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 11 publications

(10 citation statements)

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“…In a study by Araujo et al [5], stochastic Petri nets (SPNs) and reliability block diagrams (RBD) were employed to assess the availability and reliability of a vehicular cloud computing architecture with multiple Roadside Units (RSUs). Two sensitivity analyses were conducted to identify the components of the model with the most significant impact.…”

Section: Related Workmentioning

confidence: 99%

“…The proposed model is capable of calculating the mean response time, resource utilization, and the number of discarded requests. Araujo et al [5] utilize SPNs and reliability block diagrams (RBD) to assess the availability and reliability of a vehicular cloud computing (VCC) architecture with multiple roadside units (RSUs). Two sensitivity analyses were conducted to identify the model components that have the most significant impact.…”

Section: Related Workmentioning

confidence: 99%

“…In this study, Gonçalves et al [17] developed stochastic Petri net models for a surveillance monitoring system, analyzing several parameters to achieve the highest level of dependability. Furthermore, only four papers have investigated dependability in the context of vehicular ad-hoc networks (VANETs) [29,13,31,5]. For instance, Qi et al [29] utilized Time Petri nets (TPN) and Synchronized Petri nets (SPNs) to design a traffic control system (ITCS) for intersections, addressing accidents and providing emergency response to prevent further accidents.…”

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confidence: 99%

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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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Effective quality management plays a pivotal role in ensuring the smooth operation of smart city systems, which have significant implications for safety, accessibility, affordability, and maintainability. Dependability of autonomous systems is of utmost importance, as achieving satisfactory levels of availability and reliability poses considerable challenges. Smart cities are characterized by interconnected sub-architectures, encompassing vehicle monitoring, sidewalk monitoring, and building monitoring, all of which need to function efficiently. Analytical models such as Petri nets, Markov chains, and fault trees are well-suited for evaluating complex scenarios in the context of smart cities. This paper presents analytical models that utilize fault tree and Markov chain techniques to assess the availability and reliability of smart city monitoring systems. The model is divided into shared and non-shared components, with non-shared components being specific to certain contextual applications, while shared components, such as data processing and electrical power, are essential for all smart city monitoring and management systems. The study underscores the ease with which the fault tree model can enhance availability by modifying failure requirements and resources. Case studies provide concrete examples of how availability improved from 95.3% to 99.8% by varying a configuration known as "KooN" in multiple components. This paper takes a comprehensive approach to evaluating the dependability of smart city architectures and contributes advancements, such as hierarchical modeling, sequential sensitivity analysis, and the "KooN" analytic method. These contributions expand the Francisco Airton Silva (F.A.S.), Iure Fé (I.F.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

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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

Self Cite

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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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“…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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Vehicular cloud computing networks: availability modelling and sensitivity analysis

Cited by 11 publications

References 0 publications

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

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

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

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