Multigateway Designation for Real-Time TSCH Networks Using Spectral Clustering and Centrality

Abstract

This letter proposes a multi-gateway 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 un-supervised learning that allows defining arbitrary k disjoint clusters without knowledge of the nodes 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 5gateways, 99% schedulability can be achieved with 3.5 times more real-time flows than in a random benchmark.

Ultralow Power and Green TSCH-Based WSNs With Proactive Reduction of Idle Listening

“…In particular, in [27] the VAM-HSA algorithm was proposed to solve an energy-efficient maximization problem by reducing its complexity, in [28] the PRCOS algorithm was proposed to obtain a scheduling aimed at maximizing system lifetime by taking into account power consumption, in [29] a MAC layer scheduling algorithm named TREE was proposed to dynamically optimize allocated cells, instead in [30] the scheduling algorithm optimizes the use of shared cells. A suitable scheduling not only permits to decrease power consumption of the network, but also to improve its real-time capabilities: in [31] this was achieved with the combination of spectral clustering unsupervised learning and earliest deadline first (EDF) scheduling algorithm, while in [32] similar goals were obtained with an orchestrator (SDN-TSCH) that acts in a centralized fashion.…”