Fault-Tolerant Scheduler with Genetic Algorithm for Safety-Critical Time-Triggered Systems of Systems

2020 ◽  
Author(s):  
Setareh Majidi ◽  
Roman Obermaisser ◽  
Sudam Wasala ◽  
Mario Qosja
Keyword(s):  
Genetic Algorithm ◽  
Fault Tolerant ◽  
Critical Time ◽  
Systems Of Systems ◽  
Safety Critical

scholarly journals Fault Tolerant PLBGSA: Precedence Level Based Genetic Scheduling Algorithm for P2P Grid

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Piyush Chauhan ◽  
Nitin
Keyword(s):  
Genetic Algorithm ◽  
Directed Acyclic Graph ◽  
Fault Tolerant ◽  
Scheduling Algorithm ◽  
Complex Task ◽  
Grid Scheduling ◽  
Complex Tasks ◽  
Small Organizations ◽  
Grid Resources ◽  
Desirable Trait

Due to monetary limitation, small organizations cannot afford high end supercomputers to solve highly complex tasks. P2P (peer to peer) grid computing is being used nowadays to break complex task into subtasks in order to solve them on different grid resources. Workflows are used to represent these complex tasks. Finishing such complex task in a P2P grid requires scheduling subtasks of workflow in an optimized manner. Several factors play their part in scheduling decisions. The genetic algorithm is very useful in scheduling DAG (directed acyclic graph) based task. Benefit of a genetic algorithm is that it takes into consideration multiple criteria while scheduling. In this paper, we have proposed a precedence level based genetic algorithm (PLBGSA), which yields schedules for workflows in a decentralized fashion. PLBGSA is compared with existing genetic algorithm based scheduling techniques. Fault tolerance is a desirable trait of a P2P grid scheduling algorithm due to the untrustworthy nature of grid resources. PLBGSA handles faults efficiently.

Safety-Critical, Dependable, and Fault-Tolerant Cyber-Physical Systems

2018 ◽  
pp. 54-78
Author(s):  
Guru Prasad Bhandari ◽  
Ratneshwer Gupta
Keyword(s):  
Fault Tolerance ◽  
Fault Tolerant ◽  
Cyber Physical Systems ◽  
General Information ◽  
The Internet ◽  
Physical Systems ◽  
Safety Critical ◽  
Computer Based

Cyber-physical systems (CPSs) are co-engineered integrating with physical and computational components networks. Additionally, a CPS is a mechanism controlled or monitored by computer-based algorithms, tightly interacting with the internet and its users. This chapter presents the definitions relating to dependability, safety-critical and fault-tolerance of CPSs. These definitions are supplemented by other definitions like reliability, availability, safety, maintainability, integrity. Threats to dependability and security like faults, errors, failures are also discussed. Taxonomy of different faults and attacks in CPSs are also presented in this chapter. The main objective of this chapter is to give the general information about secure CPS to the learners for the further enhancement in the field of CPSs.

High-Power-Density Fault-Tolerant PM Generator for Safety-Critical Applications

2014 ◽  
Vol 50 (3) ◽  
pp. 1717-1728 ◽  
Author(s):  
Ayman M. EL-Refaie ◽  
Manoj R. Shah ◽  
Kum-Kang Huh
Keyword(s):  
Power Density ◽  
High Power ◽  
Fault Tolerant ◽  
High Power Density ◽  
Safety Critical

Genetic multistart algorithm for the design of fault-tolerant systems

2008 ◽  
Vol 222 (1) ◽  
pp. 17-29
Author(s):  
K Echtle ◽  
I Eusgeld ◽  
D Hirsch
Keyword(s):  
Genetic Algorithm ◽  
Fault Tolerance ◽  
Fault Tolerant ◽  
Design Method ◽  
Fitness Function ◽  
Evolutionary Process ◽  
Mechatronic Systems ◽  
Fast Evaluation ◽  
Pareto Solution ◽  
Fault Tolerant Systems

This paper presents a new approach to the multiobjective design of fault-tolerant systems. The design objectives are fault tolerance and cost. Reducing the cost is of particular importance for fault-tolerant systems because the overhead caused by redundant components is considerable. The new design method consists of a special genetic algorithm that is tailored to the particular issues of fault-tolerant systems. The interface of the present tool ePADuGA (elitist and Pareto-based Approach to Design fault-tolerant systems using a Genetic Algorithm) allows for adaptation to various fields of application. The degree of fault tolerance is measured by the number of tolerated faults rather than traditional reliability metrics, because reliability numbers are mostly unknown during early design phases. The special features of the genetic algorithm comprise a graph-oriented representation of systems (which are the individuals during the evolutionary process), a simple yet expressive fault model, a very efficient procedure for fault-tolerance evaluation, and a Pareto-oriented fitness function. In a genetic algorithm generating thousands of individuals, a very fast evaluation of each individual is mandatory. For this purpose, state-space-oriented evaluation methods have been cut down to an extremely simple function which is still sufficient to assess the fault tolerance of individuals. An innovative aspect is also a multistart technique to find a Pareto solution set, which is independent of any parameters. In this paper, experimental results are presented showing the feasibility of the approach as well as the usefulness of the final fault-tolerant architectures, particularly in the field of mechatronic systems.

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