A Formal Approach for RT-DVS Algorithms Evaluation Based on Statistical Model Checking

Dai, Shengxin; Mei, Hong; Guo, Bing; He, Yang; Zhang, Qiongyu; Sun, Lin; Du, Yi

doi:10.1155/2015/815230

Cited by 1 publication

(2 citation statements)

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“…This is because we had depicted these templates in the previous paper [11], so we only depict the template of reliability-aware power management in this section.…”

Section: Modeling In Uppaal-smcmentioning

confidence: 99%

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A Comparative Study of Reliability-Ignorant and Reliability-Aware Energy Management Schemes Using UPPAAL-SMC

Dai¹,

Mei²,

Guo³

2017

Scientific Programming

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Energy saving and high reliability are two key concerns in the design of real time systems. However, high reliability and low energy consumption are conflicting objects, and they are generally contrasted with temporal correctness. In this paper, we propose comparing reliability-ignorant and reliability-aware power management schemes with statistical model checking approach using UPPAAL-SMC. The power management schemes and the relevant components are modeled in the form of stochastic timed automata. And the analysis objectives are expressed as verification queries. With the model and queries as inputs, UPPAAL-SMC returns the probability of system failure and the expected value of energy consumption. In this analysis, we have considered three reliability-ignorant power management schemes and two reliability-aware power management schemes. Based on the comparative study, we provided guidelines for choosing the suitable scheme for a given system. One thing that should be emphasized is that our methodology is not limited to the schemes involved in this paper. The modeling and evaluating procedure can be applied to analyse other energy management schemes in practical application.

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“…This is because we had depicted these templates in the previous paper [11], so we only depict the template of reliability-aware power management in this section.…”

Section: Modeling In Uppaal-smcmentioning

confidence: 99%

“…In [11], Dai et al illustrated the applicability of statistical model checking to the area of RT-DVS algorithms evaluation. The relevant components involved in RT-DVS algorithms evaluation are modeled as stochastic timed automata and implemented in statistical model checker UPPAAL-SMC.…”

Section: Related Workmentioning

confidence: 99%