974 research outputs found

    Optimizing performance of workflow executions under authorization control

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    “Business processes or workflows are often used to model enterprise or scientific applications. It has received considerable attention to automate workflow executions on computing resources. However, many workflow scenarios still involve human activities and consist of a mixture of human tasks and computing tasks. Human involvement introduces security and authorization concerns, requiring restrictions on who is allowed to perform which tasks at what time. Role- Based Access Control (RBAC) is a popular authorization mechanism. In RBAC, the authorization concepts such as roles and permissions are defined, and various authorization constraints are supported, including separation of duty, temporal constraints, etc. Under RBAC, users are assigned to certain roles, while the roles are associated with prescribed permissions. When we assess resource capacities, or evaluate the performance of workflow executions on supporting platforms, it is often assumed that when a task is allocated to a resource, the resource will accept the task and start the execution once a processor becomes available. However, when the authorization policies are taken into account,” this assumption may not be true and the situation becomes more complex. For example, when a task arrives, a valid and activated role has to be assigned to a task before the task can start execution. The deployed authorization constraints may delay the workflow execution due to the roles’ availability, or other restrictions on the role assignments, which will consequently have negative impact on application performance. When the authorization constraints are present to restrict the workflow executions, it entails new research issues that have not been studied yet in conventional workflow management. This thesis aims to investigate these new research issues. First, it is important to know whether a feasible authorization solution can be found to enable the executions of all tasks in a workflow, i.e., check the feasibility of the deployed authorization constraints. This thesis studies the issue of the feasibility checking and models the feasibility checking problem as a constraints satisfaction problem. Second, it is useful to know when the performance of workflow executions will not be affected by the given authorization constraints. This thesis proposes the methods to determine the time durations when the given authorization constraints do not have impact. Third, when the authorization constraints do have the performance impact, how can we quantitatively analyse and determine the impact? When there are multiple choices to assign the roles to the tasks, will different choices lead to the different performance impact? If so, can we find an optimal way to conduct the task-role assignments so that the performance impact is minimized? This thesis proposes the method to analyze the delay caused by the authorization constraints if the workflow arrives beyond the non-impact time duration calculated above. Through the analysis of the delay, we realize that the authorization method, i.e., the method to select the roles to assign to the tasks affects the length of the delay caused by the authorization constraints. Based on this finding, we propose an optimal authorization method, called the Global Authorization Aware (GAA) method. Fourth, a key reason why authorization constraints may have impact on performance is because the authorization control directs the tasks to some particular roles. Then how to determine the level of workload directed to each role given a set of authorization constraints? This thesis conducts the theoretical analysis about how the authorization constraints direct the workload to the roles, and proposes the methods to calculate the arriving rate of the requests directed to each role under the role, temporal and cardinality constraints. Finally, the amount of resources allocated to support each individual role may have impact on the execution performance of the workflows. Therefore, it is desired to develop the strategies to determine the adequate amount of resources when the authorization control is present in the system. This thesis presents the methods to allocate the appropriate quantity for resources, including both human resources and computing resources. Different features of human resources and computing resources are taken into account. For human resources, the objective is to maximize the performance subject to the budgets to hire the human resources, while for computing resources, the strategy aims to allocate adequate amount of computing resources to meet the QoS requirements

    InfraPhenoGrid: A scientific workflow infrastructure for Plant Phenomics on the Grid

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    International audiencePlant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges , in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time (as it is the case when phenomic traits are measured manually), such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data. In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middle-ware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained (using provenance information) is kept as simple as possible for end-users

    Design of a Workflow-Based Grid Framework

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    This paper aims to present the design of the Grid Collaborative Framework which has been proposed in one of our previous work. Grid infrastructure for resources sharing is somewhat stable with the wide acceptance of the Open Grid Services Architecture (OGSA) and Web Services Resource Framework (WSRF), but Grid framework for collaboration is far from desired. Current Grid Collaborative Frameworks (GCFs) are domain specific and lack of plan-supported capability. These limitations make them less useful and narrow in scope of application. Our grid collaborative framework aims to improve these limitations. With the theoretical foundation based on the activity theory, workflow languages, and designed on top of existing OGSA infrastructure, our proposed framework aims at accelerating the development of grid collaborative systems that consider work plans as central role

    Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

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    The Helmholtz Association funded the "Large-Scale Data Management and Analysis" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities

    Challenges Emerging from Future Cloud Application Scenarios

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    The cloud computing paradigm encompasses several key differentiating elements and technologies, tackling a number of inefficiencies, limitations and problems that have been identified in the distributed and virtualized computing domain. Nonetheless, and as it is the case for all emerging technologies, their adoption led to the presentation of new challenges and new complexities. In this paper we present key application areas and capabilities of future scenarios, which are not tackled by current advancements and highlight specific requirements and goals for advancements in the cloud computing domain. We discuss these requirements and goals across different focus areas of cloud computing, ranging from cloud service and application integration, development environments and abstractions, to interoperability and relevant to it aspects such as legislation. The future application areas and their requirements are also mapped to the aforementioned areas in order to highlight their dependencies and potential for moving cloud technologies forward and contributing towards their wider adoption

    Comparison of composition engines and identification of shortcomings with respect to cloud computing

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    Most workflow engines are currently not Cloud-aware. This is due to multiple reasons like no support for transparent scalability, no multi-tenancy support, no ability to store process related data in a Cloud storage, or no support for quality of service enforcements. Recently Cloud based workflow services appeared in the workflow landscape and promise to run workflows in the Cloud. This student reports evaluates current state of the art BPEL and BPMN workflow engines and Cloud based workflow services according to their Cloud- awareness and general workflow functionalities. Identified shortcomings are described and prioritized. As a result of this evaluation the workflow engine WSO2 Stratos is best suited for running workflows in the Cloud, but it lacks native clustering support and quality of service enforcement

    Consortium Proposal NFDI-MatWerk

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    This is the official proposal the NFDI-consortium NFDI-MatWerk submitted to the DFG within the request for funding the project. Visit www.dfg.de/nfdi for more infos on the German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur - NFDI) initiative. Visit www.nfdi-matwerk.de for last infos about the project NFDI-MatWerk

    Obstructions in Security-Aware Business Processes

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    This Open Access book explores the dilemma-like stalemate between security and regulatory compliance in business processes on the one hand and business continuity and governance on the other. The growing number of regulations, e.g., on information security, data protection, or privacy, implemented in increasingly digitized businesses can have an obstructive effect on the automated execution of business processes. Such security-related obstructions can particularly occur when an access control-based implementation of regulations blocks the execution of business processes. By handling obstructions, security in business processes is supposed to be improved. For this, the book presents a framework that allows the comprehensive analysis, detection, and handling of obstructions in a security-sensitive way. Thereby, methods based on common organizational security policies, process models, and logs are proposed. The Petri net-based modeling and related semantic and language-based research, as well as the analysis of event data and machine learning methods finally lead to the development of algorithms and experiments that can detect and resolve obstructions and are reproducible with the provided software
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