WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Conference Object Citation - WoS: 17Citation - Scopus: 30A Performance and Profit Oriented Data Replication Strategy for Cloud Systems(Institute of Electrical and Electronics Engineers Inc., 2017) Tos, Uras; Mokadem, Riad; Hameurlain, Abdelkader; Ayav, Tolga; Bora, ŞebnemIn today's world, tenants of cloud systems expect timely responses to queries that process ever-increasing sizes of data. However, most cloud providers offer their services without any performance guarantees to their tenants. In this paper we propose a data replication strategy that aims to satisfy performance guarantees for the tenant while ensuring profitability of the cloud provider. Our strategy estimates the response time of the queries, as well as the expenditures that affect the profitability of the cloud provider. The decision of whether to perform replication is determined by the fulfillment of these two criteria. Validity of the proposed strategy is provided by means of a simulation study.Conference Object Citation - WoS: 4Citation - Scopus: 6Robust Placement of Mobile Relational Operators for Large Scale Distributed Query Optimization(Institute of Electrical and Electronics Engineers Inc., 2007) Ergenç, Belgin; Morvan, Franck; Hameurlain, AbdelkaderThis paper presents a compile-time placement method of mobile relational operators MROs in a large scale environment. MROs are self adaptive to changing runtime conditions by deciding their execution place if they discover compile-time estimation errors. Proposed placement methods tend to have a main drawback with MROs running over a large scale environment: their focus is on finding optimal performance depending on single-point estimation at compile-time, instead of optimal performance over an estimation interval. We propose: (i) to determine the migration space of a MRO including the sites on which the MRO is allowed to migrate during its execution, and (ii) to find the robust site which will allow acceptable response time in an estimation interval. Performance study shows that, with a risk of loosing around 6% in response time, it is possible to gain up to 300% with the proposed robust placement.