Download now Free registration required
Data aggregations from Sensors to a sink in Wireless Sensor Networks (WSNs) are typically characterized by correlation along the spatial, semantic, and temporal dimensions. Exploiting such correlation when performing data aggregation can result in considerable improvements in the bandwidth and energy performance of WSNs. For the sensors-to-sink data delivery, the authors first explore two theoretical solutions: the Shortest Path Tree (SPT) and the Minimum Spanning Tree (MST) approaches. To approximate the optimal solution (MST) in case of perfect correlation among data, they propose a new aggregation which combines the Minimum Dominating Set (MDS) with the Shortest Path Tree (SPT) in order to aggregate correlated data.
- Format: PDF
- Size: 937 KB