Dynamic cluster scheduling for cluster-tree WSNs

Abstract

While Cluster-Tree network topologies look promising for WSN applications with timeliness and energy-efficiency requirements, we are yet to witness its adoption in commercial and academic solutions. One of the arguments that hinder the use of these topologies concerns the lack of flexibility in adapting to changes in the network, such as in traffic flows. This paper presents a solution to enable these networks with the ability to self-adapt their clusters' duty-cycle and scheduling, to provide increased quality of service to multiple traffic flows. Importantly, our approach enables a network to change its cluster scheduling without requiring long inaccessibility times or the re-association of the nodes. We show how to apply our methodology to the case of IEEE 802.15.4/ZigBee cluster-tree WSNs without significant changes to the protocol. Finally, we analyze and demonstrate the validity of our methodology through a comprehensive simulation and experimental validation using commercially available technology on a Structural Health Monitoring application scenario.

A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

“…In addition, selecting CHs/forwarders with low amount of resources can further increase delay [244]. In [245], the authors introduce a treebased WSN clustering method which can balance the load of the network by reordering clusters based on available streams to reduce dynamic end-to-end delay. The proposed method analyzes the packet streams on-the-fly and changes the clusters and routes to reduce delay.…”

“…In [270], the authors introduce a method to utilize bandwidth allocation based on inter-cluster aggregation which reduces the volume of data in a hierarchical clustering technique in each layer, in addition to reducing energy consumption and bandwidth allocation in upper layers. In [245], the authors use a heuristic scheduling model in clusters to adapt the network with end-to-end delay and bandwidth allocation requirements. They use a scheduling model that can react to different data flow changes in routers (CHs) by re-ordering active periods of clusters and optimizing the time-slot to access shared channels by each cluster.…”