Abstract

This letter proposes a multigateway designation framework to design real-time wireless sensor networks (WSNs) improving traffic schedulability, i.e., meeting the traffic time constraints. To this end, we resort to spectral clustering-unsupervised learning that allows defining arbitrary $k$ disjoint clusters without the knowledge of the node's physical position. In each cluster, we use a centrality metric from social sciences to designate one gateway. This novel combination is applied to a time-synchronized channel-hopping (TSCH) WSN under earliest-deadline-first (EDF) scheduling and shortest path routing. Simulation results under varying configurations show that our framework is able to produce WSN designs that greatly reduce the worst case network demand. In a situation with five gateways, 99% schedulability can be achieved with 3.5 times more real-time flows than in a random benchmark.