@InProceedings{CarnielRoCiVaCoCi:2018:EfFlSp,
               author = "Carniel, Anderson Chaves and Roumelis, George and Ciferri, Ricardo 
                         Rodrigues and Vassilakopoulos, Michael and Corral, Antonio and 
                         Ciferri, Cristina Dutra de Aguiar",
          affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {University of 
                         Thessaly} and {Universidade Federal de S{\~a}o Carlos (UFSCar)} 
                         and {University of Thessaly} and {University of Almeria} and 
                         {Universidade de S{\~a}o Paulo (USP)}",
                title = "An efficient flash-aware spatial index for points",
                 year = "2018",
               editor = "Vinhas, L{\'u}bia (INPE) and Campelo, Claudio (UFCG)",
                pages = "68--79",
         organization = "Simp{\'o}sio Brasileiro de Geoinform{\'a}tica, 19. (GEOINFO)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Spatial database systems often employ spatial indices to speed up 
                         the processing of spatial queries. In addition, modern spatial 
                         database applica- tions are interested in exploiting the positive 
                         characteristics of flash-based Solid State Drives (SSDs) like fast 
                         reads and writes. However, designing spatial in- dices for SSDs 
                         (i.e., flash-aware spatial indices) has been a challenging task 
                         because of the intrinsic characteristics of these devices. In this 
                         paper, we pro- pose the eFIND xBR+-tree, a novel flash-aware 
                         spatial index for points. The eFIND xBR+-tree combines the 
                         efficient indexing method of the xBR+-tree with the sophisticated 
                         data structures and algorithms of eFIND to handle points in SSDs 
                         efficiently. Experiments carried out considering real and 
                         synthetic spa- tial data showed that the eFIND xBR+-tree overcame 
                         its closest competitor by reducing the elapsed time to construct 
                         the index from 28.4% to 83.5% and to execute spatial queries up to 
                         34.6%.",
  conference-location = "Campina Grande",
      conference-year = "05-07 dez. 2018",
                 issn = "2179-4847",
             language = "pt",
                  ibi = "8JMKD3MGPDW34P/3SEUQ98",
                  url = "http://urlib.net/ibi/8JMKD3MGPDW34P/3SEUQ98",
           targetfile = "p7.pdf",
        urlaccessdate = "28 abr. 2024"
}