A novel complex system approach for the determination of renewable energy sources impact on electricity infrastructures

The increasing environmental awareness, associated with the increasing demand and price of fossil fuels, is leading to the implementation of novel energy models based on renewable energy sources (RES) and sustainable mobility. However, the actual physical and economic models on which power system management rules are based on, are not able to properly manage the high amount of unwanted power fluctuations introduced by RES power generation. For such reason, major issues has been pointed out in term of energy security and access, inspiring changes in methods and paradigms associated to energy supply management. Moreover, the transaction towards an emission free mobility must be based on the interaction between RES generation and Electric Vehicles (EV) mobility, pointing out the need of a new approach able to combine mobility and energy supply infrastructures. In order to describe and model power systems with an high amount of RES generation, is important to indicate that such systems are made by a great number of microscopical interacting elements which behave in a stochastic way. For this reason, these systems can not easily be described in a deterministic way, but must be described by a statistical representation of the system observables. In this thesis, a novel approach based on statistical mechanics methods is presented, able to model the impact of such sources over the system. By using such approach, has been possible to evaluate the possible impact of such sources in terms of power system stability and sustainable mobility

Protection and efficient management of big health data in cloud environment

University of Technology Sydney. Faculty of Engineering and Information Technology.Healthcare data has become a great concern in the academic world and in industry. The deployment of electronic health records (EHRs) and healthcare-related services on cloud platforms will reduce the cost and complexity of handling and integrating medical records while improving efficiency and accuracy. To make effective use of advanced features such as high availability, reliability, and scalability of Cloud services, EHRs have to be stored in the clouds. By exposing EHRs in an outsourced environment, however, a number of serious issues related to data security and privacy, distribution and processing such as the loss of the controllability, different data formats and sizes, the leakage of sensitive information in processing, sensitive-delay requirements has been naturally raised. Many attempts have been made to address the above concerns, but most of the attempts tackled only some aspects of the problem. Encryption mechanisms can resolve the data security and privacy requirements but introduce intensive computing overheads as well as complexity in key distribution. Data is not guaranteed being protected when it is moved from one cloud to another because clouds may not use equivalent protection schemes. Sensitive data is being processed at only private clouds without sufficient resources. Consequently, Cloud computing has not been widely adopted by healthcare providers and users. Protecting and managing health data efficiently in many aspects is still an open question for current research. In this dissertation, we investigate data security and efficient management of big health data in cloud environments. Regarding data security, we establish an active data protection framework to protect data; we investigate a new approach for data mobility; we propose trusted evaluation for cloud resources in processing sensitive data. For efficient management, we investigate novel schemes and models in both Cloud computing and Fog computing for data distribution and data processing to handle the rapid growth of data, higher security on demand, and delay requirements. The novelty of this work lies in the novel data mobility management model for data protection, the efficient distribution scheme for a large-scale of EHRs, and the trust-based scheme in security and processing. The contributions of this thesis can be summarized according to data security and efficient data management. On data security, we propose a data mobility management model to protect data when it is stored and moved in clouds. We suggest a trust-based scheduling scheme for big data processing with MapReduce to fulfil both privacy and performance issues in a cloud environment. • The data mobility management introduces a new location data structure into an active data framework, a Location Registration Database (LRD), protocols for establishing a clone supervisor and a Mobility Service (MS) to handle security and privacy requirements effectively. The model proposes a novel security approach for data mobility and leads to the introduction of a new Data Mobility as a Service (DMaaS) in the Cloud. • The Trust-based scheduling scheme investigates a novel composite trust metric and a real-time trust evaluation for cloud resources to provide the highest trust execution on sensitive data. The proposed scheme introduces a new approach for big data processing to meet with high security requirements. On the efficient data management, we propose a novel Hash-Based File Clustering (HBFC) scheme and data replication management model to distribute, store and retrieve EHRs efficiently. We propose a data protection model and a task scheduling scheme which is Region-based for Fog and Cloud to address security and local performance issues. • The HBFC scheme innovatively utilizes hash functions to cluster files in defined clusters such that data can be stored and retrieved quickly while maintaining the workload balance efficiently. The scheme introduces a new clustering mechanism in managing a large-scale of EHRs to deliver healthcare services effectively in the cloud environment. • The trust-based scheduling model uses the proposed trust metric for task scheduling with MapReduce. It not only provides maximum trust execution but also increases resource utilization significantly. The model suggests a new trust-oriented scheduling mechanism between tasks and resources with MapReduce. • We introduce a novel concept “Region” in Fog computing to handle the data security and local performance issues effectively. The proposed model provides a novel Fog-based Region approach to handle security and local performance requirements. We implement and evaluate our proposed models and schemes intensively based on both real infrastructures and simulators. The outcomes demonstrate the feasibility and the efficiency of our research in this thesis. By proposing innovative concepts, metrics, algorithms, models, and services, the significant contributions of this thesis enable both healthcare providers and users to adopt cloud services widely, and allow significant improvements in providing better healthcare services

D2D communications in 5G mobile cellular networks : we propose and validate a novel approach to mobility management

University of Technology Sydney. Faculty of Engineering and Information Technology.Fifth Generation (5G) stands for future fitness combined with flexible technical solutions that combine with the latest wireless technology. 5G is expected to multiply a thousand times (1000x) in data speed with 20.4 billion devices (IoT) connected to the network by 2020. This literally means everything connecting to everything. From the network point of view, lower latency along with high flexibility is not limited just to 5G. It is already being implemented in real networks. The number of wireless devices connected to networks has increased remarkably over the last couple of decades. Ubiquitous voice and data connections are the fundamental requirements for the next generation of wireless technology. Device-to-Device communication is widely known as D2D. It is a new paradigm for cellular communication. It was initially proposed to boost network performance. It is considered to be an integral part of the next generation (5G) of telecommunications networks. It takes place when two devices communicate directly without significant help from the base station. In a cellular network, Device-to-Device communication has been viewed as a promising technology overcoming many existing problems. These include capacity, quality and scarce spectrum resources. However, this comes at the price of increased interference and complex mobility issues, even though it was proposed as a new paradigm to enhance network performance. Nevertheless, it is still a challenge to manage devices that are moving. Cellular devices without well-managed mobility are hardly acceptable. Considering in-band underlay D2D communication, a well-managed mobility system in cellular communication should have lower latency, lower power consumption and higher data rates. In this dissertation, we review existing mobility management systems for LTE-Advanced technology and propose an algorithm to be used over the current system so that lower signalling overheads and less delay, along with uninterrupted D2D communication, are guaranteed. We model and simulate our algorithm, comparing the results with mathematical models based on Markov theory. As in other similar communication systems, mobility management for D2D communication is yet to be explored fully. There are few research papers published so far. What we can say is that the intention of such systems in cellular networks are to enable lower latency, lower power consumption, less complexity and, last but not least, uninterrupted data connections. Our simulation results validate our proposed model and highlight D2D communication and its mobility issues. An essential element of our proposal is to estimate the user’s location. We can say that a mobility management system for D2D communication is hardly workable if the location of the users is not realisable. This dissertation also shows some latest techniques for estimating the direction of arrival (DOA) with mathematical models and simulation results. Smart antenna systems are proposed. It is possible to determine the location of a user by considering the uplink transmission system. Estimating the channel and actual path delay is also an important task, which might be done by using 1D uniform linear array (ULA) or 2D Uniform Rectangular (URA) array antenna systems. In this chapter, 1D ULA is described utilising some well-known techniques. The channel characteristics largely determine the performance of an end-to-end communication system. It determines the signal transformation while propagating through the channel between receivers and transmitters. Accurate channel information is crucial for both the transmitter and receiver ends to perform at their best. The ultimate focus of this part is to estimate the channel based on 2D parameter estimation. Uniform Rectangular Array (URA) is used to perform the 2D parameter estimation. It is possible to estimate azimuth and elevation of a source by using the URA model. The problem of mobility in this context has been investigated in few papers, with no reliable solutions as yet. We propose a unique algorithm for mobility management for D2D communications. In this dissertation, we highlight and explain the mobility model mathematically and analytically, along with the simulation of the Markovian model. A Markov model is essentially a simplified approach to describing a system that occupies a discrete state at any point in time. We also make a bridge between our mobility algorithm and a Markovian model

A cluster-based approach using smartphone data for bike-sharing docking stations identification: Lisbon case study

Urban mobility is a massive issue in the current century, being widely promoted the need of adopting sustainable solutions regarding transportation within large urban centres. The evolution of technologies has democratised smart cities to better plan and manage their mobility solutions, without compromising the social, economic, and environmental impacts. Pursuing the carbon neutrality and the climate agreement goals, soft mobility is one of the most popular emerging methods to provide greener alternatives regarding mobility. Among these transportation modes are the bicycle, which has been widely used in several public systems across the world, one of them being in Lisbon. This article provides a decision support system for bike-sharing docking stations for three council parishes of the city, namely, Parque das Nações, Marvila, and Beato. Taking advantage of clustering methods and GSM data from a telecommunication operator, this study pretends to highlight a novel approach to identify soft mobility hotspots, in specific bike-sharing docking stations, for suited mobility management systems in Lisbon’s city centre.This research was funded by ANI—Agência Nacional de Inovação within the R&D Units Project Scope: POCI-01-0247-FEDER-045919/2019

A novel mechanical analogy based battery model for SoC estimation using a multi-cell EKF

The future evolution of technological systems dedicated to improve energy efficiency will strongly depend on effective and reliable Energy Storage Systems, as key components for Smart Grids, microgrids and electric mobility. Besides possible improvements in chemical materials and cells design, the Battery Management System is the most important electronic device that improves the reliability of a battery pack. In fact, a precise State of Charge (SoC) estimation allows the energy flows controller to exploit better the full capacity of each cell. In this paper, we propose an alternative definition for the SoC, explaining the rationales by a mechanical analogy. We introduce a novel cell model, conceived as a series of three electric dipoles, together with a procedure for parameters estimation relying only on voltage measures and a given current profile. The three dipoles represent the quasi-stationary, the dynamics and the istantaneous components of voltage measures. An Extended Kalman Filer (EKF) is adopted as a nonlinear state estimator. Moreover, we propose a multi-cell EKF system based on a round-robin approach to allow the same processing block to keep track of many cells at the same time. Performance tests with a prototype battery pack composed by 18 A123 cells connected in series show encouraging results.Comment: 8 page, 12 figures, 1 tabl

Hierarchical Syntactic Models for Human Activity Recognition through Mobility Traces

Recognizing users’ daily life activities without disrupting their lifestyle is a key functionality to enable a broad variety of advanced services for a Smart City, from energy-efficient management of urban spaces to mobility optimization. In this paper, we propose a novel method for human activity recognition from a collection of outdoor mobility traces acquired through wearable devices. Our method exploits the regularities naturally present in human mobility patterns to construct syntactic models in the form of finite state automata, thanks to an approach known as grammatical inference. We also introduce a measure of similarity that accounts for the intrinsic hierarchical nature of such models, and allows to identify the common traits in the paths induced by different activities at various granularity levels. Our method has been validated on a dataset of real traces representing movements of users in a large metropolitan area. The experimental results show the effectiveness of our similarity measure to correctly identify a set of common coarse-grained activities, as well as their refinement at a finer level of granularity

Energy Efficient Mobility Management for the Macrocell – Femtocell LTE Network

Femtocells will play a key role in future deployments of the 3rd Generation Partnership Project (3GPP) the Long Term Evolution (LTE) system, as they are expected to enhance system capacity, and greatly improve the energy-efficiency in a cost-effective manner. Due to the short transmit-receive distance, femtocells prolong handset battery life and enhance the Quality of Service (QoS) perceived by the end users. However, large-scale femtocell deployment comprises many technical challenges, mainly including security, interference and mobility management. Under the viewpoint of energy-efficient mobility management, this chapter discusses the key features of the femtocell technology and presents a novel energy-efficient handover decision policy for the macrocell – femtocell LTE network. The proposed HO decision policy aims at reducing the transmit power of the LTE mobile terminals in a backwards compatible with the standard LTE handover decision procedure. Simulation results show that significantly lower energy and power consumption can be attained if the proposed approach is employed, at the cost of a moderately increased number of handover executions events