Vol. 18 No. 4 (2016)
Original articles

Determination of optimum parameters in the implementation of an antnet routing algorithm for improving data transmission

Jose Emmanuel Cruz de la Cruz
National University of the Altiplano Puno Peru
Eudes Rigoberto Apaza Estaño
National University of the Altiplano Puno Peru
Luis Enrique Baca Wiesse
National University of the Altiplano Puno Peru

Published 2016-12-20

Keywords

  • ant algorithm,
  • ant colony algorithm,
  • routing protocols,
  • routing simulation

How to Cite

Cruz de la Cruz, J. E. ., Apaza Estaño, E. R., & Baca Wiesse, L. E. . (2016). Determination of optimum parameters in the implementation of an antnet routing algorithm for improving data transmission. Revista De Investigaciones Altoandinas - Journal of High Andean Research, 18(4), 439-448. https://doi.org/10.18271/ria.2016.236

Abstract

The main objective on this research is the development of finding the optimal parameters for a routing algorithm for network routers based on the ant algorithm described as AntNet. The optimum parameters for this type of algorithm improve a more efficient alternative to those given by the RIP, EIGRP and OSPF routing protocols, to be applied in a data network. This shall be tested in two networks and routers defined, taking the same characteristics for the three groups: RIP, OSPF and by the result provided by the genetic algorithm implemented using a static network. The system recognizes the best path between networks of routers, based on the principle of AntNet networks or networks of ants, which are the best way from exploring almost all roads, using estimergia to go there and make optimal. MatLab was used to detect the best way. Later this road was implemented in a real network data, sending a test file in compressed format. Its efficiency compared with RIP and OSPF protocols are checked. For validation of the network, compressed files, which were sent for ten consecutive times and the results were taken using a server and a network connected by the given client used. The server and client are implemented in Linux, to measure the arrival time of the file and thus the data transfer rate. It was found that the routing algorithm, under the optimal parameters found, provided a reliable alternative for routing data networks.

References

  1. Alexandrovich, D. & Yurievich, I. (2016). Paired transitions algorithm of communication links in computer networks based on subnet routing method. IEEE Xplore. Visited 10 August 2016 on http://ieeexplore.ieee.org/document/7525755/
  2. Cruz, J. (2014). Diseño e implementacion de un algoritmo de encaminamiento para una red de routers basado en algoritmo antnet para mejorar la transmision en redes de datos. Disertación doctoral, Facultad de Producción y Servicios, Universidad Nacional de San Agustín. Arequipa, Perú.
  3. Lammle, T. (2014). CCNA/CCENT IOS Commands Survival Guide: Exams 100-101, 200-101, and 200-120 2nd Edition. United States of America, Sybex.
  4. Lammle, T. (2013). CCNA Routing and Switching Study Guide: Exams 100-101, 200-101, and 200-120 1st Edition. United States of America, Sybex.
  5. Leonov, A. (2016). Application of bee colony algorithm for FANET routing. IEEE Xplore. Visited 13 August 2016 on http://ieeexplore.ieee.org/document/7538709/
  6. Luo, Z.; Lu, L.; Xie, J. & He, J. (2016). An ant colony optimization-based trustful routing algorithm for wireless sensor networks. IEEE Xplore. Visited 1 July 2016 on http://ieeexplore.ieee.org/document/7490933/
  7. Moriya, H. & Miura, Y. (2016). Performance improvement method of the adaptive routing algorithm for 2-dimensional torus network. IEEE Xplore. Visited 1 August 2016 on http://ieeexplore.ieee.org/document/7521019/
  8. Sachdev, A.; Mehta, K. & Malik, L. (2016). Design of Protocol For Cluster based routing in VANET Using Fire Fly Algorithm. IEEE Xplore, Visited 19 September 2016 on http://ieeexplore.ieee.org/document/7569301/
  9. Sadrosadati, M.; Bashizade, R.; Roozkhosh, S.; Shafiee, A. & Sarbazi-Azad, H. (2016). A Method to Improve Adaptivity of Odd-Even Routing Algorithm in Mesh NoCs. IEEE Xplore, Visited 29 April 2016 on http://ieeexplore.ieee.org/document/7445418/
  10. Umale, M. & Markande S. D. (2016). Network and Energy efficient routing algorithm on the target tracking in Wireless Sensor. IEEE Xplore. Visited 1 July 2016 on http://ieeexplore.ieee.org/document/7489373/
  11. Wang, G.; Shao M.; Li, R.; Ma, Y. & Wang, B. (2016). Spray and Wait routing algorithm based on Transfer Utility of Node in DTN. IEEE Xplore. Visited 1 July 2016 on http://ieeexplore.ieee.org/document/7489883/
  12. Wang, L.; Wang, X. & Mak T. (2015). Adaptive Routing Algorithms for Lifetime Reliability Optimization in Network-on-Chip. IEEE Xplore, Visited 9 April 2016 on http://ieeexplore.ieee.org/document/7349176/authors
  13. Wei, Y. & Wang, J. (2016). A DTN Routing Algorithm Based on Traffic Prediction. IEEE Xplore. Visited 7 August 2016 on http://ieeexplore.ieee.org/document/7528887/
  14. Xu, Z.; Zhu, F.; Fu, Y.; Liu, Q. & You, S. (2016). A dyna-Q based multi-path load-balancing routing algorithm in wireless sensor networks. IEEE Xplore. Visited 1 July 2016 http://ieeexplore.ieee.org/document/7461455/
  15. Zhihui, H. (2016). Research on WSN Routing Algorithm Based on Energy Efficiency. IEEE Xplore. Visited 1 July 2016 on http://ieeexplore.ieee.org/document/7462714/