A new algorithm for wireless network nodes effectiveness
- https://doi.org/10.2991/isct-16.2016.2How to use a DOI?
- network node; long; autoregressive moving average model; linear fractional stable noise model
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/isct-16.2016.2 ID - Wang2016/12 ER -