38 research outputs found

    Softwarization in Future Mobile Networks and Energy Efficient Networks

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    The data growth generated by pervasive mobile devices and the Internet of Things at the network edge (i.e., closer to mobile users), couple with the demand for ultra-low latency, requires high computation resources which are not available at the end-user device. This demands a new network design paradigm in order to handle user demands. As a remedy, a new MN network design paradigm has emerged, called Mobile Edge Computing (MEC), to enable low-latency and location-aware data processing at the network edge. MEC is based on network function virtualization (NFV) technology, where mobile network functions (NFs) that formerly existed in the evolved packet core (EPC) are moved to the access network [i.e., they are deployed on local cloud platforms in proximity to the base stations (BSs)]. In order to reap the full benefits of the virtualized infrastructure, the NFV technology shall be combined with intelligent mechanisms for handling network resources. Despite the potential benefits presented by MEC, energy consumption is a challenge due to the foreseen dense deployment of BSs empowered with computation capabilities. In the effort to build greener 5G mobile network (MN), we advocate the integration of energy harvesting (EH) into future edge systems

    Energy sustainable paradigms and methods for future mobile networks: A survey

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    In this survey, we discuss the role of energy in the design of future mobile networks and, in particular, we advocate and elaborate on the use of energy harvesting (EH) hardware as a means to decrease the environmental footprint of 5G technology. To take full advantage of the harvested (renewable) energy, while still meeting the quality of service required by dense 5G deployments, suitable management techniques are here reviewed, highlighting the open issues that are still to be solved to provide eco-friendly and cost-effective mobile architectures. Several solutions have recently been proposed to tackle capacity, coverage and efficiency problems, including: C-RAN, Software Defined Networking (SDN) and fog computing, among others. However, these are not explicitly tailored to increase the energy efficiency of networks featuring renewable energy sources, and have the following limitations: (i) their energy savings are in many cases still insufficient and (ii) they do not consider network elements possessing energy harvesting capabilities. In this paper, we systematically review existing energy sustainable paradigms and methods to address points (i) and (ii), discussing how these can be exploited to obtain highly efficient, energy self-sufficient and high capacity networks. Several open issues have emerged from our review, ranging from the need for accurate energy, transmission and consumption models, to the lack of accurate data traffic profiles, to the use of power transfer, energy cooperation and energy trading techniques. These challenges are here discussed along with some research directions to follow for achieving sustainable 5G systems.Comment: Accepted by Elsevier Computer Communications, 21 pages, 9 figure

    Bayesian Learning Strategies in Wireless Networks

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    This thesis collects the research works I performed as a Ph.D. candidate, where the common thread running through all the works is Bayesian reasoning with applications in wireless networks. The pivotal role in Bayesian reasoning is inference: reasoning about what we don’t know, given what we know. When we make inference about the nature of the world, then we learn new features about the environment within which the agent gains experience, as this is what allows us to benefit from the gathered information, thus adapting to new conditions. As we leverage the gathered information, our belief about the environment should change to reflect our improved knowledge. This thesis focuses on the probabilistic aspects of information processing with applications to the following topics: Machine learning based network analysis using millimeter-wave narrow-band energy traces; Bayesian forecasting and anomaly detection in vehicular monitoring networks; Online power management strategies for energy harvesting mobile networks; Beam training and data transmission optimization in millimeter-wave vehicular networks. In these research works, we deal with pattern recognition aspects in real-world data via supervised/unsupervised learning methods (classification, forecasting and anomaly detection, multi-step ahead prediction via kernel methods). Finally, the mathematical framework of Markov Decision Processes (MDPs), which also serves as the basis for reinforcement learning, is introduced, where Partially Observable MDPs use the notion of belief to make decisions about the state of the world in millimeter-wave vehicular networks. The goal of this thesis is to investigate the considerable potential of inference from insightful perspectives, detailing the mathematical framework and how Bayesian reasoning conveniently adapts to various research domains in wireless networks

    Sustainable marine ecosystems: deep learning for water quality assessment and forecasting

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    An appropriate management of the available resources within oceans and coastal regions is vital to guarantee their sustainable development and preservation, where water quality is a key element. Leveraging on a combination of cross-disciplinary technologies including Remote Sensing (RS), Internet of Things (IoT), Big Data, cloud computing, and Artificial Intelligence (AI) is essential to attain this aim. In this paper, we review methodologies and technologies for water quality assessment that contribute to a sustainable management of marine environments. Specifically, we focus on Deep Leaning (DL) strategies for water quality estimation and forecasting. The analyzed literature is classified depending on the type of task, scenario and architecture. Moreover, several applications including coastal management and aquaculture are surveyed. Finally, we discuss open issues still to be addressed and potential research lines where transfer learning, knowledge fusion, reinforcement learning, edge computing and decision-making policies are expected to be the main involved agents.Postprint (published version

    Oblivious Network Optimization and Security Modeling in Sustainable Smart Grids and Cities

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    Today\u27s interconnected world requires an inexpensive, fast, and reliable way of transferring information. There exists an increasingly important need for intelligent and adaptable routing of network flows. In the last few years, many researchers have worked toward developing versatile solutions to the problem of routing network flows in unpredictable circumstances. These attempts have evolved into a rich literature in the area of oblivious network design which typically route the network flows via a routing scheme that makes use of a spanning tree or a set of trees of the graph representation of the network. In the first chapter, we provide an introduction to network design. This introductory chapter has been designed to clarify the importance and position of oblivious routing problems in the context of network design as well as its containing field of research. Part I of this dissertation discusses the fundamental role of linked hierarchical data structures in providing the mathematical tools needed to construct rigorous versatile routing schemes and applies hierarchical routing tools to the process of constructing versatile routing schemes. Part II of this dissertation applies the routing tools generated in Part I to address real-world network optimization problems in the area of electrical power networks, clusters of micrograms, and content-centric networks. There is an increasing concern regarding the security and privacy of both physical and communication layers of smart interactive customer-driven power networks, better known as smart grids. Part III of this dissertation utilizes an advanced interdisciplinary approach to address existing security and privacy issues, proposing legitimate countermeasures for each of them from the standpoint of both computing and electrical engineering. The proposed methods are theoretically proven by mathematical tools and illustrated by real-world examples

    DECOMOBIL Roadmap for research on Human Centred Design of ICT for clean and safe mobility. Deliverable 2.2

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    The scientific seminar on 'Roadmap of Information & Communication Technology design for clean and efficient multimodal mobility' organized by Ifsttar in the framework of the European project DECOMOBIL, has been held the 28th of May 2013 in Munich, Germany. The aims of the event were to overview perspectives of research in the domain of ICT and green transport, with presentation of the main key issues, the on-going major projects, some outstanding results and the scientific and technical lacks of knowledge to overcome, in order to debate about future steps to follow to reach identified and consensual objectives in this domain. Speakers have been identified as key experts in the ecomobility research areas, with diversified points of view and approaches, in order to give to the audience a holistic vision of this issue. During this seminar, an overview of European projects on ecomobility such as eCoMove, compass4D, Adasis, Amitran, has been provided. Experience gained from the iMobility WG on ICT for clean and efficient mobility, which aims providing a vision on eco-friendly mobility, has been presented. Priorities for road safety research in Europe have been defined through the presentation of the PROS project, and transport cross-modal considerations on safety and human factors have been discussed through the presentation of the EXCROSS project. Perspectives on Powered-Two-Wheels contribution to ecomobility in addition to sustainable driving/riding training for a safe and cost efficient behavior have been drawn. Finally, main issues related to design, integration and safety of mobile service for ecomobility and concept of cooperative services have been presented and discussed.A round table allowed the audience to interact in a fruitful way with all the speakers of the day.After summarizing the context linked to ecomobility at a European level, this report gathers a summary of each presentation in addition to the full set of slides displayed at the seminar.Furthermore, all the presentations (slides and video recordings of the speakers) are available for downloading on the DECOMOBIL website http://decomobil.humanist-vce.eu/Downloads.html Document type: Repor
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