Multi-metaheuristic Optimization Algorithms for Effective Routing System
| dc.contributor.author | Hakeem Babalola Akande, Fatimoh Abidemi Taofeek-Ibrahim, Oluwakemi Christiana Abikoye, Taye Oladele Aro | |
| dc.date.accessioned | 2024-04-22T10:15:25Z | |
| dc.date.available | 2024-04-22T10:15:25Z | |
| dc.date.issued | 2020-09 | |
| dc.description.abstract | One of the predominant problems that require great attention in the packet-switch network is finding the optimal routing path for packets movement. The problem leads to an increase in the size of the network, thereby making routing of the network becomes more difficult due to traffic congestion, delay, and time at which packets are delivered over the network. Hence, there is a need to develop an effective routing algorithm that can reduce congestion and time of packet delivery when transferring data over network nodes. This paper applied multi-meta-heuristic optimization algorithms to develop an enhanced routing system by application of three combined natured inspired metaheuristic algorithms; Ant Colony Optimization (ACO), Bat Algorithm, and Tabu Search to reduce the routing problems. Experimental results showed that the developed multi-metaheuristic routing system performed efficiently with 0.002E14s of delay time against the shortest time, 70MB packet size passed through the highest path and 9.4E14 s average delay time against the packet size. | |
| dc.identifier.uri | https://www.allengineeringjournal.in/archives/2020/vol6/issue3 | |
| dc.identifier.uri | https://uilspace.unilorin.edu.ng/handle/123456789/12414 | |
| dc.language.iso | en | |
| dc.publisher | International Journal of Research in Advanced Engineering and Technology | |
| dc.title | Multi-metaheuristic Optimization Algorithms for Effective Routing System | |
| dc.type | Article |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Multi-Metaheuristic optimization algorithms for an effective routing system.pdf
- Size:
- 351.05 KB
- Format:
- Adobe Portable Document Format
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 1.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: