Vehicular cloud computing networks: availability modelling and sensitivity analysis

Araújo, Gabriel; Rodrigues, Laécio; Oliveira, Kelly Mari Pires de; Fé, Iure; Khan, Razib Hayat; Silva, Francisco Airton

doi:10.1504/ijsnet.2021.117229

Cited by 7 publications

(2 citation statements)

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“…The power generator behaves differently from the other model components. The power generator has a cold standby mechanism [29]; that is, it will be only active when a certain condition is reached. The SWITCH_TIME transition will ensure the power generator is only activated when there is no other active energy source.…”

Section: Power System Smart Hospitalmentioning

confidence: 99%

Model-Driven Impact Quantification of Energy Resource Redundancy and Server Rejuvenation on the Dependability of Medical Sensor Networks in Smart Hospitals

Silva

Brito

Araújo

et al. 2022

Sensors

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The spread of the Coronavirus (COVID-19) pandemic across countries all over the world urges governments to revolutionize the traditional medical hospitals/centers to provide sustainable and trustworthy medical services to patients under the pressure of the huge overload on the computing systems of wireless sensor networks (WSNs) for medical monitoring as well as treatment services of medical professionals. Uncertain malfunctions in any part of the medical computing infrastructure, from its power system in a remote area to the local computing systems at a smart hospital, can cause critical failures in medical monitoring services, which could lead to a fatal loss of human life in the worst case. Therefore, early design in the medical computing infrastructure’s power and computing systems needs to carefully consider the dependability characteristics, including the reliability and availability of the WSNs in smart hospitals under an uncertain outage of any part of the energy resources or failures of computing servers, especially due to software aging. In that regard, we propose reliability and availability models adopting stochastic Petri net (SPN) to quantify the impact of energy resources and server rejuvenation on the dependability of medical sensor networks. Three different availability models (A, B, and C) are developed in accordance with various operational configurations of a smart hospital’s computing infrastructure to assimilate the impact of energy resource redundancy and server rejuvenation techniques for high availability. Moreover, a comprehensive sensitivity analysis is performed to investigate the components that impose the greatest impact on the system availability. The analysis results indicate different impacts of the considered configurations on the WSN’s operational availability in smart hospitals, particularly 99.40%, 99.53%, and 99.64% for the configurations A, B, and C, respectively. This result highlights the difference of 21 h of downtime per year when comparing the worst with the best case. This study can help leverage the early design of smart hospitals considering its wireless medical sensor networks’ dependability in quality of service to cope with overloading medical services in world-wide virus pandemics.

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Section: Power System Smart Hospitalmentioning

confidence: 99%

Model-Driven Impact Quantification of Energy Resource Redundancy and Server Rejuvenation on the Dependability of Medical Sensor Networks in Smart Hospitals

Silva

Brito

Araújo

et al. 2022

Sensors

Self Cite

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“…This section presents the structure of the extended model applying Cold, Warm and Hot Standby redundancies [28,29,30]. The MTTF and MTTR values for the extended models are the same as in Table 4 presented earlier.…”

Section: Extended Modelsmentioning

confidence: 99%

Blockchain as a service environment: a dependability evaluation

Correia

Ramalho

Silva

2022

Preprint

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Blockchain has become an important processing paradigm in recent years. The blockchain supports financial transactions and validates contracts, documents and data. However, the evolution of blockchain has become viable for many applications. The servers' availability and reliability (dependence) are required in the data processing. The contract will only be signed if there are enough components to form the blockchain blocks. This paper analyses the dependency between project components that use blockchain. We present a model based on stochastic Petri net (SPN) for evaluating the dependency of the blockchain architecture. The Design of Experiments (DoE) method was used to analyze this model's factors, seeking to know which ones had the higher impact on the system. The sensitivity analysis showed that the MongoDB component has a greater impact on the system dependency and the need to upgrade such a component. Also, for reliability, making component improvements is unnecessary if the system has fewer than 36,000 hours of runtime.

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Quantifying the impact of resource redundancy on smart city system dependability: a model-driven approach

Silva,

Fé,

Silva

et al. 2024

Cluster Comput

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Vehicular cloud computing networks: availability modelling and sensitivity analysis

Cited by 7 publications

References 0 publications

Model-Driven Impact Quantification of Energy Resource Redundancy and Server Rejuvenation on the Dependability of Medical Sensor Networks in Smart Hospitals

Model-Driven Impact Quantification of Energy Resource Redundancy and Server Rejuvenation on the Dependability of Medical Sensor Networks in Smart Hospitals

Blockchain as a service environment: a dependability evaluation

Quantifying the impact of resource redundancy on smart city system dependability: a model-driven approach

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