Real-Time Kinematic (RTK) positioning is a technique used to provide precise positioning services at centimetre accuracy level in the context of Global Navigation Satellite Systems (GNSS). While a Network-based RTK (N-RTK) system involves multiple continuously operating reference stations (CORS), the simplest form of a NRTK system is a single-base RTK. In Australia there are several NRTK services operating in different states and over 1000 single-base RTK systems to support precise positioning applications for surveying, mining, agriculture, and civil construction in regional areas. Additionally, future generation GNSS constellations, including modernised GPS, Galileo, GLONASS, and Compass, with multiple frequencies have been either developed or will become fully operational in the next decade. A trend of future development of RTK systems is to make use of various isolated operating network and single-base RTK systems and multiple GNSS constellations for extended service coverage and improved performance. Several computational challenges have been identified for future NRTK services including: • Multiple GNSS constellations and multiple frequencies • Large scale, wide area NRTK services with a network of networks • Complex computation algorithms and processes • Greater part of positioning processes shifting from user end to network centre with the ability to cope with hundreds of simultaneous users’ requests (reverse RTK) There are two major requirements for NRTK data processing based on the four challenges faced by future NRTK systems, expandable computing power and scalable data sharing/transferring capability. This research explores new approaches to address these future NRTK challenges and requirements using the Grid Computing facility, in particular for large data processing burdens and complex computation algorithms. A Grid Computing based NRTK framework is proposed in this research, which is a layered framework consisting of: 1) Client layer with the form of Grid portal; 2) Service layer; 3) Execution layer. The user’s request is passed through these layers, and scheduled to different Grid nodes in the network infrastructure. A proof-of-concept demonstration for the proposed framework is performed in a five-node Grid environment at QUT and also Grid Australia. The Networked Transport of RTCM via Internet Protocol (Ntrip) open source software is adopted to download real-time RTCM data from multiple reference stations through the Internet, followed by job scheduling and simplified RTK computing. The system performance has been analysed and the results have preliminarily demonstrated the concepts and functionality of the new NRTK framework based on Grid Computing, whilst some aspects of the performance of the system are yet to be improved in future work.

Zugl.: Potsdam, Universiẗat, Diss., 2008.

Universiẗat, Diss., 2009--Bayreuth.

The avalanche of data from scientific instruments and the ensuing interest from geographically distributed users to analyze and interpret it accentuates the need for efficient data dissemination. An optimal data distribution scheme will find the delicate balance between conflicting requirements of minimizing transfer times, minimizing the impact on the network, and uniformly distributing load among participants. We identify several data distribution techniques, some successfully employed by today's peer-to-peer networks: staging, data partitioning, orthogonal bandwidth exploitation, and combinations of the above. We use simulations to explore the performance of these techniques in contexts similar to those used by today's data-centric scientific collaborations and derive several recommendations for efficient data dissemination. Our experimental results show that the peer-to-peer solutions that offer load balancing and good fault tolerance properties and have embedded participation incentives lead to unjustified costs in today's scientific data collaborations deployed on over-provisioned network cores. However, as user communities grow and these deployments scale, peer-to-peer data delivery mechanisms will likely outperform other techniques. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

No description available.

The use of the distributed file system, AFS, as a solution to the “input/output sandbox” problem in grid computing is studied. A computational grid middleware, primarily to accommodate the environment of the BaBar Computing Model, has been designed, written and is presented. A summary of the existing grid middleware and resources is discussed. A number of benchmarks (one written for this thesis) are used to test the performance of the AFS over the wide area network and grid environment. The performance of the AFS is also tested using a straightforward BaBar Analysis code on real data. Secure web-based and command-line interfaces created to monitor job submission and grid fabric are presented.

Epigenetics is the study of factors that can change DNA and passed to next generation without change to DNA sequence. DNA methylation is one of the categories of epigenetic change. DNA methylation is the attachment of methyl group (CH3) to DNA. Most of the time it occurs in the sequences that G is followed by C known as CpG sites and by addition of methyl to the cytosine residue. As science and technology progress new data are available about individual’s DNA methylation profile in different conditions. Also new features discovered that can have role in DNA methylation. The availability of new data on DNA methylation and other features of DNA provide challenge to bioinformatics and the opportunity to discover new knowledge from existing data. In this research multiple data series were used to identify classes of methylation DNA to CpG sites. These classes are a) Never methylated CpG sites,b) Always methylated CpG sites, c) Methylated CpG sites in cancer/disease samples and non-methylated in normal samples d) Methylated CpG sites in normal samples and non-methylated in cancer/disease samples. After identification of these sites and their classes, an analysis was carried out to find the features which can better classify these sites a matrix of features was generated using four applications in EMBOSS software suite. Features matrix was also generated using the gUse/WS-PGRADE portal workflow system. In order to do this each of the four applications were grid enabled and ported to BOINC platform. The gUse portal was connected to the BOINC project via 3G-bridge. Each node in the workflow created portion of matrix and then these portions were combined together to create final matrix. This final feature matrix used in a hill climbing workflow. Hill climbing node was a JAVA program ported to BOINC platform. A Hill climbing search workflow was used to search for a subset of features that are better at classifying the CpG sites using 5 different measurements and three different classification methods: support vector machine, naïve bayes and J48 decision tree. Using this approach the hill climbing search found the models which contain less than half the number of features and better classification results. It is also been demonstrated that using gUse/WS-PGRADE workflow system can provide a modular way of feature generation so adding new feature generator application can be done without changing other parts. It is also shown that using grid enabled applications can speedup both feature generation and feature subset selection. The approach used in this research for distributed workflow based feature generation is not restricted to this study and can be applied in other studies that involve feature generation. The approach also needs multiple binaries to generate portions of features. The grid enabled hill climbing search application can also be used in different context as it only requires to follow the same format of feature matrix.

Diplomarbeit im Schnittgebiet von Cluster- und Grid-Computing. Einbindung verteilter Ressourcen in eine Infrastruktur. Realisierung einer einfachen Checkpointing-Umgebung.

No description available.

An increased need for collaborative research among different organizations, together with continuing advances in communication technology and computer hardware, has facilitated the development of distributed systems that can provide users non-trivial access to geographically dispersed computing resources (processors, storage, applications, data, instruments, etc.) that are administered in multiple computer domains. The term grid computing or grids is popularly used to refer to such distributed systems. A broader definition of grid computing includes the use of computing resources within an organization for running organization-specific applications. This research is in the context of using grid computing within an enterprise to maximize the use of available hardware and software resources for processing enterprise applications. Large scale scientific simulations have traditionally been the primary benefactor of grid computing. The application of this technology to simulation in industry has, however, been negligible. This research investigates how grid technology can be effectively exploited by simulation practitioners using Windows-based commercially available simulation packages to model simulations in industry. These packages are commonly referred to as Commercial Off-The-Shelf (COTS) Simulation Packages (CSPs). The study identifies several higher level grid services that could be potentially used to support the practise of simulation in industry. It proposes a grid computing framework to investigate these services in the context of CSP-based simulations. This framework is called the CSP-Grid Computing (CSP-GC) Framework. Each identified higher level grid service in this framework is referred to as a CSP-specific service. A total of six case studies are presented to experimentally evaluate how grid computing technologies can be used together with unmodified simulation packages to support some of the CSP-specific services. The contribution of this thesis is the CSP-GC framework that identifies how simulation practise in industry may benefit from the use of grid technology. A further contribution is the recognition of specific grid computing software (grid middleware) that can possibly be used together with existing CSPs to provide grid support. With its focus on end-users and end-user tools, it is intended that this research will encourage wider adoption of grid computing in the workplace and that simulation users will derive benefit from using this technology.