Wireless Meter-Bus is an open standard for power-efficient smart metering. Data are collected from meters and transmitted to the collector for processing. In smart cities, placing meters with the best quality communication signal is often challenging for urban constraints and other communication signals. Meters can also have limited capabilities in terms of memory and CPU. Previous work has been addressing the reliability issue only in the context of direct collector-meter communication. This paper proposes a novel noise adaptive routing for utility networks (NARUN) protocol for improved performance and efficient routing in a partially connected mesh network. The collector keeps a weighted graph of the whole network where weights define the link failure index. No keep-alive or control messages are used to update the weights. Meters eavesdrop on the surrounding environment and efficiently report link failure indexes to the collector with ordinary reading messages. We validate NARUN on a real case study.

NARUN: noise adaptive routing for utility networks

Mostarda L.;
2022

Abstract

Wireless Meter-Bus is an open standard for power-efficient smart metering. Data are collected from meters and transmitted to the collector for processing. In smart cities, placing meters with the best quality communication signal is often challenging for urban constraints and other communication signals. Meters can also have limited capabilities in terms of memory and CPU. Previous work has been addressing the reliability issue only in the context of direct collector-meter communication. This paper proposes a novel noise adaptive routing for utility networks (NARUN) protocol for improved performance and efficient routing in a partially connected mesh network. The collector keeps a weighted graph of the whole network where weights define the link failure index. No keep-alive or control messages are used to update the weights. Meters eavesdrop on the surrounding environment and efficiently report link failure indexes to the collector with ordinary reading messages. We validate NARUN on a real case study.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1568815
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact