ous Skyline Computati rs Based on Manhattan

The continuous Skyline query h the subject of the several researches due to its applications such as multi-criteria decisio analysis network, wireless sensor network and In these applications, the datasets are huge dimensions. Moreover, they constantly chan Therefore, this query is considered as a com operation that finding the result in a rea challenge. In this paper, we present an continuous Skyline approach. In our sugge dataset points are sorted and pruned bas distance. Moreover, we use several optimiz optimize memory usage in comparis implementation. In addition, besides the ap parallelization methods, we partition the time number of available cores. The experimental r that contains 800k points with 7 dimensions speedup.