A Genetic Algorithm for Optimal Path Routing in Computer Networks
 |
International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2019 by IJETT Journal | ||
| Volume-67 Issue-12 |
||
| Year of Publication : 2019 | ||
| Authors : Sowmya KS, N Raksha Rao, Disha P Khanted |
||
| DOI : 10.14445/22315381/IJETT-V67I12P213 |
Citation
MLA Style: Sowmya KS, N Raksha Rao, Disha P Khanted "A Genetic Algorithm for Optimal Path Routing in Computer Networks" International Journal of Engineering Trends and Technology 67.12 (2019):83-87.
APA Style:Sowmya KS, N Raksha Rao, Disha P Khanted. A Genetic Algorithm for Optimal Path Routing in Computer Networks International Journal of Engineering Trends and Technology, 67(12),83-87.
Abstract
Optimal path routing in computer networks refers to the process of finding paths through a network that have a minimum cost. A network mainly consists of nodes and edges, with each edge having a specific weight. The optimal path may be defined in terms of various factors such as throughput, propagation delay, latency and bandwidth, which can be represented as weights of the edges in the network, as a combination of the aforementioned factors. The simulation and algorithm developed achieves convergence at a high rate for large networks. The computer simulation is not dependent on the source and destination nodes. This paper provides a genetic algorithm (GA) approach to arrive at the most optimal path in a large network of computer network nodes.
Reference
[1] Gihan Nagib and Wahied G.Ali, Network Routing Protocol using Genetic Algorithms, International Journal of Electrical & Computer Sciences IJECS-IJENS Vol:10 No:02(references)
[2] Yong Deng, Yang Liu and Deyun Zhou, School of Electronics and 1)Information, Northwestern Polytechnical University, Xian, Shaanxi 710071, China 2)School of Computer and Information Science, Southwest University, Chongqing 400715, China- An IMproved Genetic Algorithm with Initial Population Strategy for Symmetric TSP
[3] Cooper, Jason. “Improving performance of genetic algorithms by using novel fitness functions.” (2006).
[4] Y. Qiu, F. Liu and X. Huang, "Network Optimization based on Genetic Algorithm and Estimation of Distribution Algorithm," 2008 International Conference on Computer Science and Software Engineering, Hubei, 2008, pp. 1058- 1061. doi: 10.1109/CSSE.2008.1511
[5] Chang Wook Ahn and R. S. Ramakrishna, "A genetic algorithm for shortest path routing problem and the sizing of populations," in IEEE Transactions on Evolutionary Computation, vol. 6, no. 6, pp. 566-579, Dec. 2002. doi: 10.1109/TEVC.2002.804323
[6] Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators P. LARRANAGA, C.M.H. KUIJPERS, R.H. MURGA, I. INZA and ˜ S. DIZDAREVIC Dept. of Computer Science and Artificial Intelligence, University of the Basque Country, P.O. Box 649, E-20080 San Sebastian, The Basque Country, Spain
Keywords
genetic algorithms, optimization, metaheuristic, optimization, chromosome, gene, mutation, crossover, routing problem, multi-hop, networks