Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 15Citation - Scopus: 18Achieving Query Performance in the Cloud Via a Cost-Effective Data Replication Strategy(Springer, 2021) Tos, Uras; Mokadem, Riad; Hameurlain, Abdelkader; Ayav, TolgaMeeting performance expectations of tenants without sacrificing economic benefit is a tough challenge for cloud providers. We propose a data replication strategy to simultaneously satisfy both the performance and provider profit. Response time of database queries is estimated with the consideration of parallel execution. If the estimated response time is not acceptable, bottlenecks are identified in the query plan. Data replication is realized to resolve the bottlenecks. Data placement is heuristically performed in a way to satisfy query response times at a minimal cost for the provider. We demonstrate the validity of our strategy in a performance evaluation study.Article Citation - WoS: 26Citation - Scopus: 30Ensuring Performance and Provider Profit Through Data Replication in Cloud Systems(Springer Verlag, 2017) Tos, Uras; Mokadem, Riad; Hameurlain, Abdelkader; Ayav, Tolga; Bora, ŞebnemCloud 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: 24Citation - Scopus: 31Dynamic Replication Strategies in Data Grid Systems: A Survey(Springer Verlag, 2015) Tos, Uras; Mokadem, Riad; Hameurlain, Abdelkader; Ayav, Tolga; Bora, ŞebnemIn data grid systems, data replication aims to increase availability, fault tolerance, load balancing and scalability while reducing bandwidth consumption, and job execution time. Several classification schemes for data replication were proposed in the literature, (i) static vs. dynamic, (ii) centralized vs. decentralized, (iii) push vs. pull, and (iv) objective function based. Dynamic data replication is a form of data replication that is performed with respect to the changing conditions of the grid environment. In this paper, we present a survey of recent dynamic data replication strategies. We study and classify these strategies by taking the target data grid architecture as the sole classifier. We discuss the key points of the studied strategies and provide feature comparison of them according to important metrics. Furthermore, the impact of data grid architecture on dynamic replication performance is investigated in a simulation study. Finally, some important issues and open research problems in the area are pointed out.Article Citation - WoS: 4Citation - Scopus: 9Identifying Critical Architectural Components With Spectral Analysis of Fault Trees(Elsevier Ltd., 2016) Ayav, Tolga; Sözer, HasanWe 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.
