A state-of-the-art review on performance measurement petri net models for safety critical systems of NPP

Jyotish, Nand Kumar; Singh, Lalit Kumar; Kumar, Chiranjeev

doi:10.1016/j.anucene.2021.108635

Cited by 20 publications

(5 citation statements)

References 72 publications

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“…The maintenance of a sizable amount of state overhead is required by this method, as is the division of the domain state among the participating controllers. In the paper by Jyotish et al [97], a performance metric based on dependability, availability, and security is described.…”

Section: Challenges Of Logically Centralized Controllersmentioning

confidence: 99%

A Qualitative and Comparative Performance Assessment of Logically Centralized SDN Controllers via Mininet Emulator

Sheikh,

Hwang,

Raza

et al. 2024

Computers

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An alternative networking approach called Software Defined Networking (SDN) enables dynamic, programmatically efficient network construction, hence enhancing network performance. It splits a traditional network into a centralized control plane and a configurable data plane. Because the core component overseeing every data plane action is the controller in the control plane, which may contain one or more controllers and is thought of as the brains of the SDN network, controller functionality and performance are crucial to achieve optimal performances. There is much controller research available in the existing literature. Nevertheless, no qualitative comparison study of OpenFlow-enabled distributed but logically centralized controllers exists. This paper includes a quantitative investigation of the performance of several distributed but logically centralized SDN controllers in custom network scenarios using Mininet, as well as a thorough qualitative comparison of them. More precisely, we give a qualitative evaluation of their attributes and classify and categorize 13 distributed but logically centralized SDN controllers according to their capabilities. Additionally, we offer a comprehensive SDN emulation tool, called Mininet-based SDN controller performance assessment, in this study. Using six performance metrics—bandwidth, round-trip time, delay, jitter, packet loss, and throughput—this work also assesses five distributed but logically centralized controllers within two custom network scenarios (uniform and non-uniform host distribution). Our analysis reveals that the Ryu controller outperforms the OpenDayLight controller in terms of latency, packet loss, and round-trip time, while the OpenDayLight controller performs well in terms of throughput, bandwidth, and jitter. Throughout the entire experiment, the HyperFlow and ONOS controllers performed worst in all performance metrics. Finally, we discuss detailed research findings on performance. These experimental results provide decision-making guidelines when selecting a controller.

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Section: Challenges Of Logically Centralized Controllersmentioning

confidence: 99%

A Qualitative and Comparative Performance Assessment of Logically Centralized SDN Controllers via Mininet Emulator

Sheikh,

Hwang,

Raza

et al. 2024

Computers

View full text Add to dashboard Cite

show abstract

“…The maintenance of a sizable amount of state overhead is required by this method, as is the division of domain state among the participating controllers. In the paper Jyotish et al [96], a performance metric based on dependability, availability, and security is described.…”

Section: Challenges Of Logically Centralized Controllersmentioning

confidence: 99%

A Qualitative and Comparative Performance Assessment of Logically Centralized SDN Controllers by Mininet Emulator

Sheikh,

Hwang,

Raza

et al. 2024

Preprint

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Software-defined networking (SDN) divides a traditional network into a programmable data plane and a centralized control plane. This technology is expected to transform traditional network companies that provide flexible and intelligent network operations. The core component utilized to oversee every data plane action is the controller in the control plane. In order to achieve optimal performances, the controller’s performance and capabilities are therefore crucial. There are lots of controller research available in existing literature. Nevertheless, no qualitative comparison study of OpenFlow-enabled distributed but logically centralized controllers exists for them. This article also includes a quantitative investigation of the performance of several distributed but logically centralized SDN controllers in custom network scenarios using Mininet, as well as a thorough qualitative comparison of them. More precisely, we give a qualitative evaluation of their attributes and classify and categorize 13 distributed but logically centralized SDN controllers according to their capabilities. Additionally, we offer a comprehensive SDN emulation tool called Mininet-based SDN controller performance assessment in this study. Using six performance metrics—bandwidth, round- trip time, delay, jitter, packet loss, and throughput—this work also assesses five distributed but logically centralized controllers against two custom network scenarios (uniform and non-uniform host distribution). Our investigation shows that the OpenDayLight controller performs the best across all performance criteria, with the exception of delay, packet loss and round trip time, where the Ryu controller excels. In the entire experiment, the HyperFlow and ONOS controller performs the worst in terms of all performance metrics. Finally, we discuss detailed research findings on the performance. These experimental results provide a decision-making guideline when selecting a controller.

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“…It has evolved to support formalisms like stochastic, colored, and stochastic colored, as well as the commonly used simple place and transition formalism. GreatSPN provides a range of tools to simplify the creation of system representations, including features for generating reachability graphs, verifying for dead markings, and facilitating the token [29,30].…”

Section: Different Simulation Tools Of Petri Netsmentioning

confidence: 99%

Dynamic Simulation and Modeling of a Novel NeuRaiSya for Railway Monitoring System Using Petri Nets

Deplomo,

Villaverde,

Paglinawan

2024

Sensors

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This research introduces the NeuRaiSya (Neural Railway System Application), an innovative railway signaling system integrating deep learning for passenger analysis. The objectives of this research are to simulate the NeuRaiSya and evaluate its effectiveness using the GreatSPN tool (graphical editor for Petri nets). GreatSPN facilitates evaluations of system behavior, ensuring safety and efficiency. Five models were designed and simulated using the Petri nets model, including the Dynamics of Train Departure model, Train Operations with Passenger Counting model, Timestamp Data Collection model, Train Speed and Location model, and Train Related-Issues model. Through simulations and modeling using Petri nets, the study demonstrates the feasibility of the proposed NeuRaiSya system. The results highlight its potential in enhancing railway operations, ensuring passenger safety, and maintaining service quality amidst the evolving railway landscape in the Philippines.

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A state-of-the-art review on performance measurement petri net models for safety critical systems of NPP

Cited by 20 publications

References 72 publications

A Qualitative and Comparative Performance Assessment of Logically Centralized SDN Controllers via Mininet Emulator

A Qualitative and Comparative Performance Assessment of Logically Centralized SDN Controllers via Mininet Emulator

A Qualitative and Comparative Performance Assessment of Logically Centralized SDN Controllers by Mininet Emulator

Dynamic Simulation and Modeling of a Novel NeuRaiSya for Railway Monitoring System Using Petri Nets

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