarios, and show that the multipath root mean square delay spread can be reduced when using transmitter and receiver antenna pointing angles that result in the strongest received power. Raw omnidirectional path loss data and closed-form optimization formulas for all path loss models are given in the Appendices.

515 citations


Journal ArticleDOI
TL;DR: This survey presents a thorough investigation of the development of NFV under the software-defined NFV architecture, with an emphasis on service chaining as its application.
Abstract: Diverse proprietary network appliances increase both the capital and operational expense of service providers, meanwhile causing problems of network ossification. Network function virtualization (NFV) is proposed to address these issues by implementing network functions as pure software on commodity and general hardware. NFV allows flexible provisioning, deployment, and centralized management of virtual network functions. Integrated with SDN, the software-defined NFV architecture further offers agile traffic steering and joint optimization of network functions and resources. This architecture benefits a wide range of applications (e.g., service chaining) and is becoming the dominant form of NFV. In this survey, we present a thorough investigation of the development of NFV under the software-defined NFV architecture, with an emphasis on service chaining as its application. We first introduce the software-defined NFV architecture as the state of the art of NFV and present relationships between NFV and SDN. Then, we provide a historic view of the involvement from middlebox to NFV. Finally, we introduce significant challenges and relevant solutions of NFV, and discuss its future research directions by different application domains.

455 citations


Journal ArticleDOI
TL;DR: Various technologies and issues regarding green IoT, which further reduces the energy consumption of IoT are discussed, and the latest developments and future vision about sensor cloud are reviewed and introduced.
Abstract: Smart world is envisioned as an era in which objects (e.g., watches, mobile phones, computers, cars, buses, and trains) can automatically and intelligently serve people in a collaborative manner. Paving the way for smart world, Internet of Things (IoT) connects everything in the smart world. Motivated by achieving a sustainable smart world, this paper discusses various technologies and issues regarding green IoT, which further reduces the energy consumption of IoT. Particularly, an overview regarding IoT and green IoT is performed first. Then, the hot green information and communications technologies (ICTs) (e.g., green radio-frequency identification, green wireless sensor network, green cloud computing, green machine to machine, and green data center) enabling green IoT are studied, and general green ICT principles are summarized. Furthermore, the latest developments and future vision about sensor cloud, which is a novel paradigm in green IoT, are reviewed and introduced, respectively. Finally, future research directions and open problems about green IoT are presented. Our work targets to be an enlightening and latest guidance for research with respect to green IoT and smart world.

393 citations


Journal ArticleDOI
TL;DR: The basic concepts of rays, ray tracing algorithms, and radio propagation modeling using ray tracing methods are reviewed to envision propagation modeling in the near future as an intelligent, accurate, and real-time system in which ray tracing plays an important role.
Abstract: This paper reviews the basic concepts of rays, ray tracing algorithms, and radio propagation modeling using ray tracing methods We focus on the fundamental concepts and the development of practical ray tracing algorithms The most recent progress and a future perspective of ray tracing are also discussed We envision propagation modeling in the near future as an intelligent, accurate, and real-time system in which ray tracing plays an important role This review is especially useful for experts who are developing new ray tracing algorithms to enhance modeling accuracy and improve computational speed

375 citations


Journal ArticleDOI
TL;DR: SIoV is a vehicular instance of the Social IoT (SIoT), where vehicles are the key social entities in the machine-to-machine vehicular social networks and the social structures of SIoV components, their relationships, and the interaction types are identified.
Abstract: The main vision of the Internet of Things (IoT) is to equip real-life physical objects with computing and communication power so that they can interact with each other for the social good. As one of the key members of IoT, Internet of Vehicles (IoV) has seen steep advancement in communication technologies. Now, vehicles can easily exchange safety, efficiency, infotainment, and comfort-related information with other vehicles and infrastructures using vehicular ad hoc networks (VANETs). We leverage on the cloud-based VANETs theme to propose cyber-physical architecture for the Social IoV (SIoV). SIoV is a vehicular instance of the Social IoT (SIoT), where vehicles are the key social entities in the machine-to-machine vehicular social networks. We have identified the social structures of SIoV components, their relationships, and the interaction types. We have mapped VANETs components into IoT-A architecture reference model to offer better integration of SIoV with other IoT domains. We also present a communication message structure based on automotive ontologies, the SAE J2735 message set, and the advanced traveler information system events schema that corresponds to the social graph. Finally, we provide the implementation details and the experimental analysis to demonstrate the efficacy of the proposed system as well as include different application scenarios for various user groups.

334 citations


Journal ArticleDOI
TL;DR: The key approach to enable efficient and reliable management of WSN within an infrastructure supporting various WSN applications and services is a cross-layer design of lightweight and cloud-based RESTful Web service.
Abstract: With the accelerated development of Internet-of-Things (IoT), wireless sensor networks (WSNs) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with the Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for WSNs design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards, and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross-layer design of lightweight and cloud-based RESTful Web service.

290 citations


Journal ArticleDOI
TL;DR: Experimental results show that based on these four metrics, a multi-objective optimization method is better than other similar methods, especially as it increased 56.6% in the best case scenario.
Abstract: For task-scheduling problems in cloud computing, a multi-objective optimization method is proposed here. First, with an aim toward the biodiversity of resources and tasks in cloud computing, we propose a resource cost model that defines the demand of tasks on resources with more details. This model reflects the relationship between the user’s resource costs and the budget costs. A multi-objective optimization scheduling method has been proposed based on this resource cost model. This method considers the makespan and the user’s budget costs as constraints of the optimization problem, achieving multi-objective optimization of both performance and cost. An improved ant colony algorithm has been proposed to solve this problem. Two constraint functions were used to evaluate and provide feedback regarding the performance and budget cost. These two constraint functions made the algorithm adjust the quality of the solution in a timely manner based on feedback in order to achieve the optimal solution. Some simulation experiments were designed to evaluate this method’s performance using four metrics: 1) the makespan; 2) cost; 3) deadline violation rate; and 4) resource utilization. Experimental results show that based on these four metrics, a multi-objective optimization method is better than other similar methods, especially as it increased 56.6% in the best case scenario.

Journal ArticleDOI
TL;DR: A controlled charging algorithm is proposed to improve the voltage quality at the EV load locations while avoiding customer inconvenience and significantly decreases the impacts of EV load charging on system peak load demand and feeder voltages.
Abstract: This paper aims to understand, identify, and mitigate the impacts of residential electric vehicle (EV) charging on distribution system voltages. A thorough literature review on the impacts of residential EV charging is presented, followed by a proposed method for evaluating the impacts of EV loads on the distribution system voltage quality. Practical solutions to mitigate EV load impacts are discussed as well, including infrastructural changes and indirect controlled charging with time-of-use (TOU) pricing. An optimal TOU schedule is also presented, with the aim of maximizing both customer and utility benefits. This paper also presents a discussion on implementing smart charging algorithms to directly control EV charging rates and EV charging starting times. Finally, a controlled charging algorithm is proposed to improve the voltage quality at the EV load locations while avoiding customer inconvenience. The proposed method significantly decreases the impacts of EV load charging on system peak load demand and feeder voltages.

Journal ArticleDOI
TL;DR: A system that helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance and the total number of free places in each car park is proposed.
Abstract: This paper introduces a novel algorithm that increases the efficiency of the current cloud-based smart-parking system and develops a network architecture based on the Internet-of-Things technology. This paper proposed a system that helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance and the total number of free places in each car park. This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results show that the algorithm helps improve the probability of successful parking and minimizes the user waiting time. We also successfully implemented the proposed system in the real world.

Journal ArticleDOI
TL;DR: This paper presents a complete approach to a successful utilization of a high-performance extreme learning machines (ELM) Toolbox for Big Data, and summarizes recent advantages in algorithmic performance; gives a fresh view on the ELM solution in relation to the traditional linear algebraic performance; and reaps the latest software and hardware performance achievements.
Abstract: This paper presents a complete approach to a successful utilization of a high-performance extreme learning machines (ELMs) Toolbox for Big Data. It summarizes recent advantages in algorithmic performance; gives a fresh view on the ELM solution in relation to the traditional linear algebraic performance; and reaps the latest software and hardware performance achievements. The results are applicable to a wide range of machine learning problems and thus provide a solid ground for tackling numerous Big Data challenges. The included toolbox is targeted at enabling the full potential of ELMs to the widest range of users.

Journal ArticleDOI
TL;DR: An innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors using low-cost ultrasonic and infrared range finders.
Abstract: This paper demonstrates an innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors. The sensors exploited in this paper are low-cost ultrasonic and infrared range finders, which are much cheaper though noisier than more expensive sensors such as laser scanners. This needs to be taken into consideration for the design, implementation, and parametrization of the signal processing and control algorithm for such a system, which is the topic of this paper. For improved data fusion, inertial and optical flow sensors are used as a distance derivative for reference. As a result, a UAV is capable of distance controlled collision avoidance, which is more complex and powerful than comparable simple solutions. At the same time, the solution remains simple with a low computational burden. Thus, memory and time-consuming simultaneous localization and mapping is not required for collision avoidance.

Journal ArticleDOI
TL;DR: This work proposes two novel methods for compression: one based on eliminating lowly active channels and the other on coupling pruning with repeated use of already computed elements.
Abstract: A major challenge in biometrics is performing the test at the client side, where hardware resources are often limited. Deep learning approaches pose a unique challenge: while such architectures dominate the field of face recognition with regard to accuracy, they require elaborate, multi-stage computations. Recently, there has been some work on compressing networks for the purpose of reducing run time and network size. However, it is not clear that these compression methods would work in deep face nets, which are, generally speaking, less redundant than the object recognition networks, i.e., they are already relatively lean. We propose two novel methods for compression: one based on eliminating lowly active channels and the other on coupling pruning with repeated use of already computed elements. Pruning of entire channels is an appealing idea, since it leads to direct saving in run time in almost every reasonable architecture.

Journal ArticleDOI
TL;DR: This paper describes a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems and describes applications of this sparse signal processing paradigm in Multiple Input Multiple Output random access, cloud radio access networks, compressive channel-source network coding, and embedded security.
Abstract: As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges, and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper, we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will also describe applications of this sparse signal processing paradigm in Multiple Input Multiple Output random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize an important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.

Journal ArticleDOI
TL;DR: A framework is presented, which results in more effective handling of control saturations and provides a means for incorporating a whole family of user-defined constraints into the online computation of a CLF-based controller.
Abstract: This paper presents a novel method to address the actuator saturation for nonlinear hybrid systems by directly incorporating user-defined input bounds in a controller design In particular, we consider the application of bipedal walking and show that our method [based on a quadratic programming (QP) implementation of a control Lyapunov function (CLF)-based controller] enables a gradual performance degradation while still continuing to walk under increasingly stringent input bounds We draw on our previous work, which has demonstrated the effectiveness of the CLF-based controllers for stabilizing periodic gaits for biped walkers This paper presents a framework, which results in more effective handling of control saturations and provides a means for incorporating a whole family of user-defined constraints into the online computation of a CLF-based controller This paper concludes with an experimental validation of the main results on the bipedal robot MABEL, demonstrating the usefulness of the QP-based CLF approach for real-time robotic control

Journal ArticleDOI
TL;DR: The state-of-the-art AI-based techniques for evolving the smarter HetNets infrastructure and systems are discussed, focusing on the research issues of self-configuration, self-healing, and self-optimization, respectively.
Abstract: Recently, mobile networking systems have been designed with more complexity of infrastructure and higher diversity of associated devices and resources, as well as more dynamical formations of networks, due to the fast development of current Internet and mobile communication industry. In such emerging mobile heterogeneous networks (HetNets), there are a large number of technical challenges focusing on the efficient organization, management, maintenance, and optimization, over the complicated system resources. In particular, HetNets have attracted great interest from academia and industry in deploying more effective solutions based on artificial intelligence (AI) techniques, e.g., machine learning, bio-inspired algorithms, fuzzy neural network, and so on, because AI techniques can naturally handle the problems of large-scale complex systems, such as HetNets towards more intelligent and automatic-evolving ones. In this paper, we discuss the state-of-the-art AI-based techniques for evolving the smarter HetNets infrastructure and systems, focusing on the research issues of self-configuration, self-healing, and self-optimization, respectively. A detailed taxonomy of the related AI-based techniques of HetNets is also shown by discussing the pros and cons for various AI-based techniques for different problems in HetNets. Opening research issues and pending challenges are concluded as well, which can provide guidelines for future research work.

Journal ArticleDOI
TL;DR: A tree-cluster-based data-gathering algorithm for WSNs with a mobile sink that can significantly balance the load of the whole network, reduce the energy consumption, alleviate the hotspot problem, and prolong the network lifetime is proposed.
Abstract: Wireless sensor networks (WSNs) have been widely applied in various industrial applications, which involve collecting a massive amount of heterogeneous sensory data. However, most of the data-gathering strategies for WSNs cannot avoid the hotspot problem in local or whole deployment area. Hotspot problem affects the network connectivity and decreases the network lifetime. Hence, we propose a tree-cluster-based data-gathering algorithm (TCBDGA) for WSNs with a mobile sink. A novel weight-based tree-construction method is introduced. The root nodes of the constructed trees are defined as rendezvous points (RPs). Additionally, some special nodes called subrendezvous points (SRPs) are selected according to their traffic load and hops to root nodes. RPs and SRPs are viewed as stop points of the mobile sink for data collection, and can be reselected after a certain period. The simulation and comparison with other algorithms show that our TCBDGA can significantly balance the load of the whole network, reduce the energy consumption, alleviate the hotspot problem, and prolong the network lifetime.

Journal ArticleDOI
TL;DR: An optimization algorithm, which can provide a schedule for smart home appliance usage, is proposed based on the mixed-integer programming technique and shows that adding a PV system in the home results in the reduction of electricity bills and the export of energy to the national grid in times when solar energy production is more than the demand of the home.
Abstract: In this paper, we propose a solution to the problem of scheduling of a smart home appliance operation in a given time range. In addition to power-consuming appliances, we adopt a photovoltaic (PV) panel as a power-producing appliance that acts as a micro-grid. An appliance operation is modeled in terms of uninterruptible sequence phases, given in a load demand profile with a goal of minimizing electricity cost fulfilling duration, energy requirement, and user preference constraints. An optimization algorithm, which can provide a schedule for smart home appliance usage, is proposed based on the mixed-integer programming technique. Simulation results demonstrate the utility of our proposed solution for appliance scheduling. We further show that adding a PV system in the home results in the reduction of electricity bills and the export of energy to the national grid in times when solar energy production is more than the demand of the home.

Journal ArticleDOI
G. Zhao1, Ke Xu1, Li Xu1, Bo Wu1
TL;DR: A novel system placed at the network egress point that aims to efficiently and effectively detect APT malware infections based on malicious DNS and traffic analysis and built a reputation engine to compute a reputation score for an IP address using these features vector together.
Abstract: Advanced persistent threat (APT) is a serious threat to the Internet. With the aid of APT malware, attackers can remotely control infected machines and steal sensitive information. DNS is popular for malware to locate command and control (C&C) servers. In this paper, we propose a novel system placed at the network egress point that aims to efficiently and effectively detect APT malware infections based on malicious DNS and traffic analysis. The system uses malicious DNS analysis techniques to detect suspicious APT malware C&C domains, and then analyzes the traffic of the corresponding suspicious IP using the signature-based and anomaly based detection technology. We extracted 14 features based on big data to characterize different properties of malware-related DNS and the ways that they are queried, and we also defined network traffic features that can identify the traffic of compromised clients that have remotely been controlled. We built a reputation engine to compute a reputation score for an IP address using these features vector together. Our experiment was performed at a large local institute network for two months, and all the features were studied with big data, which includes $\sim 400$ million DNS queries. Our security approach cannot only substantially reduce the volume of network traffic that needs to be recorded and analyzed but also improve the sustainability of the system.

Journal ArticleDOI
TL;DR: CMOS compatible Si-NW FET nanobiosensors are summarized and recent developments in device fabrication, fluid integration, surface functionalization, and biosensing applications are summarized.
Abstract: Silicon nanowire field-effect transistors (Si-NW FETs) have been demonstrated as a versatile class of potentiometric nanobiosensors for real time, label-free, and highly sensitive detection of a wide range of biomolecules. In this review, we summarize the principles of such devices and recent developments in device fabrication, fluid integration, surface functionalization, and biosensing applications. The main focus of this review is on CMOS compatible Si-NW FET nanobiosensors.

Journal ArticleDOI
TL;DR: A genetic algorithm is employed for tuning the parameters of the ESN and its prediction accuracy is compared with a standard autoregressive integrated moving average model.
Abstract: In this paper, we approach the problem of forecasting a time series (TS) of an electrical load measured on the Azienda Comunale Energia e Ambiente (ACEA) power grid, the company managing the electricity distribution in Rome, Italy, with an echo state network (ESN) considering two different leading times of 10 min and 1 day. We use a standard approach for predicting the load in the next 10 min, while, for a forecast horizon of one day, we represent the data with a high-dimensional multi-variate TS, where the number of variables is equivalent to the quantity of measurements registered in a day. Through the orthogonal transformation returned by PCA decomposition, we reduce the dimensionality of the TS to a lower number $k$ of distinct variables; this allows us to cast the original prediction problem in $k$ different one-step ahead predictions. The overall forecast can be effectively managed by $k$ distinct prediction models, whose outputs are combined together to obtain the final result. We employ a genetic algorithm for tuning the parameters of the ESN and compare its prediction accuracy with a standard autoregressive integrated moving average model.

Journal ArticleDOI
TL;DR: A comprehensive survey of the cloud radio access network (RAN) and fog network structures is conducted, and possible harmonization to integrate both for the diverse needs of 5G mobile communications is investigated.
Abstract: To guarantee the ubiquitous and fully autonomous Internet connections in our daily life, the new technical challenges of mobile communications lie on the efficient utilization of resource and social information. To facilitate the innovation of the fifth generation (5G) networks, the cloud radio access network (RAN) and fog network have been proposed to respond newly emerging traffic demands. The cloud RAN functions more toward centralized resource management to achieve optimal transmissions. The fog network takes advantage of social information and edge computing to efficiently alleviate the end-to-end latency. In this paper, we conduct a comprehensive survey of these two network structures, and then investigate possible harmonization to integrate both for the diverse needs of 5G mobile communications. We analytically study the harmonization of cloud RAN and fog network from various points of view, including the cache of Internet contents, mobility management, and radio access control. The performance of transition between the cloud RAN and the fog network has been presented and the subsequent switching strategy has been proposed to ensure engineering flexibility and success.

Journal ArticleDOI
TL;DR: The theoretical and practical implications of the developed models will push the research frontier of proactive response and recovery schemes in electric power grids, while its flexibility will support application to a variety of infrastructures, in response to a wide range of extreme weather events and natural disasters.
Abstract: This paper presents a significant change in current electric power grid response and recovery schemes by developing a framework for proactive recovery of electric power assets with the primary objective of resiliency enhancement. Within the proposed framework, which can potentially present the next generation decision-making tool for proactive recovery, several coordinated models will be developed including: 1) the outage models to indicate the impact of hurricanes on power system components; 2) a stochastic pre-hurricane crew mobilization model for managing resources before the event; and 3) a deterministic post-hurricane recovery model for managing resources after the event. Proposed models will be extended to ensure applicability to a variety of electric power grids with different technologies and regulatory issues. The theoretical and practical implications of the developed models will push the research frontier of proactive response and recovery schemes in electric power grids, while its flexibility will support application to a variety of infrastructures, in response to a wide range of extreme weather events and natural disasters.

Journal ArticleDOI
TL;DR: A hierarchal D2D communication architecture where a centralized software-defined network (SDN) controller communicates with the cloud head to reduce the number of requested long-term evolution (LTE) communication links, thereby improving energy consumption is proposed.
Abstract: The device-to-device (D2D) communication paradigm in 5G networks provides an effective infrastructure to enable different smart city applications such as public safety. In future smart cities, dense deployment of wireless sensor networks (WSNs) can be integrated with 5G networks using D2D communication. D2D communication enables direct communication between nearby user equipments (UEs) using cellular or ad hoc links, thereby improving the spectrum utilization, system throughput, and energy efficiency of the network. In this paper, we propose a hierarchal D2D communication architecture where a centralized software-defined network (SDN) controller communicates with the cloud head to reduce the number of requested long-term evolution (LTE) communication links, thereby improving energy consumption. The concept of local and central controller enables our architecture to work in case of infrastructure damage and hotspot traffic situation. The architecture helps to maintain the communication between disaster victims and first responders by installing multi-hop routing path with the support of the SDN controller. In addition, we highlight the robustness and potential of our architecture by presenting a public safety scenario, where a part of the network is offline due to extraordinary events such as disaster or terrorist attacks.

Journal ArticleDOI
TL;DR: The most common and most efficient known spreading techniques are considered, looking for spreading parameters that ensure the highest EMI reduction and the lowest performance reduction in the circuit where the spreading is applied.
Abstract: Spread spectrum is a technique introduced for mitigating electromagnetic interference (EMI) problems in many class of circuits. In this paper, with particular emphasis on switching DC/DC converters, we consider the most common and most efficient known spreading techniques, looking for spreading parameters that ensure the highest EMI reduction and the lowest performance reduction in the circuit where the spreading is applied. The result is an interesting tradeoff not only between EMI reduction and performance drop, but also on the EMI reduction itself when considering different EMI victim models. The proposed analysis is supported by measurements on two switching DC/DC converters: 1) based on pulse-width modulation and 2) based on the resonant converter class.

Journal ArticleDOI
TL;DR: A study on the bandwidth performance of the proposed design reveals that wide bandwidth can be achieved for the antenna by choosing a thick supporting substrate between the water patch and the ground plane, and can be conveniently integrated with the solar cells to realize a dual-function design.
Abstract: A novel water dense dielectric patch antenna (DDPA) fed by an L-shaped probe is proposed and investigated. In contrast to the water antennas in the literature, including the water monopole and the water dielectric resonator antenna, the operation mechanism of the proposed water DDPA is similar to the conventional metallic patch antenna. The antenna is excited in a mode like the TM $_{{\textrm {10}}}$ mode of the rectangular patch antenna. An L-shaped probe, which is widely used for the conventional patch antenna, is used to excite the water DDPA. A study on the bandwidth performance of the proposed design reveals that wide bandwidth can be achieved for the antenna by choosing a thick supporting substrate between the water patch and the ground plane. A prototype is fabricated to confirm the correctness of the design. An impedance bandwidth of 8%, maximum gain of 7.3 dBi, radiation efficiency up to 70%, and symmetrically unidirectional patterns with low backlobe and low cross polarization levels are obtained. Furthermore, owing to the transparency of the water patch, the proposed water DDPA can be conveniently integrated with the solar cells to realize a dual-function design. Measurements on the prototype demonstrate that the existence of the solar cells does not significantly affect the performance of the antenna and vice versa.

Journal ArticleDOI
TL;DR: This paper uses a low-cost solution for developing the virtual and remote labs shared in this open course, based on the use of a free authoring tool Easy Java/Javascript Simulations (EJsS) for building the laboratories' user interfaces and a cheap development platform board (BeagleBone Black).
Abstract: This paper presents an open course in the University Network of Interactive Laboratories, which offers several virtual and remote laboratories on automatic control, accessible to anyone. All the details on one of these labs (a two electric coupled drives system that allows performing control practices in a 2 $\times $ 2 MIMO system with industrial applications) and the activities that can be performed with it are given. We use a low-cost solution for developing the virtual and remote labs shared in this open course, based on the use of a free authoring tool Easy Java/Javascript Simulations (EJsS) for building the laboratories’ user interfaces and a cheap development platform board (BeagleBone Black). The virtual and remote labs are deployed into a free Learning Management System (Moodle) Web environment that facilitates their management and maintenance.