Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Ayav, TolgaWoS Q: search.filters.wosQuartile.Q1

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  • Article
    Citation - WoS: 26
    Citation - Scopus: 30
    Ensuring Performance and Provider Profit Through Data Replication in Cloud Systems
    (Springer Verlag, 2017) Tos, Uras; Mokadem, Riad; Hameurlain, Abdelkader; Ayav, Tolga; Bora, Şebnem
    Cloud computing is a relatively recent computing paradigm that is often the answer for dealing with large amounts of data. Tenants expect the cloud providers to keep supplying an agreed upon quality of service, while cloud providers aim to increase profits as it is a key ingredient of any economic enterprise. In this paper, we propose a data replication strategy for cloud systems that satisfies the response time objective for executing queries while simultaneously enables the provider to return a profit from each execution. The proposed strategy estimates the response time of the queries and performs data replication in a way that the execution of any particular query is still estimated to be profitable for the provider. We show with simulations that how the proposed strategy fulfills these two criteria.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 9
    Identifying Critical Architectural Components With Spectral Analysis of Fault Trees
    (Elsevier Ltd., 2016) Ayav, Tolga; Sözer, Hasan
    We increasingly rely on software-intensive embedded systems. Increasing size and complexity of these hardware/software systems makes it necessary to evaluate reliability at the system architecture level. One aspect of this evaluation is sensitivity analysis, which aims at identifying critical components of the architecture. These are the components of which unreliability contributes the most to the unreliability of the system. In this paper, we propose a novel approach for sensitivity analysis based on spectral analysis of fault trees. We show that measures obtained with our approach are both consistent and complementary with respect to the recognized metrics in the literature.