5,316 research outputs found

    DEMO: integrating MPC in big data workflows

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    Secure multi-party computation (MPC) allows multiple parties to perform a joint computation without disclosing their private inputs. Many real-world joint computation use cases, however, involve data analyses on very large data sets, and are implemented by software engineers who lack MPC knowledge. Moreover, the collaborating parties -- e.g., several companies -- often deploy different data analytics stacks internally. These restrictions hamper the real-world usability of MPC. To address these challenges, we combine existing MPC frameworks with data-parallel analytics frameworks by extending the Musketeer big data workflow manager [4]. Musketeer automatically generates code for both the sensitive parts of a workflow, which are executed in MPC, and the remainder of the computation, which runs on scalable, widely-deployed analytics systems. In a prototype use case, we compute the Herfindahl-Hirschman Index (HHI), an index of market concentration used in antitrust regulation, on an aggregate 156GB of taxi trip data over five transportation companies. Our implementation computes the HHI in about 20 minutes using a combination of Hadoop and VIFF [1], while even "mixed mode" MPC with VIFF alone would have taken many hours. Finally, we discuss future research questions that we seek to address using our approach

    A Taxonomy of Workflow Management Systems for Grid Computing

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    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

    ADEPT2 - Next Generation Process Management Technology

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    If current process management systems shall be applied to a broad spectrum of applications, they will have to be significantly improved with respect to their technological capabilities. In particular, in dynamic environments it must be possible to quickly implement and deploy new processes, to enable ad-hoc modifications of single process instances at runtime (e.g., to add, delete or shift process steps), and to support process schema evolution with instance migration, i.e., to propagate process schema changes to already running instances. These requirements must be met without affecting process consistency and by preserving the robustness of the process management system. In this paper we describe how these challenges have been addressed and solved in the ADEPT2 Process Management System. Our overall vision is to provide a next generation process management technology which can be used in a variety of application domains

    Possibilistic Information Flow Control for Workflow Management Systems

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    In workflows and business processes, there are often security requirements on both the data, i.e. confidentiality and integrity, and the process, e.g. separation of duty. Graphical notations exist for specifying both workflows and associated security requirements. We present an approach for formally verifying that a workflow satisfies such security requirements. For this purpose, we define the semantics of a workflow as a state-event system and formalise security properties in a trace-based way, i.e. on an abstract level without depending on details of enforcement mechanisms such as Role-Based Access Control (RBAC). This formal model then allows us to build upon well-known verification techniques for information flow control. We describe how a compositional verification methodology for possibilistic information flow can be adapted to verify that a specification of a distributed workflow management system satisfies security requirements on both data and processes.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

    Autonomic Cloud Computing: Open Challenges and Architectural Elements

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    As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

    TumorML: Concept and requirements of an in silico cancer modelling markup language

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    This paper describes the initial groundwork carried out as part of the European Commission funded Transatlantic Tumor Model Repositories project, to develop a new markup language for computational cancer modelling, TumorML. In this paper we describe the motivations for such a language, arguing that current state-of-the-art biomodelling languages are not suited to the cancer modelling domain. We go on to describe the work that needs to be done to develop TumorML, the conceptual design, and a description of what existing markup languages will be used to compose the language specification
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