Hybrid Rough Genetic algorithm for Selecting Optimal Routes

Routing protocols in most networks use the length of paths or the minimum-hops thatcan be achieved, as the routing metric. This led to the motivation to propose a new algorithm that satisfies multiple constraints for finding a feasible path and apply GA to reduce the time taken to find a feasible path. To achieve this, The Rough sets Theory (RST) is applied to reduce the Performance metrics successfully and decide the most effective ones. ROSETTA software is applied to deduce a QoS metric as a substitution for all routing metrics. This metric is used to select the optimal routes. The results confirm that the proposed metric is adequately suit for selecting the proper routes. Then, Genetic Algorithms (GA) is used to select the optimal routes with new coding and new operators. The proposed Quality of Service Routing Genetic Algorithm (QoSRGA) has been tested on a subnet case study.