Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

Browse

Filters

2012 - 20172

Settings

Publisher: search.filters.publisher.Springer VerlagWoS Q: search.filters.wosQuartile.Q1

Search Results

Now showing 1 - 2 of 2
  • 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: 69
    Citation - Scopus: 89
    Joint Optimization for Object Class Segmentation and Dense Stereo Reconstruction
    (Springer Verlag, 2012) Ladicky, Lubor; Sturgess, Paul; Russell, Chris; Sengupta, Sunando; Baştanlar, Yalın; Clocksin, William; Torr, Philip H.S.
    The problems of dense stereo reconstruction and object class segmentation can both be formulated as Random Field labeling problems, in which every pixel in the image is assigned a label corresponding to either its disparity, or an object class such as road or building. While these two problems are mutually informative, no attempt has been made to jointly optimize their labelings. In this work we provide a flexible framework configured via cross-validation that unifies the two problems and demonstrate that, by resolving ambiguities, which would be present in real world data if the two problems were considered separately, joint optimization of the two problems substantially improves performance. To evaluate our method, we augment the Leu-ven data set (http://cms.brookes.ac.uk/research/visiongroup/ files/Leuven.zip), which is a stereo video shot from a car driving around the streets of Leuven, with 70 hand labeled object class and disparity maps. We hope that the release of these annotations will stimulate further work in the challenging domain of street-view analysis. Complete source code is publicly available (http://cms.brookes.ac.uk/ staff/Philip-Torr/ale.htm). © 2011 Springer Science+Business Media, LLC.