Software-Defined Infrastructure for IoT-based Energy Systems

Internet of Things (IoT) devices are becoming an essential part of our everyday lives. These physical devices are connected to the internet and can measure or control the environment around us. Further, IoT devices are increasingly being used to monitor buildings, farms, health, and transportation. As these connected devices become more pervasive, these devices will generate vast amounts of data that can be used to gain insights and build intelligence into the system. At the same time, large-scale deployment of these devices will raise new challenges in efficiently managing and controlling them. In this thesis, I argue that the IoT devices need programmability and need to provide software controls in order to manage them efficiently. Further, it will need data-driven modeling techniques to process and analyze a vast amount of data from heterogeneous devices to derive actionable insights. My thesis explores the problems posed by software-defined IoT energy infrastructure. I present four techniques that use systems and machine learning principles to design, analyze and deploy the next generation of smart IoT energy systems. First, I discuss how current state-of-the-art LIDAR-based approaches in identifying ideal locations on rooftops for deploying energy systems such as solar do not scale to many regions of the world. To address the challenges, I propose DeepRoof, a data-driven approach that uses deep learning to estimate the solar potential of roofs using satellite imagery and identify ideal locations for installation. We evaluate our approach on different types of roof and show that our technique is comparable to LIDAR-based methods. Second, I study how excessive solar can cause problems in the grid and examine how programmatic control of the solar output can prevent congestion in the electric grid. Further, I present a decentralized approach that can control the solar arrays in a grid-friendly manner. Also, my approach provides flexible control of solar output, and I show that such mechanisms allow for higher solar penetration in the grid. Third, I discuss the challenges in community-owned (and shared) distributed energy resources that do not provide independent control to users. To do so, I propose vSolar, an approach to virtualize the solar arrays and energy storage that allows independent control. Further, I show how using vSolar users can exercise independent control, implement their custom energy sharing policies, and reduce energy costs through energy trading. Finally, I present the challenges, and the high throughput needs to enable a peer-to-peer energy trading platform using permissioned blockchains. I propose FabricPlus, an enhanced Hyperledger Fabric blockchain, that contains a series of optimizations to enable high throughput transactions. FabricPlus increases the transaction throughput many folds, without requiring any changes to its external interfaces. I also show considerable performance improvement over the baseline Fabric

Wireless Network Virtualization as an Enabler for Spectrum Sharing

Spectrum Sharing and Wireless Network Virtualization have been explored as methods to achieve spectrum efficiency, increase network capacity and, overall, to address the existing spectrum scarcity problems. This work aims at exploring the link between these two topics, by specifically placing virtualization as a technology that can render spectrum sharing schemes feasible. No complete analysis can be made without taking into account three important axes: technology, policy and economics. In this light, in order to explore how virtualization enables spectrum sharing, flexibility is studied as a common attribute, due to the characteristics it presents regarding the three preceding axes. By determining how spectrum sharing, wireless virtualization and flexibility tie together, ground can be laid toward exploring further opportunities that would enhance spectrum usage, making it possible for this resource to foster these days’ ever-increasing demand

Orchestration of Crosshaul slices from federated administrative domains

Proceeding of: 2016 European Conference on Networks and Communications (EuCNC)With the advent of 5G networks, more dynamicity and flexibility will be needed for the deployment of services with very distinct requirements. Crosshaul areas (those integrating fronthaul and backhaul) are especially critical because of the variability of the demand and the cost of the (own) network deployment, which in many cases is jeopardized by the huge level of investment needed. A common market place to trade the required networking and computing facilities (in the form of a slice) in a multi-domain federated environment is envisaged as the solution for easing the adaptation to future demands. This paper proposes to develop the concept of multi-domain Crosshaul by enabling the dynamic request of Crosshaul slices through a multi-provider exchange.This work has been supported by the European Community through the projects 5GEx (grant no. 671636) and 5GCrosshaul (grant no. 671598) within the H2020 programme

Small cell cloud proof of concept implementation and monitoring schemes analysis

Cloud Computing has grown exponentially in popularity in the last few years, becoming a key technology for both personal and enterprise applications due to the numerous benefits it offers. On the other hand, Small Cell technology is considered by many to be the solution to the challenges that are expected to arise caused by the continuously increasing number of interconnected mobile devices. This project presents a basic design and a proof of concept implementation of a Small Cell Cloud, a current research field on mobile communications that aims to leverage the capabilities offered by the parallel and distributed computation of Cloud Computing to enhance Small Cells functionality. The purpose of the described Small Cell Cloud is to allow application offloading of mobile devices to Small Cells, allowing the execution of more resource demanding applications at the same time energy consumption is reduced in those devices. Furthermore, a detailed analysis on different Small Cell monitoring schemes is carried out, comparing the achieved performance with each of them in terms of data reliability and generated network traffic. Finally, based on the proof of concept implementation and a series of stress performance test, conclusions on the viability of the proposed Small Cell Cloud design and the most appropriate monitoring scheme are presented. Guidelines for future research work are also provided, considering the work developed in this project as a first step towards a new mobile technology.Ingeniería de Telecomunicació