Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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

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Subject: search.filters.subject.Cloud computingWoS Q: search.filters.wosQuartile.Q1

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  • Article
    Citation - WoS: 28
    Citation - Scopus: 28
    Multi-Helper Noma for Cooperative Mobile Edge Computing
    (Institute of Electrical and Electronics Engineers, 2022) Yılmaz, Saadet Simay; Özbek, Berna
    The next-generation wireless networks are expected to support a number of computation-intensive and delay-sensitive applications such as virtual reality (VR), autonomous driving, telesurgery and unmanned aerial vehicles (UAVs). Since many devices are computation and power limited, mobile edge computing (MEC) has been deemed as a promising way to enhance computation service. In this paper, we propose a novel cooperative MEC that exploits the combination of non-orthogonal multiple access (NOMA) and multiple helpers. In the proposed system featuring a user, multiple helpers and a base station (BS), the user can simultaneously offload its computation-intensive tasks to the helpers using NOMA when there is no strong direct transmission link between the user and the BS. Then, the helpers can compute and offload these tasks through NOMA. Thus, in the proposed scheme, the computation and offloading modes at the helpers are determined with respect to the optimized task offloading decision factor. The simulation results show that the proposed NOMA-based cooperative MEC significantly increases the total offloading data under the latency constraints compared to the benchmark schemes featuring one helper with strong direct transmission link. IEEE
  • 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.