Maximizing Fault Tolerance and Minimizing Delay in Virtual Network Embedding using NSGA-II
Angel Bansal, Omprakash Kaiwartya, Ravindra Kumar Singh, Shiv Prakash · 2015
Due to growing interest in network cost optimization through resource sharing, virtual network embedding has significantly attracted the attention of researchers. Recently, various virtual network embedding algorithms have been suggested. The mapping of these algorithms is not reliable due to the absence of fault tolerance capability. Therefore, this paper proposes a technique for maximizing fault tolerance and minimizing delay in Virtual Network Embedding (VNE) using Non-dominated Sorting Genetic Algorithm (NSGA-II). The multi-objective optimization problem is mathematically formulated. An adapted NSGA-II is proposed for solving the optimization problem. The major components of adapted NSGA-II are representation of chromosome, computation of fault tolerance and delay, sorting using non-domination, and crossover and mutation operation. Two novel mathematical functions for computing fault tolerance and delay are developed. The analysis of simulation results clearly indicates that the proposed technique effectively optimizes both the considered objectives in VNE.