ARIMA Prediction Model-based Cluster Algorithm in Ad Hoc Networks

DOI

10.2991/iccasm.2012.34How to use a DOI?

Keywords

Ad Hoc network, ARIMA, Clustering algorithm, CBRP, Prediction

Abstract

The paper introduces prediction mechanism in weighted clustering algorithm (WCA). Time series model (ARIMA) is embedded into the algorithm during routing maintance to predict the network node location. Combining with location information of nodes provided by GPS systems, the algorithm uses ARIMA to predict position of nodes at next time interval. So, it can calculate aggregate holding time of the nodes. Then, compare the predicted aggregate holding time of next moment with time warning threshold. If cluster structure is predicted unstable, recovery process will be activated before the link fails, and it will search appropriate routing in order to avoid frequent failures of network links. In this way, the influence to the routing protocols brought by the dynamic changes of network topology can be reduced. The simulation results show that, compared with LOWID and RLWCA not joined the forecasting mechanism, the proposed algorithm can dramatically improve the network packet delivery rate, reduce the network normalized expenses and the number of routing interruptions significantly, and improve network performance.

Copyright

© 2012, 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  - Yingyu Cao
AU  - Ting Cao
AU  - Huang Ye
AU  - Yang Yan
AU  - Jiafu Chu
PY  - 2012/08
DA  - 2012/08
TI  - ARIMA Prediction Model-based Cluster Algorithm in Ad Hoc Networks
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 132
EP  - 136
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.34
DO  - 10.2991/iccasm.2012.34
ID  - Cao2012/08
ER  -