Automatic Weather Stations (AWSs) are widely used in environmental sensing. Often working in harsh environments, AWSs are equipped with rechargeable batteries, energy harvesting and meteorological sensors connected to a processing unit where a sensing and communication policy is executed. An optimal policy should provide the desired sensing and communication rates, while rmly guaranteeing the survival of the system. In this paper, we introduce a power model for AWSs and describe a simulator based on the Stochastic Activity Networks formalism. The simulator helps the designer in assessing the feasibility of a given policy, taking in consideration context information such as temperature and solar radiation. We successfully validated the simulator with data collected by a real-world AWS installed on an alpine glacier. A comparison showed that the proposed simulative approach is more accurate than analytical models based on average power production and consumption.

Simulation of Automatic Weather Stations for the Energy Estimation of Sensing and Communication Software Policies

AVVENUTI, MARCO;CESARINI, DANIEL;
2013

Abstract

Automatic Weather Stations (AWSs) are widely used in environmental sensing. Often working in harsh environments, AWSs are equipped with rechargeable batteries, energy harvesting and meteorological sensors connected to a processing unit where a sensing and communication policy is executed. An optimal policy should provide the desired sensing and communication rates, while rmly guaranteeing the survival of the system. In this paper, we introduce a power model for AWSs and describe a simulator based on the Stochastic Activity Networks formalism. The simulator helps the designer in assessing the feasibility of a given policy, taking in consideration context information such as temperature and solar radiation. We successfully validated the simulator with data collected by a real-world AWS installed on an alpine glacier. A comparison showed that the proposed simulative approach is more accurate than analytical models based on average power production and consumption.
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/11568/207985
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact