A Novel Trust Evaluation Method for Logic Circuits in IoT Applications Based on the E-PTM Model

Xiao, Jie; Jiang, Jianhui; Li, Xiaoxin; Huang, Yina; Yang, Xuhua; Shi, Zhanhui; Lou, Jungang

doi:10.1109/access.2018.2845911

Cited by 7 publications

(3 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Specific IoT research topics for 4th industrial revolution provide opportunities for smart manufacturing in terms of real-time traceability, visibility and interoperability in production planning, implementation and control (Zhang et al., 2016), flexibility in systems, monitoring, and adaptation to change manufacturing needs (Kumar, 2018), besides that reliability is also an important research topic in other IoT applications and cloud environments (Xiao et al., 2018).…”

Section: Resultsmentioning

confidence: 99%

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Dachyar

Zagloel

Saragih

2019

Heliyon

104

View full text Add to dashboard Cite

The term "Internet of Things" first appeared in publication paper since 2006, describing the paradigm of evolution concept that brought about by the presence of internet technology (Vermesan and Friess, 2015) which is very important in contemporary circumstances. This study conducted an in-depth analysis of the research material written on 26420 papers which focused on the published Internet of Things (IoT) research, starting from the firstly year IoT keyword appeared in 2006 until 2018. The selected paper is a combination of various disciplines and publications which are all indexed by Scopus wherein the article discusses IoT. IoT articles are classified using key attributes in sequence: the methodology used, general knowledge and applied concepts, and various general exploration topics. By using the Scientometrics method, this method will group the overall terms that appear frequently from the Scopus paper database according to keywords, titles, and abstracts. The resulting data is then studied to understand and distinguish trends that occur in the time span along with the general characteristics of the paper, in the mathematics visual scheme. All various issues that are considered in the paper's methodology selection, their studied and services innovations, and continuing discoveries on the characteristics, concepts, and processes applied to IoT success. Although it only involves scopus indexed paper, this study found a remarkable increase in the number of articles on IoT in each category of the paper. This study also reveals the direction of the regular discipline of knowledge. The use of the Scientometrics method makes the analysis able to focus on the movement of characteristics and IoT themes to researcher's direction that has not found at this time, as a comprehensive guide to further research and industry strategy that is more directed on concepts that support the 4th industrial revolution.

show abstract

Section: Resultsmentioning

confidence: 99%

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Dachyar

Zagloel

Saragih

2019

Heliyon

104

View full text Add to dashboard Cite

show abstract

“…The circuit's primary input fanouts are not considered effective fanouts. This is due to our assumption of error-free primary input, as indicated in [12], [15] and [23], a probability input matrix of [1 0] is considered. Consequently, in terms of input fanout configurations, the binary nature of the input probability matrix eliminates the possibility of similar iterative states or impassable states in the computations.…”

Section: A Effective Fanout Algorithmmentioning

confidence: 99%

“…Various solutions have been proposed to address this issue, often by adding specific assumptions to improve accuracy while reducing computational costs. Exact methods like Probabilistic Transfer Matrices (PTMs) [13], [14], [15], Probabilistic Gate Models (PGMs) [16], Binary Decision Diagrams (BDDs) [17], Boolean Difference Calculus [18], [19], [20], Conditional Probability Matrix (CPM) [21], [22], and Bayesian Networks (BNs) [1], [23], calculate signal probability. However, their exponential time/space complexity limits their applicability to small circuits.…”

Section: Introductionmentioning

confidence: 99%

An Effective Fanout-Based Method for Improving Error Propagation Probability Estimation in Combinational Circuits

Esmaieli,

Peiravi,

Sedaghat

2024

IEEE Access

View full text Add to dashboard Cite

The downsizing of nanoscale circuits imposes new challenges for circuit reliability, including hard defects, soft errors and unsaturated voltage/current. Many studies on the reliability of digital circuits have focused on achieving accurate reliability estimation and more efficiency for larger circuits. To achieve accurate reliability estimation, it is necessary to address the issue of error propagation and consider correlated signals from reconverging paths in reliability calculations. In this paper, an error propagation probability model for each gate, which takes into account the probability of an unreliable logic gate's input signal and relates it to the probability of the output signal is proposed. Additionally, we introduce an efficient approach that utilizes a new fanout matrix to tackle the reconvergent fanouts problem. Furthermore, to ensure an accurate estimation of combinational logic circuit reliability, the probabilities obtained for each fanout should be included in the calculations by defining a fanout probability matrix. To address this issue, a new method is proposed at each calculation stage, aiming to minimize computational complexity making it suitable for large circuits with a significant number of fanouts. We conducted various simulations to demonstrate the accuracy and scalability of the proposed method on the ISCAS 85 benchmark circuit and EPFL Benchmark. The results show less than 1% average relative error in reliability estimation and outperform state-of-the-art methods in reliability estimation and algorithm runtime.

show abstract

A Location Method for Reliability-Critical Paths Based on Monte Carlo Search Tree

Sun

et al. 2020

Machine Learning for Cyber Security

View full text Add to dashboard Cite

A Novel Trust Evaluation Method for Logic Circuits in IoT Applications Based on the E-PTM Model

Cited by 7 publications

References 36 publications

Knowledge growth and development: internet of things (IoT) research, 2006–2018

Knowledge growth and development: internet of things (IoT) research, 2006–2018

An Effective Fanout-Based Method for Improving Error Propagation Probability Estimation in Combinational Circuits

A Location Method for Reliability-Critical Paths Based on Monte Carlo Search Tree

Contact Info

Product

Resources

About