A new algorithm for wireless network nodes effectiveness

DOI

10.2991/isct-16.2016.2How to use a DOI?

Keywords

network node; long; autoregressive moving average model; linear fractional stable noise model

Abstract

According to the network congestion caused by node failure, presents a measuring node effectiveness evaluation index. The index for the long correlation properties of the actual flow, respectively using the autoregressive moving average (Auto-Regressive and Moving Average, ARAMA) model and linear fractional stable noise (Stable Noise Linear Fractiona, SNLF) model prediction method of traffic arrival, and through simulation experiments to study the relationship between the index and the average arrival rate, between the results show that, when the average arrival rate is lower the ARAMA model performance is better, and better performance of SNLF model.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - XiangZhong Wang
AU  - Moyi Duan
PY  - 2016/12
DA  - 2016/12
TI  - A new algorithm for wireless network nodes effectiveness
BT  - Proceedings of the 4th International Conference on Information Systems and Computing Technology
PB  - Atlantis Press
SP  - 7
EP  - 12
SN  - 2352-538X
UR  - https://doi.org/10.2991/isct-16.2016.2
DO  - 10.2991/isct-16.2016.2
ID  - Wang2016/12
ER  -