scholarly journals Vulnerability-Aware Resilient Networks: Software Diversity-based Network Adaptation

2021 ◽  
pp. 1-1
Author(s):  
Qisheng Zhang ◽  
Jin-Hee Cho ◽  
Terrence J. Moore ◽  
Ing-Ray Chen
Keyword(s):  
Network Adaptation ◽  
Software Diversity ◽  
Resilient Networks

EXPERIENCE IN METRICS AND MEASUREMENTS FOR N-VERSION PROGRAMMING

1994 ◽  
Vol 01 (01) ◽  
pp. 41-62 ◽  
Author(s):  
MICHAEL R. LYU ◽  
JIA-HONG CHEN ◽  
ALGIRDAS AVIŽIENIS
Keyword(s):  
Life Cycle ◽  
Flight Control ◽  
Fault Tolerant ◽  
Structural Diversity ◽  
Control Software ◽  
Baseline Design ◽  
Software Diversity ◽  
Points Of View ◽  
Design Diversity ◽  
Diversity Measurement

The N-Version Programming (NVP) approach applies the idea of design diversity to obtain fault-tolerant software units, called N-Version Software (NVS) units. The effectiveness of this approach is examined by the software diversity achieved in the member versions of an NVS unit. We define and formalize the concept of design diversity and software diversity in this paper. Design diversity is a property naturally applicable to the NVP process to increase its fault-tolerance attributes. The baseline design diversity is characterized by the employment of independent programming teams in the NVP. More design diversity investigations could be enforced in the NVP design process, including different languages, different tools, different algorithms, and different methodologies. Software diversity is the resulting dissimilarities appearing in the NVS member versions. We characterize it from four different points of view that are designated as: structural diversity, fault diversity, tough-spot diversity, and failure diversity. Our goals are to find a way to quantify software diversity and to investigate the measurements which can be applied during the life cycle of NVS to gain confidence that operation will be dependable when NVS is actually employed. The versions from a six-language N-Version Programming project for fault-tolerant flight control software were used in the software diversity measurement.

Automatic Software Diversity

2015 ◽  
Vol 13 (2) ◽  
pp. 30-37 ◽  
Author(s):  
Per Larsen ◽  
Stefan Brunthaler ◽  
Michael Franz
Keyword(s):  
Software Diversity ◽  
Automatic Software

scholarly journals High-Performance Adaptive Neurofuzzy Classifier with a Parametric Tuning

2018 ◽  
Vol 155 ◽  
pp. 01037
Author(s):  
Sergey Gorbachev ◽  
Vladimir Syryamkin
Keyword(s):  
Decision Tree ◽  
High Performance ◽  
Fuzzy Inference ◽  
Back Propagation ◽  
Adaptive Algorithms ◽  
Fuzzy Classifier ◽  
Network Adaptation ◽  
Error Back Propagation ◽  
Multicriteria Problems ◽  
Neuro Fuzzy

The article is devoted to research and development of adaptive algorithms for neuro-fuzzy inference when solving multicriteria problems connected with analysis of expert (foresight) data to identify technological breakthroughs and strategic perspectives of scientific, technological and innovative development. The article describes the optimized structuralfunctional scheme of the high-performance adaptive neuro-fuzzy classifier with a logical output, which has such specific features as a block of decision tree-based fuzzy rules and a hybrid algorithm for neural network adaptation of parameters based on the error back-propagation to the root of the decision tree.

scholarly journals Stochastic Models of Emerging Infectious Disease Transmission on Adaptive Random Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Navavat Pipatsart ◽  
Wannapong Triampo ◽  
Charin Modchang
Keyword(s):  
Infectious Disease ◽  
Disease Transmission ◽  
Random Network ◽  
Network Models ◽  
Transmission Probability ◽  
Stochastic Simulations ◽  
Random Networks ◽  
Cumulative Number ◽  
Network Adaptation ◽  
Infectious Disease Dynamics

We presented adaptive random network models to describe human behavioral change during epidemics and performed stochastic simulations of SIR (susceptible-infectious-recovered) epidemic models on adaptive random networks. The interplay between infectious disease dynamics and network adaptation dynamics was investigated in regard to the disease transmission and the cumulative number of infection cases. We found that the cumulative case was reduced and associated with an increasing network adaptation probability but was increased with an increasing disease transmission probability. It was found that the topological changes of the adaptive random networks were able to reduce the cumulative number of infections and also to delay the epidemic peak. Our results also suggest the existence of a critical value for the ratio of disease transmission and adaptation probabilities below which the epidemic cannot occur.

Topological Design Using Genetic Algorithms

2013 ◽  
pp. 153-173
Author(s):  
Rui Manuel Morais ◽  
Armando Nolasco Pinto
Keyword(s):  
Genetic Algorithm ◽  
Programming Model ◽  
Capital Expenditure ◽  
Initial Population ◽  
Minimum Capital ◽  
Topological Design ◽  
Node Location ◽  
Telecommunications Services ◽  
Resilient Networks

The proliferation of Internet access and the appearance of new telecommunications services are originating a demand for resilient networks with extremely high capacity. Thus, topologies able to recover connections in case of failure are essential. Given the node location and the traffic matrix, the survivable topological design is the problem of determining the network topology at minimum capital expenditure such that survivability is ensured. This problem is strongly NP-hard and heuristics are traditionally used to search near-optimal solutions. The authors present a genetic algorithm for this problem. As the convergence of the genetic algorithm depends on the used operators, an analysis of their impact on the quality of the obtained solutions is presented as well. Two initial population generators, two selection methods, two crossover operators, and two population sizes are compared, and the quality of the obtained solutions is assessed using an integer linear programming model.

Metacommentary and Mythology

2019 ◽  
pp. 163-180
Author(s):  
Jonathan Bignell
Keyword(s):  
Hybrid Identity ◽  
Performance Style ◽  
Network Adaptation ◽  
National Differences ◽  
Similarities And Differences ◽  
And Performance ◽  
Production Company ◽  
Husband And Wife

The chapter focuses on the comedy drama Episodes (2011–2018), made by the British production company Hat Trick for the BBC and Showtime. A British husband and wife duo of screenwriters work on a US network adaptation of their hit UK comedy show, which is “Americanized,” and they fight for their creative authority and their marriage. Episodes has a hybrid identity in terms of form, format, and genre, expressed in decisions including setting, casting, and performance style. Each of these can be read as a commentary on the similarities and differences between American and British television cultures, alongside the narrative’s thematization of cultural and national differences. Episodes talks about transatlantic television and self-consciously performs it, asking whether a program or a person can be transatlantic by making a joke of it. The chapter argues that Episodes is a metacommentary on deeply embedded myths about the TV of each nation.

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