Self-adaptive Grid Resource Monitoring and discovery

The Grid provides a novel platform where the scientific and engineering communities can share data and computation across multiple administrative domains. There are several key services that must be offered by Grid middleware; one of them being the Grid Information Service( GIS). A GIS is a Grid middleware component which maintains information about hardware, software, services and people participating in a virtual organisation( VO). There is an inherent need in these systems for the delivery of reliable performance. This thesis describes a number of approaches which detail the development and application of a suite of benchmarks for the prediction of the process of resource discovery and monitoring on the Grid. A series of experimental studies of the characterisation of performance using benchmarking, are carried out. Several novel predictive algorithms are presented and evaluated in terms of their predictive error. Furthermore, predictive methods are developed which describe the behaviour of MDS2 for a variable number of user requests. The MDS is also extended to include job information from a local scheduler; this information is queried using requests of greatly varying complexity. The response of the MDS to these queries is then assessed in terms of several performance metrics. The benchmarking of the dynamic nature of information within MDS3 which is based on the Open Grid Services Architecture (OGSA), and also the successor to MDS2, is also carried out. The performance of both the pull and push query mechanisms is analysed. GridAdapt (Self-adaptive Grid Resource Monitoring) is a new system that is proposed, built upon the Globus MDS3 benchmarking. It offers self-adaptation, autonomy and admission control at the Index Service, whilst ensuring that the MIDS is not overloaded and can meet its quality-of-service,f or example,i n terms of its average response time for servicing synchronous queries and the total number of queries returned per unit time

Grid service discovery with rough sets

Copyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.The computational grid is evolving as a service-oriented computing infrastructure that facilitates resource sharing and large-scale problem solving over the Internet. Service discovery becomes an issue of vital importance in utilising grid facilities. This paper presents ROSSE, a Rough sets based search engine for grid service discovery. Building on Rough sets theory, ROSSE is novel in its capability to deal with uncertainty of properties when matching services. In this way, ROSSE can discover the services that are most relevant to a service query from a functional point of view. Since functionally matched services may have distinct non-functional properties related to Quality of Service (QoS), ROSSE introduces a QoS model to further filter matched services with their QoS values to maximise user satisfaction in service discovery. ROSSE is evaluated in terms of its accuracy and efficiency in discovery of computing services

Probabilistic grid scheduling based on job statistics and monitoring information

This transfer thesis presents a novel, probabilistic approach to scheduling applications on computational Grids based on their historical behaviour, current state of the Grid and predictions of the future execution times and resource utilisation of such applications. The work lays a foundation for enabling a more intuitive, user-friendly and effective scheduling technique termed deadline scheduling. Initial work has established motivation and requirements for a more efficient Grid scheduler, able to adaptively handle dynamic nature of the Grid resources and submitted workload. Preliminary scheduler research identified the need for a detailed monitoring of Grid resources on the process level, and for a tool to simulate non-deterministic behaviour and statistical properties of Grid applications. A simulation tool, GridLoader, has been developed to enable modelling of application loads similar to a number of typical Grid applications. GridLoader is able to simulate CPU utilisation, memory allocation and network transfers according to limits set through command line parameters or a configuration file. Its specific strength is in achieving set resource utilisation targets in a probabilistic manner, thus creating a dynamic environment, suitable for testing the scheduler’s adaptability and its prediction algorithm. To enable highly granular monitoring of Grid applications, a monitoring framework based on the Ganglia Toolkit was developed and tested. The suite is able to collect resource usage information of individual Grid applications, integrate it into standard XML based information flow, provide visualisation through a Web portal, and export data into a format suitable for off-line analysis. The thesis also presents initial investigation of the utilisation of University College London Central Computing Cluster facility running Sun Grid Engine middleware. Feasibility of basic prediction concepts based on the historical information and process meta-data have been successfully established and possible scheduling improvements using such predictions identified. The thesis is structured as follows: Section 1 introduces Grid computing and its major concepts; Section 2 presents open research issues and specific focus of the author’s research; Section 3 gives a survey of the related literature, schedulers, monitoring tools and simulation packages; Section 4 presents the platform for author’s work – the Self-Organising Grid Resource management project; Sections 5 and 6 give detailed accounts of the monitoring framework and simulation tool developed; Section 7 presents the initial data analysis while Section 8.4 concludes the thesis with appendices and references

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

Self-adaptive Grid Resource Monitoring and discovery

The Grid provides a novel platform where the scientific and engineering communities can share data and computation across multiple administrative domains. There are several key services that must be offered by Grid middleware; one of them being the Grid Information Service( GIS). A GIS is a Grid middleware component which maintains information about hardware, software, services and people participating in a virtual organisation( VO). There is an inherent need in these systems for the delivery of reliable performance. This thesis describes a number of approaches which detail the development and application of a suite of benchmarks for the prediction of the process of resource discovery and monitoring on the Grid. A series of experimental studies of the characterisation of performance using benchmarking, are carried out. Several novel predictive algorithms are presented and evaluated in terms of their predictive error. Furthermore, predictive methods are developed which describe the behaviour of MDS2 for a variable number of user requests. The MDS is also extended to include job information from a local scheduler; this information is queried using requests of greatly varying complexity. The response of the MDS to these queries is then assessed in terms of several performance metrics. The benchmarking of the dynamic nature of information within MDS3 which is based on the Open Grid Services Architecture (OGSA), and also the successor to MDS2, is also carried out. The performance of both the pull and push query mechanisms is analysed. GridAdapt (Self-adaptive Grid Resource Monitoring) is a new system that is proposed, built upon the Globus MDS3 benchmarking. It offers self-adaptation, autonomy and admission control at the Index Service, whilst ensuring that the MIDS is not overloaded and can meet its quality-of-service,f or example,i n terms of its average response time for servicing synchronous queries and the total number of queries returned per unit time.EThOS - Electronic Theses Online ServiceUniversity of Warwick (UoW)GBUnited Kingdo

Designing a Resource Broker for Heterogeneous Grids

Grids provide uniform access to aggregations of heterogeneous resources and services such as computers, networks and storage owned by multiple organizations. However, such a dynamic environment poses many challenges for application composition and deployment. In this paper, we present the design of the Gridbus Grid resource broker that allows users to create applications and specify different objectives through different interfaces without having to deal with the complexity of Grid infrastructure. We present the unique requirements that motivated our design and discuss how these provide flexibility in extending the functionality of the broker to support different low-level middlewares and user interfaces. We evaluate the broker with different job profiles and Grid middleware and conclude with the lessons learnt from our development experience.Comment: 26 pages, 15 figure

Dimensionerings- en werkverdelingsalgoritmen voor lambda grids

Grids bestaan uit een verzameling reken- en opslagelementen die geografisch verspreid kunnen zijn, maar waarvan men de gezamenlijke capaciteit wenst te benutten. Daartoe dienen deze elementen verbonden te worden met een netwerk. Vermits veel wetenschappelijke applicaties gebruik maken van een Grid, en deze applicaties doorgaans grote hoeveelheden data verwerken, is het noodzakelijk om een netwerk te voorzien dat dergelijke grote datastromen op betrouwbare wijze kan transporteren. Optische transportnetwerken lenen zich hier uitstekend toe. Grids die gebruik maken van dergelijk netwerk noemt men lambda Grids. Deze thesis beschrijft een kader waarin het ontwerp en dimensionering van optische netwerken voor lambda Grids kunnen beschreven worden. Ook wordt besproken hoe werklast kan verdeeld worden op een Grid eens die gedimensioneerd is. Een groot deel van de resultaten werd bekomen door simulatie, waarbij gebruik gemaakt wordt van een eigen Grid simulatiepakket dat precies focust op netwerk- en Gridelementen. Het ontwerp van deze simulator, en de daarbijhorende implementatiekeuzes worden dan ook uitvoerig toegelicht in dit werk