Management of and interaction with OLAP cloud service

Cloud Computing ist ein relativ neu entstandenes High Performance Parallel Computing Paradigma. Viele Algorithmen aus der Vergangenheit können nun von Cloud Computing profitieren und neue Möglichkeiten finden. Nach einigen Monaten Untersuchungen zur Theorie und Umsetzung von On-Line Analytical Processing (OLAP), vor allem, die OLAP-Engine aus dem GridMiner Projekt (http://www.gridminer.org), haben wir beschlossen, ein OLAP System für Cloud Computing Umgebung zu entwerfen und Implementieren. Für das Cloud-enabled OLAP System brauchen wir auch Mittel für das Management und Interaktion mit ihm, die durch eine Multi-Tier Client Subsystem einschließlich einiger Business-Logik und Graphical User Interfaces (GUI) umgesetzt werden sollten. In dieser Arbeit die ursprngliche Gestaltung und Umsetzung der Multi-Tier Client Subsystem wird beschriebt und diskutiert. Management und Interaktion mit dem OLAP Cloud bedeutet auf der einen Seite das Laden von Daten aus der Datenquelle, die Umwandlung und Übertragung von Daten auf das OLAP Cloud um Data Cube zu konstruieren, Auf der anderen Seite, Versand von OLAP Analyse Abfragen und Empfang des Ergebnis. Unser Client-Subsystem wurde hauptsächlich mit dem Google Web Toolkit (GWT) als web-basierte Multi-Tier Anwendung entwickelt. Es könnte Daten von verschiedene Datenquelle einlesen, z.B. von Relational Database Management Systeme (RMDBS) oder von integrierten Abfrage-Ergebnis von mehreren RMDBS durch Open Grid Services Architecture - Data Access and Integration (OGSA-DAI) Server, der Distributed Query Processing bietet ( DQP). Operationen wie das Laden von Daten auf OLAP Cloud und OLAP Abfrage sind durch die Interaktion mit dem Representational State Transfer (REST) APIs des OLAP Cloud erreicht. Daten in unserem System werden in WebRowSet Format dargestellt, und die Operationen werden mit OLAP Modelling Markup Language (OMML) version 2.0 beschreibt, die in dieser Masterarbeit vorgeschlagen, beschriebt und implementiert wird.Cloud Computing is a relatively newly emerged high performance parallel computing paradigm. A lot of algorithms from the past could now find new opportunities and benefit from it. After several month of study on theory and implementation of On-Line Analytical Processing (OLAP), especially, the OLAP engine from the GridMiner project (http://www.gridminer.org), we decided to design and implement an OLAP system for Cloud Computing environment. For this cloud-enabled OLAP system we have also provided means for management and interaction with it, which are implemented by a multi-tier client subsystem including some business logic and Graphical User Interfaces (GUI) in an easy to use and understandable way. In this thesis the original design and implementation of the multi-tier client subsystem is described and discussed. Management of and interaction with the OLAP cloud means on one hand loading data from data source, transforming and transferring it to the OLAP cloud to construct data cube, On the other hand, submitting OLAP analysis queries and handling the results. Practically, the implemented client subsystem was developed mainly using Google Web Toolkit (GWT) as a web-based multi-tier application. It is able to load data either from a single Relational Database Management System (RMDBS) via Java Database Connectivity (JDBC), or from Open Grid Services Architecture - Data Access and Integration (OGSA-DAI) server, which integrates data from heterogeneous data sources. Operations such as loading data to OLAP cloud and OLAP query are achieved by interacting with the Representational State Transfer (REST) APIs provided by the OLAP cloud. Data is represented in WebRowSet format, operations are described in OLAP Modeling Markup Language (OMML) version 2.0, which is proposed, described and implemented in this thesis

Sensor web geoprocessing on the grid

Recent standardisation initiatives in the fields of grid computing and geospatial sensor middleware provide an exciting opportunity for the composition of large scale geospatial monitoring and prediction systems from existing components. Sensor middleware standards are paving the way for the emerging sensor web which is envisioned to make millions of geospatial sensors and their data publicly accessible by providing discovery, task and query functionality over the internet. In a similar fashion, concurrent development is taking place in the field of grid computing whereby the virtualisation of computational and data storage resources using middleware abstraction provides a framework to share computing resources. Sensor web and grid computing share a common vision of world-wide connectivity and in their current form they are both realised using web services as the underlying technological framework. The integration of sensor web and grid computing middleware using open standards is expected to facilitate interoperability and scalability in near real-time geoprocessing systems. The aim of this thesis is to develop an appropriate conceptual and practical framework in which open standards in grid computing, sensor web and geospatial web services can be combined as a technological basis for the monitoring and prediction of geospatial phenomena in the earth systems domain, to facilitate real-time decision support. The primary topic of interest is how real-time sensor data can be processed on a grid computing architecture. This is addressed by creating a simple typology of real-time geoprocessing operations with respect to grid computing architectures. A geoprocessing system exemplar of each geoprocessing operation in the typology is implemented using contemporary tools and techniques which provides a basis from which to validate the standards frameworks and highlight issues of scalability and interoperability. It was found that it is possible to combine standardised web services from each of these aforementioned domains despite issues of interoperability resulting from differences in web service style and security between specifications. A novel integration method for the continuous processing of a sensor observation stream is suggested in which a perpetual processing job is submitted as a single continuous compute job. Although this method was found to be successful two key challenges remain; a mechanism for consistently scheduling real-time jobs within an acceptable time-frame must be devised and the tradeoff between efficient grid resource utilisation and processing latency must be balanced. The lack of actual implementations of distributed geoprocessing systems built using sensor web and grid computing has hindered the development of standards, tools and frameworks in this area. This work provides a contribution to the small number of existing implementations in this field by identifying potential workflow bottlenecks in such systems and gaps in the existing specifications. Furthermore it sets out a typology of real-time geoprocessing operations that are anticipated to facilitate the development of real-time geoprocessing software.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (EPSRC) : School of Civil Engineering & Geosciences, Newcastle UniversityGBUnited Kingdo

The Object of Platform Studies: Relational Materialities and the Social Platform (the case of the Nintendo Wii)

Racing the Beam: The Atari Video Computer System,by Ian Bogost and Nick Montfort, inaugurated thePlatform Studies series at MIT Press in 2009.We’ve coauthored a new book in the series, Codename: Revolution: the Nintendo Wii Video Game Console. Platform studies is a quintessentially Digital Humanities approach, since it’s explicitly focused on the interrelationship of computing and cultural expression. According to the series preface, the goal of platform studies is “to consider the lowest level of computing systems and to understand how these systems relate to culture and creativity.”In practice, this involves paying close attentionto specific hardware and software interactions--to the vertical relationships between a platform’s multilayered materialities (Hayles; Kirschenbaum),from transistors to code to cultural reception. Any given act of platform-studies analysis may focus for example on the relationship between the chipset and the OS, or between the graphics processor and display parameters or game developers’ designs.In computing terms, platform is an abstraction(Bogost and Montfort), a pragmatic frame placed around whatever hardware-and-software configuration is required in order to build or run certain specificapplications (including creative works). The object of platform studies is thus a shifting series of possibility spaces, any number of dynamic thresholds between discrete levels of a system