Performance Evaluation of Optimization Algorithms for BGP Slow Convergence Problem
| dc.contributor.advisor | Yalemzewd Negash (PhD) | |
| dc.contributor.author | Mihret Gebre | |
| dc.date.accessioned | 2024-07-31T08:32:19Z | |
| dc.date.available | 2024-07-31T08:32:19Z | |
| dc.date.issued | 2022-06 | |
| dc.description.abstract | Border Gateway Protocol (BGP) is an inter-domain routing protocol that provides routing or reachability information inside or between different Autonomous Systems (AS). The existing inter-domain routing architecture has a major challenge due to slow convergence during network failures. The slow routing convergence time results in intermittent loss of connectivity, increased packet loss, and latency. The Minimum Route Advertisement Interval (MRAI) timer limits the number of messages propagated by BGP speakers. Convergence time can be characterized in terms of MRAI rounds. Thus, the optimum MRAI timer implementation plays a vital role in improving the convergence time of BGP. This thesis is conducted to evaluate and analyze the performance of optimization algorithms to determine an optimum value for the MRAI timer, which minimizes the convergence time without affecting the number of update messages. The dataset has been gathered from the network topology with different values of MRAI using Graphical Network Simulator-3 (GNS3). The Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is trained with the dataset to generate a model. Finally, three optimization algorithms such as Artificial Bee Colony (ABC), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are applied to the model to get the optimum value for the MRAI timer. The implementation has been performed using MATLAB. The results indicated that the PSO model outperforms the ABC and GA which reduces the running time and lowers the convergence rate required to complete the search process. The experimental results and analysis also show that in optimized BGP convergence time is improved by 55%, and packet loss is improved by 19% as compared to default BGP. | |
| dc.identifier.uri | https://etd.aau.edu.et/handle/123456789/3362 | |
| dc.language.iso | en_US | |
| dc.publisher | Addis Ababa University | |
| dc.subject | BGP | |
| dc.subject | Convergence time | |
| dc.subject | MRAI | |
| dc.subject | ANFIS | |
| dc.subject | Optimization Algorithm | |
| dc.subject | Performance | |
| dc.title | Performance Evaluation of Optimization Algorithms for BGP Slow Convergence Problem | |
| dc.type | Thesis |