Minimal-Overlap Centrality for Multi-Gateway Designation in Real-Time TSCH Networks

• Type: Article in International Scientific Journal
• Date: 2024

Authors

Gaitán, MG (Author) Other; Luis Almeida (Author) FEUP; D'Orey, PM (Author) Other; Santos, PM (Author) Other; Watteyne, T (Author) Other

Journal

Title: Transactions on Embedded Computing Systems

Vol. 23

Pages: 9:1-9:17

ISSN: 1539-9087

Publisher: ACM

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-010-104

DOI: 10.1145/3610583

Abstract (EN): This article presents a novel centrality-driven gateway designation framework for the improved real-time performance of low-power wireless sensor networks (WSNs) at system design time. We target time-synchronized channel hopping (TSCH) WSNs with centralized network management and multiple gateways with the objective of enhancing traffic schedulability by design. To this aim, we propose a novel network centrality metric termed minimal-overlap centrality that characterizes the overall number of path overlaps between all the active flows in the network when a given node is selected as gateway. The metric is used as a gateway designation criterion to elect as a gateway the node leading to the minimal number of overlaps. The method is then extended to multiple gateways with the aid of the unsupervised learning method of spectral clustering. Concretely, after a given number of clusters are identified, we use the new metric at each cluster to designate as cluster gateway the node with the least overall number of overlaps. Extensive simulations with random topologies under centralized earliest-deadline-first (EDF) scheduling and shortest-path routing suggest our approach is dominant over traditional centrality metrics from social network analysis, namely, eigen vector, closeness, betweenness, and degree. Notably, our approach reduces by up to 40% the worst-case end-to-end deadline misses achieved by classical centrality-driven gateway designation methods.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 17