We propose a generic algorithm to determine maximum bottleneck node weight-based data gathering (MaxBNW-DG) trees for wireless sensor networks (WSNs) and compare the performance of the MaxBNW-DG trees with those of maximum and minimum link weight-based data gathering trees (MaxLW-DG and MinLW-DG trees). Assuming each node in a WSN graph has a weight, the bottleneck weight for the path from a node u to the root node of the DG tree is the minimum of the node weights on the path (inclusive of the weights of the end nodes). The MaxBNW-DG tree algorithm determines a DG tree such that each node has a path of the largest bottleneck weight to the root node. We observe the MaxBNW-DG trees to incur lower height, larger percentage of nodes as leaf nodes and a larger weight per intermediate node compared to the leaf node; the tradeoff being a larger a network-wide data aggregation delay due to larger number of child nodes per intermediate node. The MaxBNW-DG algorithm could be used to determine DG trees with larger trust score, larger energy (and other such criterion for node weight) per intermediate node compared to the leaf node.
Classification and Analysis of Communication Protection Policy Anomalies
