RETRACTED ARTICLE: Efficient multi-dimensional web information discovery in wireless sensor network

The increasing availability of small-size sensor devices during the last few years and the large amount of data that they generate has led to the necessity for more efficient methods regarding data management. Here a model has been introduced that can be used for data gathering and information management in sensor networks which provides some advantages through the utilization of semantic web technologies. This work provides a multidimensional approach named an Octree-based Hausdorff Distance aided Unified Cube or OHD Aided Unified Cube (OAUC) which offers a generic representation for both warehoused data and Linked Object Data (LOD) at the conceptual level. A two-stage process is built using Unified Cube according to decision-makers’ needs. Initially, the schemas published with specific modeling languages are transformed into a common conceptual representation called exportation cube. Then the associated data are combined using Hausdorff Distance (HD) to form a Unified Cube. The information discovery problem is formulated as a load balancing technique for multiple attributes, with the combined aim being to increase network lifetime, reduce hotspots and also to reduce query processing latency by introducing multi-resolution. The efficiency of the proposed OAUC is analyzed by the comparison of OAUC with existing VF-CAN indexing and storage schemes. OAUC provides better performance in Hausdorff Distance (HD) calculation that is proved by comparing it with ZHD and NAIVE algorithms.