Application of Genetic Algorithm on Quality Graded Networks for Intelligent Routing

TL;DR

This paper introduces a novel two-level node selection method using genetic algorithms for efficient network routing, leveraging node intelligence and local knowledge to improve pathfinding speed.

Contribution

It proposes a grade-based two-level node selection combined with genetic algorithms, enhancing routing efficiency in intelligent networks.

Findings

Significant reduction in routing time compared to non-graded networks

Effective route selection through grading and genetic algorithms

Validated on various network topologies

Abstract

In the past decade, significant research has been carried out for realizing intelligent network routing using advertisement, position and near-optimum node selection schemes. In this paper, a grade-based two-level node selection method along with genetic algorithm (GA) is proposed for realizing an efficient routing scheme. This method assumes that the nodes are intelligent and that there exists a knowledge base about the environment in their local memory. There are two levels for approaching the effective route selection process through grading. At the first level, grade-based selection is applied and at the second level, the optimum path is explored using GA. The simulation has been carried out on different topological structures, and a significant reduction in time is achieved for determining the optimal path through this method compared to the non-graded networks.