Control and visualization system for managed self-organization network

Authors:
Shohei Kamamura;Yuki Koizumi;Takashi Miyamura;Shin'ichi Arakawa;Kohei Shiomoto;Masayuki Murata
Affiliations:
NTT Corporation, Tokyo, Japan;Osaka University, Suita, Osaka, Japan;NTT Corporation, Tokyo, Japan;Osaka University, Suita, Osaka, Japan;NTT Corporation, Tokyo, Japan;Osaka University, Suita, Osaka, Japan
Venue:
Proceedings of the 7th International Conference on Network and Services Management
Year:
2011

Citing 4
Cited 0

Visual analysis of network centralities

APVis '06 Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60
Robust virtual network topology control based on attractor selection

ONDM'09 Proceedings of the 13th international conference on Optical Network Design and Modeling
An experimental comparison of fast algorithms for drawing general large graphs

GD'05 Proceedings of the 13th international conference on Graph Drawing
Distributed virtual network topology control mechanism in GMPLS-based multiregion networks

IEEE Journal on Selected Areas in Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose the managed self-organizing network concept considering the unexpected network changes caused by the future applications, and implement the control and visualization system for it. In the managed self-organizing network, multiple virtual networks are accommodated on a single optical infrastructure. Each virtual network is controlled based on self-organizing mechanism by attractor selection algorithm that models behavior where living organisms adapt to unknown changes in their surrounding environments. On the other hand, the physical resource management server dynamically manages the resource allocation for each virtual network to optimize the utilization of total network resources. Our implemented system efficiently visualizes the behavior of managed self-organizing network with time variability, and network filtering and clustering functions are implemented for visualization of large and multiple virtual networks.