Neural network based near-optimal routing algorithm

Chang Wook Ahn, R. S. Ramakrishna, In Chan Choi, Chung Gu Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


Presents a neural network based near-optimal routing algorithm. It employs a modified Hopfield neural network (MHNN) as a means to solve the shortest path problem. It also guarantees a speedy computation that is appropriate to multi-hop radio networks. The MHNN uses every piece of information that is available at the peripheral neurons in addition to the highly correlated information that is available at the local neuron. Consequently, every neuron converges speedily and optimally to a stable state. The convergence is faster than what is usually found in algorithms that employ conventional Hopfield neural networks. Computer simulations support the indicated claims. The results are relatively independent of network topology for almost all source-destination pairs.

Original languageEnglish
Title of host publicationICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9810475241, 9789810475246
Publication statusPublished - 2002
Event9th International Conference on Neural Information Processing, ICONIP 2002 - Singapore, Singapore
Duration: 2002 Nov 182002 Nov 22


Other9th International Conference on Neural Information Processing, ICONIP 2002

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing


Dive into the research topics of 'Neural network based near-optimal routing algorithm'. Together they form a unique fingerprint.

Cite this