Reliability

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The data consists of 2 sets of 2000 data points histograms and cumulative integral plots.

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Two software testing data sets:

(1) Commercial software testing data (file 1)

(2) ISRO mission software testing data (files 2, 3 and 4)

   

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sensor data

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Safety assessment of Cyber-Physical Systems (CPS) requires a tremendous amount of effort as the complexity of cyber-physical systems is increasing. A well-known approach for the safety assessment of CPS is Fault Injection (FI). The goal of fault injection is to find a catastrophic fault that can fail the system by injecting faults into it. These catastrophic faults are less likely to happen, and finding it requires tremendous labor and cost.

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This is a numerical example of parts deterioration monitoring constructed based on the literature "Preventive Maintenance and Joint Optimization of Spare Parts Inventory and Reservation Policy"

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The database contains information about three test systems, including the network connected to Bus 5 of the Roy Billinton Test System and two netwroks with 93 and 135 load nodes.

 

 

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README.txt for simulation files IEEE_Collaboration_N_entities_2021.mdl and IEEE_2_Platforms_federation_SF_2021.mdl

 

This is a README.txt for the model published on the paper titled:

 

Improving IoT Federation Resiliency with Distributed Ledger Technology, 2021, Elo T, et al.

 

This readme describes how to replicate the main simulation results from the paper using a Vensim

model file. The model file has been generated using the Vensim DSS Macintosh Version 

8.0.7 Double Precision x64.

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This dataset is the experimental data for the manuscript entitled "Standardization Workflow Technology of Software Testing Processes and Its Application to SRGM on RSA Timing Attack Tasks". The software fault data is generated from the testing processes of related software with RSA timing attack tasks, including the test data of three versions of RSA timing attack program and workflow verification system respectively. The attributes of test data contain no. of faults, fault type, interval time between faults and cumulative time, as well as estimate values for different SRGMs' parameters.

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Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems

Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems is called ERT-CORE. It defines specific input parameters, i.e., system's workload, average request processing time and availability. Defined parameters reflect system's state and react on its changes. Based on these parameters system reliability evaluation is performed.

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