Novel Low Delay Marking Algorithm for Self-organizing Cellular Neural Networks Based on Topology Space Analysis

Author

Zhong, Yingji ; Yuan, Dongfeng

Author_Institution

Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan

Volume

3

fYear

2005

Firstpage

1895

Lastpage

1899

Abstract

This paper analyzed two topologies of self-organizing cellular neural networks based on a hybrid mode that combines IEEE 802.11g and 802.11a in different dimensions, and investigated the relationship between the attributes of the networks and the topology spaces. Then a novel scheme for the low delay marking (LDM) algorithm, called modified-low delay marking (M-LDM), is proposed. Performance analysis of the connectivity and other properties was conducted and shown that the proposed modification to the LDM algorithm can optimize the round trip time (RTT) and make the network more effective and more stable in the case of the special scenarios that were investigated, by modifying the patterns for neurons, optimizing the window size and adjusting the marking probability

Keywords

IEEE standards; cellular neural nets; delays; self-organising feature maps; telecommunication network topology; transport protocols; wireless LAN; IEEE 802.11a; IEEE 802.11g; modified low delay marking algorithm; round trip time; self-organizing cellular neural network; topology space analysis; Algorithm design and analysis; Base stations; Cellular neural networks; Delay; Information analysis; Information science; Network topology; Neurons; Performance analysis; Transport protocols; M-LDM; dimensionality analysis; self-organizing cellular neural networks; topology space;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9422-4

Type

conf

DOI

10.1109/ICNNB.2005.1614995

Filename

1614995