77,136 research outputs found

    Towards a pivotal-based approach for business process alignment.

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    This article focuses on business process engineering, especially on alignment between business analysis and implementation. Through a business process management approach, different transformations interfere with process models in order to make them executable. To keep the consistency of process model from business model to IT model, we propose a pivotal metamodel-centric methodology. It aims at keeping or giving all requisite structural and semantic data needed to perform such transformations without loss of information. Through this we can ensure the alignment between business and IT. This article describes the concept of pivotal metamodel and proposes a methodology using such an approach. In addition, we present an example and the resulting benefits

    Using formal metamodels to check consistency of functional views in information systems specification

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    UML notations require adaptation for applications such as Information Systems (IS). Thus we have defined IS-UML. The purpose of this article is twofold. First, we propose an extension to this language to deal with functional aspects of IS. We use two views to specify IS transactions: the first one is defined as a combination of behavioural UML diagrams (collaboration and state diagrams), and the second one is based on the definition of specific classes of an extended class diagram. The final objective of the article is to consider consistency issues between the various diagrams of an IS-UML specification. In common with other UML languages, we use a metamodel to define IS-UML. We use class diagrams to summarize the metamodel structure and a formal language, B, for the full metamodel. This allows us to formally express consistency checks and mapping rules between specific metamodel concepts. (C) 2007 Elsevier B.V. All rights reserved

    Extending Eventually Consistent Cloud Databases for Enforcing Numeric Invariants

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    Geo-replicated databases often operate under the principle of eventual consistency to offer high-availability with low latency on a simple key/value store abstraction. Recently, some have adopted commutative data types to provide seamless reconciliation for special purpose data types, such as counters. Despite this, the inability to enforce numeric invariants across all replicas still remains a key shortcoming of relying on the limited guarantees of eventual consistency storage. We present a new replicated data type, called bounded counter, which adds support for numeric invariants to eventually consistent geo-replicated databases. We describe how this can be implemented on top of existing cloud stores without modifying them, using Riak as an example. Our approach adapts ideas from escrow transactions to devise a solution that is decentralized, fault-tolerant and fast. Our evaluation shows much lower latency and better scalability than the traditional approach of using strong consistency to enforce numeric invariants, thus alleviating the tension between consistency and availability

    Specification of multiparty audio and video interaction based on the Reference Model of Open Distributed Processing

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    The Reference Model of Open Distributed Processing (RM-ODP) is an emerging ISO/ITU-T standard. It provides a framework of abstractions based on viewpoints, and it defines five viewpoint languages to model open distributed systems. This paper uses the viewpoint languages to specify multiparty audio/video exchange in distributed systems. To the designers of distributed systems, it shows how the concepts and rules of RM-ODP can be applied.\ud \ud The ODP Āæbinding objectĀæ is an important concept to model continuous data flows in distributed systems. We take this concept as a basis for multiparty audio and video flow exchanges, and we provide five ODP viewpoint specifications, each emphasising a particular concern. To ensure overall correctness, special attention is paid to the mapping between the ODP viewpoint specifications

    Database Vs Data Warehouse

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    Data warehouse technology includes a set of concepts and methods that offer the users useful information for decision making. The necessity to build a data warehouse arises from the necessity to improve the quality of information in the organization. The date proceeding from different sources, having a variety of forms - both structured and unstructured, are filtered according to business rules and are integrated in a single large data collection. Using informatics solutions, managers have understood that data stored in operational systems - including databases, are an informational gold mine that must be exploited. Data warehouses have been developed to answer the increasing demands for complex analysis, which could not be properly achieved with operational databases. The present paper emphasizes some of the criteria that information application developers can use in order to choose between a database solution or a data warehouse one.data warehouse, database, database management systems, information systems, data organisation in externe memory, business intelligence

    DualTable: A Hybrid Storage Model for Update Optimization in Hive

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    Hive is the most mature and prevalent data warehouse tool providing SQL-like interface in the Hadoop ecosystem. It is successfully used in many Internet companies and shows its value for big data processing in traditional industries. However, enterprise big data processing systems as in Smart Grid applications usually require complicated business logics and involve many data manipulation operations like updates and deletes. Hive cannot offer sufficient support for these while preserving high query performance. Hive using the Hadoop Distributed File System (HDFS) for storage cannot implement data manipulation efficiently and Hive on HBase suffers from poor query performance even though it can support faster data manipulation.There is a project based on Hive issue Hive-5317 to support update operations, but it has not been finished in Hive's latest version. Since this ACID compliant extension adopts same data storage format on HDFS, the update performance problem is not solved. In this paper, we propose a hybrid storage model called DualTable, which combines the efficient streaming reads of HDFS and the random write capability of HBase. Hive on DualTable provides better data manipulation support and preserves query performance at the same time. Experiments on a TPC-H data set and on a real smart grid data set show that Hive on DualTable is up to 10 times faster than Hive when executing update and delete operations.Comment: accepted by industry session of ICDE201

    An approach to rollback recovery of collaborating mobile agents

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    Fault-tolerance is one of the main problems that must be resolved to improve the adoption of the agents' computing paradigm. In this paper, we analyse the execution model of agent platforms and the significance of the faults affecting their constituent components on the reliable execution of agent-based applications, in order to develop a pragmatic framework for agent systems fault-tolerance. The developed framework deploys a communication-pairs independent check pointing strategy to offer a low-cost, application-transparent model for reliable agent- based computing that covers all possible faults that might invalidate reliable agent execution, migration and communication and maintains the exactly-one execution property
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