Penetration of wireless sensor networking (WSN) technology in different aspects of human life has made its problems more salient than ever. Routing is one of the important problems in WSN, and different algorithms have been devised to promote its efficiency and performance. In WSN, wherein normally tiny sensors have limited longevity, asymmetric load distribution among the network nodes potentially can endanger the robustness and sustainability of the network. With this aim, the paper provides a routing control framework for dynamic load balancing among the additional referral nodes.

After a good, smooth, and fluent literature review, the paper criticizes routing policies, aiming mostly at the packet delivery rates or lower delay mechanisms, mechanisms that potentially would sacrifice the overloaded nodes, cause early death, and decrease the longevity of the whole network.

In-network path tagging is the key topic of the paper. Leveraging this policy, a server in the sink point receives the information of the load ratio of nodes. Next, an unbalanced routing load detection algorithm is utilized to detect the over/under balanced nodes, and a mitigation algorithm is invoked for any possible parent exchange. The routing load balance algorithm assumes that at the same depth in the collection tree, with direct communication range, there should exist over/under loaded nodes to balance the loads with each other. It would be essential to prove that there certainly exist some such favorite pair nodes; otherwise, the algorithm is useless. It is not comprehensive.

Although the algorithm provides a nice method to increase the robustness of the network, the impact of the method on the performance and efficiency of the network (for instance, the packet delivery rate and delay, which are important criteria in the network) are vague. Empirical analysis of the algorithms via the experiments normally is not as reasonable as the algorithm analysis methodology, which was expected from the paper. The centralized nature of the proposed policies would enforce great overhead for the system as the number of nodes increases; normally in WSNs, distributed, local policies are prescribed to mitigate the issues.

The paper has good and novel ideas, with a nice structure and writing style, but I do not have an optimistic view concerning its applicability in industrial use cases.