Cautious usage of energy resources is gaining great attention nowadays, both from environmental and economical point of view. Therefore, studies devoted to analyze and predict energy consumption in a variety of application sectors are becoming increasingly important, especially in combination with other non-functional properties, such as reliability, safety and availability. This paper focuses on energy consumption strategies in the railway sector, addressing in particular rail road switches through which trains are guided from one track to another. Given the criticality of their task, the temperature of these devices needs to be kept above certain levels to assure their correct functioning. By applying a stochastic model-based approach, we analyse a family of energy consumption strategies based on thresholds to trigger the activation/deactivation of energy supply. The goal is to offer an assessment framework through which appropriate tuning of threshold-based energy supply solutions can be achieved, so to select the most appropriate one, resulting in a good compromise between energy consumption and reliability level.
CITATION STYLE
Basile, D., Di Giandomenico, F., & Gnesi, S. (2016). Tuning energy consumption strategies in the railway domain: A model-based approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9953 LNCS, pp. 315–330). Springer Verlag. https://doi.org/10.1007/978-3-319-47169-3_23
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