Extract, Transform, and Load data from Legacy Systems to Azure Cloud

Internship report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business IntelligenceIn a world with continuously evolving technologies and hardened competitive markets, organisations need to continually be on guard to grasp cutting edge technology and tools that will help them to surpass any competition that arises. Modern data platforms that incorporate cloud technologies, support organisations to strive and get ahead of their competitors by providing solutions that help them capture and optimally use untapped data, and scalable storages to adapt to ever-growing data quantities. Also, adopt data processing and visualisation tools that help to improve the decision-making process. With many cloud providers available in the market, from small players to major technology corporations, this offers much flexibility to organisations to choose the best cloud technology that will align with their use cases and overall products and services strategy. This internship came up at the time when one of Accenture’s significant client in the financial industry decided to migrate from legacy systems to a cloud-based data infrastructure that is Microsoft Azure cloud. During this internship, development of the data lake, which is a core part of the MDP, was done to understand better the type of challenges that can be faced when migrating data from on-premise legacy systems to a cloud-based infrastructure. Also, provided in this work, are the main recommendations and guidelines when it comes to performing a large scale data migration

Distributed Shared Memory based Live VM Migration

Cloud computing is the new trend in computing services and IT industry, this computing paradigm has numerous benefits to utilize IT infrastructure resources and reduce services cost. The key feature of cloud computing depends on mobility and scalability of the computing resources, by managing virtual machines. The virtualization decouples the software from the hardware and manages the software and hardware resources in an easy way without interruption of services. Live virtual machine migration is an essential tool for dynamic resource management in current data centers. Live virtual machine is defined as the process of moving a running virtual machine or application between different physical machines without disconnecting the client or application. Many techniques have been developed to achieve this goal based on several metrics (total migration time, downtime, size of data sent and application performance) that are used to measure the performance of live migration. These metrics measure the quality of the VM services that clients care about, because the main goal of clients is keeping the applications performance with minimum service interruption. The pre-copy live VM migration is done in four phases: preparation, iterative migration, stop and copy, and resume and commitment. During the preparation phase, the source and destination physical servers are selected, the resources in destination physical server are reserved, and the critical VM is selected to be migrated. The cloud manager responsibility is to make all of these decisions. VM state migration takes place and memory state is transferred to the target node during iterative migration phase. Meanwhile, the migrated VM continues to execute and dirties its memory. In the stop and copy phase, VM virtual CPU is stopped and then the processor and network states are transferred to the destination host. Service downtime results from stopping VM execution and moving the VM CPU and network states. Finally in the resume and commitment phase, the migrated VM is resumed running in the destination physical host, the remaining memory pages are pulled by destination machine from the source machine. The source machine resources are released and eliminated. In this thesis, pre-copy live VM migration using Distributed Shared Memory (DSM) computing model is proposed. The setup is built using two identical computation nodes to construct all the proposed environment services architecture namely the virtualization infrastructure (Xenserver6.2 hypervisor), the shared storage server (the network file system), and the DSM and High Performance Computing (HPC) cluster. The custom DSM framework is based on a low latency memory update named Grappa. Moreover, HPC cluster is used to parallelize the work load by using CPUs computation nodes. HPC cluster employs OPENMPI and MPI libraries to support parallelization and auto-parallelization. The DSM allows the cluster CPUs to access the same memory space pages resulting in less memory data updates, which reduces the amount of data transferred through the network. The thesis proposed model achieves a good enhancement of the live VM migration metrics. Downtime is reduced by 50 % in the idle workload of Windows VM and 66.6% in case of Ubuntu Linux idle workload. In general, the proposed model not only reduces the downtime and the total amount of data sent, but also does not degrade other metrics like the total migration time and the applications performance

WRITE-INTENSIVE DATA MANAGEMENT IN LOG-STRUCTURED STORAGE

Ph.DDOCTOR OF PHILOSOPH

Система управління та моніторингу безпілотного літального апарату. Підсистема моніторингу (компл.)

Робота публікується згідно наказу Ректора НАУ від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт здобувачів вищої освіти в репозиторії університету". Керівник роботи: д.т.н., професор, зав. кафедри авіаційних комп’ютерно-інтегрованих комплексів, Синєглазов Віктор МихайловичRecently, unmanned aviation has been rapidly developing. The development of unmanned aerial systems based on unmanned aerial vehicles is currently carried out by almost all industrialized countries of the world. Until recently, UAVs had a military purpose, now the use of UAVs is effective both in military and civilian tasks, for example, in combating the consequences of emergencies, natural disasters, agricultural applications, reconnaissance and aerial photography. The impetus for the development of unmanned aviation worldwide was the need for light, relatively cheap aircraft with high maneuverability characteristics and capable of performing a wide range of tasks. Unmanned aerial vehicles are successfully used in military operations around the world, and at the same time they successfully perform civilian tasks. Today, most of the existing unmanned aerial vehicles are piloted manually, using remote controls operating on radio channels. When manually piloting Unmanned aerial vehicles, there are difficulties associated with pilot training, insufficient operating range, and weather restrictions. UAV control is the task of a well-trained professional. For example, in the U.S. Army, UAV operators become active duty Air Force pilots after a year of preparation and training. In many aspects, it is more difficult than piloting an aircraft and, as is known, most accidents of unmanned aircraft are due to pilot-operator errors and mechanical failures. According to the official data provided for 2012, 70 unmanned aircraft crashed in the US Air Force.Останнім часом стрімко розвивається безпілотна авіація. Розробкою безпілотних авіаційних систем на базі безпілотних літальних апаратів в даний час займаються практично всі промислово розвинені країни світу. До недавнього часу БПЛА мали військове призначення, зараз використання БПЛА ефективно як в військові та цивільні завдання, наприклад, у боротьбі з наслідками надзвичайних ситуацій, стихійних лих, застосування в сільському господарстві, розвідка та аерофотозйомка. Поштовхом до розвитку безпілотної авіації в усьому світі стала потреба в легких, відносно дешевих літальних апаратах з високими маневреними характеристиками, здатних виконувати широкий спектр завдань. Безпілотні літальні апарати успішно використовуються у військових діях по всьому світу, і в той же час вони успішно виконують цивільні завдання. Сьогодні більшість існуючих безпілотних літальних апаратів управляються вручну, за допомогою пультів дистанційного керування, що працюють по радіоканалах. При ручному пілотуванні безпілотних літальних апаратів виникають труднощі, пов’язані з підготовкою пілотів, недостатньою дальністю польоту та погодними обмеженнями. Керування БПЛА – це завдання добре підготовленого професіонала. Наприклад, в армії США оператори БПЛА стають активними пілотами ВПС після року підготовки та навчання. У багатьох аспектах це складніше, ніж пілотування літака, і, як відомо, більшість аварій безпілотних літальних апаратів відбувається через помилки пілота-оператора та механічні несправності. За офіційними даними, наданими за 2012 рік, у ВПС США розбилося 70 безпілотних літаків

The 1995 Research Reports: NASA/ASEE Summer Faculty Fellowship Program

This document is a collection of technical reports on research conducted by the participants in the 1995 NASA/ASEE Summer Faculty Fellowship Program at the Kennedy Space Center (KSC). This was the eleventh year that a NASA/ASEE program has been conducted at KSC. The 1995 program was administered by the University of Central Florida in cooperation with KSC. The program was operated under the auspices of the American Society for Engineering Education (ASEE) with sponsorship and funding from the Office of Educational Affairs, NASA Headquarters, Washington, D.C. The KSC Program was one of nine such Aeronautics and Space Research Programs funded by NASA Headquarters in 1995. The NASA/ASEE Program is intended to be a two-year program to allow in-depth research by the University faculty member

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii