Most large-scale distributed file systems decouple a metadata operation from read and write operations for a file. In the distributed file systems, a certain server named a metadata server (MDS) is responsible for maintaining the metadata information of the file systems. In this paper, we propose a new metadata management scheme in order to provide the high metadata throughput and scalability for a cluster of MDSs. First, we derive a new metadata distribution technique. Then, we present a load balancing technique based on the distribution technique. Several experiments show that our scheme outperforms existing metadata management scheme in terms of scalability and load balancing.

In this paper, a new access method is proposed for current positions of moving objects on road networks in order to efficiently update their positions. In the existing index structures, the connectivity of edges is lost because the intersection points in which three or more edges are split. The proposed index structure preserves the network connectivity, which uses intersection oriented network model by not splitting intersection nodes that three or more edges meet for preserving the connectivity of adjacent road segments. The data node stores not only the positions of moving object but also the connectivity of networks.

In this paper, we propose a novel filtering method for processing continuous skyline queries in wireless sensor network environments. The existing filtering methods on such environments use filters that are based on router paths. However, these methods do not have a major effect on reducing data for sensor nodes to transmit to the base station, because the filters are applied to not the whole area but a partial area. Therefore, we propose a novel and efficient method to dramatically reduce the data transmissions of sensors through applying an effective filter with low costs to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.