An Enhanced Tree Routing through Multi-criteria Decision Making over Wireless Sensor Networks

In a small-scale wireless sensor network, tree-based routing can achieve a low control overhead, low computational cost, and high responsiveness by eliminating the path search and avoiding the use of extensive broadcast messages. To choose the optimal parent node, existing approaches consider multiple decision criteria concurrently and integrate them using the linear weighted-sum method. However, they cannot achieve a reasonable trade-off between conflicting performance metrics because their mechanisms usually adopt subjective weights, which are often less objective and reduce their acceptance within the scientific community. To solve this problem, in this paper, we propose an enhanced parent selection algorithm for finding the best parent node by determining the relative importance of the decision criteria using the analytical hierarchy process and calculating the cost using the simple additive weighting method. The simulation results prove that the proposed multi-criteria decision-making based parent selection algorithm can provide a flexible trade-off among performance metrics such as the packet delivery ratio, end-to-end delay, and energy consumption ratio.