Dárkon

Sports today are more competitive than ever, with an eye for extreme details. Small margins can differentiate between succeeding or failing. That is why it is essential for a team to pay attention to all these margins and use them to their advantage. Technology today plays a huge part in sports. With video cameras and sensors following the players’ every move, it is vital to use this technology to gain an advantage over the opponent. This thesis presents Dárkon, a video analysis system to help teams with their video analysis needs. Dárkon works together with a tagging system developed simultaneously to provide filtering based on field position, type of event, and outcome of event to find a video of a specific event or playlist of events. Along with this, Dárkon will attempt to collect videos from different sources, to bring everything into one coherent system. The videos of a single event, sequence, or playlists are generated on the fly from the metadata for the entire video to keep the storage to a minimum, while still being able to only play specific parts of a video from an entire match

Cloud application portability: an initial view.

Growing interest towards cloud application platforms has resulted in a large number of platform offerings to be already available on the market and new related products to be continuously launched. However, there are a number of challenges that prevent cloud application platforms from becoming widely adopted. One such challenge is application portability. This paper reports on an ongoing effort to explore the area of cloud application portability. We briefly examine the issue of heterogeneity in cloud platforms and highlight specific platform characteristics that may hinder the portability of cloud applications. We present some high level approaches and existing work that attempts to address this challenge. In order to narrow down the area of our exploration we have been carrying out an experiment in cross-platform application development and deployment with four prominent cloud platforms: OpenShift, Google App Engine, Heroku, and Amazon Elastic Beanstalk. We briefly discuss our initial conclusions from this ongoing experimentation

Technical Report on Deploying a highly secured OpenStack Cloud Infrastructure using BradStack as a Case Study

Cloud computing has emerged as a popular paradigm and an attractive model for providing a reliable distributed computing model.it is increasing attracting huge attention both in academic research and industrial initiatives. Cloud deployments are paramount for institution and organizations of all scales. The availability of a flexible, free open source cloud platform designed with no propriety software and the ability of its integration with legacy systems and third-party applications are fundamental. Open stack is a free and opensource software released under the terms of Apache license with a fragmented and distributed architecture making it highly flexible. This project was initiated and aimed at designing a secured cloud infrastructure called BradStack, which is built on OpenStack in the Computing Laboratory at the University of Bradford. In this report, we present and discuss the steps required in deploying a secured BradStack Multi-node cloud infrastructure and conducting Penetration testing on OpenStack Services to validate the effectiveness of the security controls on the BradStack platform. This report serves as a practical guideline, focusing on security and practical infrastructure related issues. It also serves as a reference for institutions looking at the possibilities of implementing a secured cloud solution.Comment: 38 pages, 19 figures