A New Method for Reconstructing Data on a Single Failure Node in the Distributed Storage System Based on the MSR Code
Algorithm 6
The optional topology construction method based on a hybrid genetic algorithm
1: Function (parameter initialization)
2: Initialize the population size parameter , maximum evolutionary generation , and cross variation probability ;
3: Function (population initialization)
4: Repeat Algorithm 1 times to get the initial population with the number of . Calculate the fitness value of each individual according to formula (9) and set .
5: Function (crossover operation)
6: Randomly select two individuals from the current population
7: if probability then perform Algorithm 2 to generate crossover descendants
8: else parental individuals directly join the crossover descendants
9: end if
10: Repeat the crossover descendants until the number of crossover descendants is equal to the , and the individual set of all these crossed individuals is denoted as a ;
11: Function (mutation operation)
12: From a random individual in the current population ,
13: if probability then Algorithm 3 is executed to generate mutation progeny
14: else parental individuals are directly added to cross progeny
15: end if
16: Repeat the mutation operation until the number of descendants of the mutation is equal , denoted as in the topology.
17: Function (local search)
18: Perform Algorithm 4 successively for each individual in set , perform a local search, and get three equally large subpopulations of ,, and .
19: Function (select operation)
20: Perform Algorithm 5 and set . Select individuals of as the next-generation population , and let ;
21: EndFunction
22: if the then the individual with the lowest fitness function value is the solution
