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Tuning Energy Consumption Strategies in the Railway Domain: A Model-Based Approach

Authors: Basile D; Di Giandomenico F; Gnesi S;

Tuning Energy Consumption Strategies in the Railway Domain: A Model-Based Approach

Abstract

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.

Keywords

Dependable Computing, C.3 SPECIAL-PURPOSE AND APPLICATION-BASED SYSTEMS, Green IT, I.6 SIMULATION AND MODELING, Theoretical Computer Science; Computer Science (all), Model-based analysis, C.4 PERFORMANCE OF SYSTEMS

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    7
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Average
Top 10%
Green