The Experts below are selected from a list of 11325 Experts worldwide ranked by ideXlab platform

José Pereira - One of the best experts on this subject based on the ideXlab platform.

  • DAIS - Distributed Exact Deduplication for Primary Storage Infrastructures
    Distributed Applications and Interoperable Systems, 2014
    Co-Authors: João Paulo, José Pereira
    Abstract:

    Deduplication of primary storage volumes in a cloud computing environment is increasingly desirable, as the resulting space savings contribute to the cost effectiveness of a large scale multi-tenant infrastructure. However, traditional archival and backup deduplication Systems impose prohibitive overhead for latency-sensitive applications deployed at these infrastructures while, current primary deduplication Systems rely on special cluster fileSystems, centralized components, or restrictive workload assumptions. We present DEDIS, a fully-distributed and Dependable System that performs exact and cluster-wide background deduplication of primary storage. DEDIS does not depend on data locality and works on top of any unsophisticated storage backend, centralized or distributed, that exports a basic shared block device interface. The evaluation of an open-source prototype shows that DEDIS scales out and adds negligible overhead even when deduplication and intensive storage I/O run simultaneously.

  • Distributed Exact Deduplication for Primary Storage Infrastructures
    2014
    Co-Authors: João Paulo, José Pereira
    Abstract:

    Deduplication of primary storage volumes in a cloud computing environment is increasingly desirable, as the resulting space savings contribute to the cost effectiveness of a large scale multi-tenant infrastructure. However, traditional archival and backup deduplication Systems impose prohibitive overhead for latency-sensitive applications deployed at these infrastructures while, current primary deduplication Systems rely on special cluster fileSystems, centralized components, or restrictive workload assumptions.We present DEDIS, a fully-distributed and Dependable System that performs exact and cluster-wide background deduplication of primary storage. DEDIS does not depend on data locality and works on top of any unsophisticated storage backend, centralized or distributed, that exports a basic shared block device interface. The evaluation of an open-source prototype shows that DEDIS scales out and adds negligible overhead even when deduplication and intensive storage I/O run simultaneously.

João Paulo - One of the best experts on this subject based on the ideXlab platform.

  • DAIS - Distributed Exact Deduplication for Primary Storage Infrastructures
    Distributed Applications and Interoperable Systems, 2014
    Co-Authors: João Paulo, José Pereira
    Abstract:

    Deduplication of primary storage volumes in a cloud computing environment is increasingly desirable, as the resulting space savings contribute to the cost effectiveness of a large scale multi-tenant infrastructure. However, traditional archival and backup deduplication Systems impose prohibitive overhead for latency-sensitive applications deployed at these infrastructures while, current primary deduplication Systems rely on special cluster fileSystems, centralized components, or restrictive workload assumptions. We present DEDIS, a fully-distributed and Dependable System that performs exact and cluster-wide background deduplication of primary storage. DEDIS does not depend on data locality and works on top of any unsophisticated storage backend, centralized or distributed, that exports a basic shared block device interface. The evaluation of an open-source prototype shows that DEDIS scales out and adds negligible overhead even when deduplication and intensive storage I/O run simultaneously.

  • Distributed Exact Deduplication for Primary Storage Infrastructures
    2014
    Co-Authors: João Paulo, José Pereira
    Abstract:

    Deduplication of primary storage volumes in a cloud computing environment is increasingly desirable, as the resulting space savings contribute to the cost effectiveness of a large scale multi-tenant infrastructure. However, traditional archival and backup deduplication Systems impose prohibitive overhead for latency-sensitive applications deployed at these infrastructures while, current primary deduplication Systems rely on special cluster fileSystems, centralized components, or restrictive workload assumptions.We present DEDIS, a fully-distributed and Dependable System that performs exact and cluster-wide background deduplication of primary storage. DEDIS does not depend on data locality and works on top of any unsophisticated storage backend, centralized or distributed, that exports a basic shared block device interface. The evaluation of an open-source prototype shows that DEDIS scales out and adds negligible overhead even when deduplication and intensive storage I/O run simultaneously.

Liliana Cucu-grosjean - One of the best experts on this subject based on the ideXlab platform.

  • A statistical response-time analysis of real-time embedded Systems
    Proceedings - Real-Time Systems Symposium, 2012
    Co-Authors: Yue Lu, Iain Bate, Thomas Nolte, Liliana Cucu-grosjean
    Abstract:

    Real-time embedded Systems are becoming ever more complex. We are reaching the stage where even if static Response-Time Analysis (RTA) was feasible from a cost and technical perspective, the results of such an analysis are overly pessimistic. This makes them less useful to the practitioner. In addition, the temporal validation and verification of such Systems in some applications, e.g., aeronautics, requires the probability of obtaining a worst-case response time larger than a given value in order to support Dependable System functions. All these facts advocate moving toward statistical RTA, which instead of calculating absolute worst-case timing guarantees, computes a probabilistic worst-case response time estimate. The contribution of this paper is to present and evaluate such a statistical RTA technique which uses a black box view of the Systems under analysis, by not requiring estimates of parameters such as worst-case execution times of tasks. Furthermore, our analysis is applicable to real Systems that are complex, e.g., from a task dependencies perspective.

Branimir Boguraev - One of the best experts on this subject based on the ideXlab platform.

  • DSN - A linguistic analysis engine for natural language use case description and its application to dependability analysis in industrial use cases
    2009 IEEE IFIP International Conference on Dependable Systems & Networks, 2009
    Co-Authors: Avik Sinha, Amit Paradkar, Palani Kumanan, Branimir Boguraev
    Abstract:

    We present 1) a novel linguistic engine made of configurable linguistic components for understanding natural language use case specification; and 2) results of the first of a kind large scale experiment of application of linguistic techniques to industrial use cases. Requirement defects are well known to have adverse effects on dependability of software Systems. While formal techniques are often cited as a remedy for specification errors, natural language remains the predominant mode for specifying requirements. Therefore, for Dependable System development, a natural language processing technique is required that can translate natural language textual requirements into validation ready computer models. In this paper, we present the implementation details of such a technique and the results of applying a prototype implementation of our technique to 80 industrial and academic use case descriptions. We report on the accuracy and effectiveness of our technique. The results of our experiment are very encouraging.

  • a linguistic analysis engine for natural language use case description and its application to dependability analysis in industrial use cases
    Dependable Systems and Networks, 2009
    Co-Authors: Avik Sinha, Amit Paradkar, Palani Kumanan, Branimir Boguraev
    Abstract:

    We present 1) a novel linguistic engine made of configurable linguistic components for understanding natural language use case specification; and 2) results of the first of a kind large scale experiment of application of linguistic techniques to industrial use cases. Requirement defects are well known to have adverse effects on dependability of software Systems. While formal techniques are often cited as a remedy for specification errors, natural language remains the predominant mode for specifying requirements. Therefore, for Dependable System development, a natural language processing technique is required that can translate natural language textual requirements into validation ready computer models. In this paper, we present the implementation details of such a technique and the results of applying a prototype implementation of our technique to 80 industrial and academic use case descriptions. We report on the accuracy and effectiveness of our technique. The results of our experiment are very encouraging.

Yue Lu - One of the best experts on this subject based on the ideXlab platform.

  • A statistical response-time analysis of real-time embedded Systems
    Proceedings - Real-Time Systems Symposium, 2012
    Co-Authors: Yue Lu, Iain Bate, Thomas Nolte, Liliana Cucu-grosjean
    Abstract:

    Real-time embedded Systems are becoming ever more complex. We are reaching the stage where even if static Response-Time Analysis (RTA) was feasible from a cost and technical perspective, the results of such an analysis are overly pessimistic. This makes them less useful to the practitioner. In addition, the temporal validation and verification of such Systems in some applications, e.g., aeronautics, requires the probability of obtaining a worst-case response time larger than a given value in order to support Dependable System functions. All these facts advocate moving toward statistical RTA, which instead of calculating absolute worst-case timing guarantees, computes a probabilistic worst-case response time estimate. The contribution of this paper is to present and evaluate such a statistical RTA technique which uses a black box view of the Systems under analysis, by not requiring estimates of parameters such as worst-case execution times of tasks. Furthermore, our analysis is applicable to real Systems that are complex, e.g., from a task dependencies perspective.