Innovative methods and algorithms for advanced data-intensive computing

The 2014 Special Issue of Future Generation Computer Systems is based on 'Innovative Methods and Algorithms for Advanced Data-Intensive Computing'. The first paper, titled 'Architectural Investigation of Matrix Data Layout on Multicore Processors', by Minwoo Kima and Won Woo Roa, recognizes that many practical applications include matrix operations as essential procedures. The second paper, titled 'Exploiting Fine-Grain Parallelism in the H.264 Deblocking Filter by Operation Reordering, by Tsung-Hsi Weng and Chung-Ping Chung, focuses the attention on the specific application scenario represented by the H.264 video compression standard, where the deblocking filtering contributes about one-third of all the computation in the decoder. Another paper, titled 'Mining Constrained Frequent Itemsets from Distributed Uncertain Data', by Alfredo Cuzzocrea, Carson Kai-Sang Leung and Richard Kyle MacKinnon, considers the application scenario represented by large amounts of streaming data generated from various sources, such as sensor data from environmental surveillance networks.