Proceedings of the 2nd International Conference on Computer Application and System Modeling 2012
DOI: 10.2991/iccasm.2012.34
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ARIMA Prediction Model-based Cluster Algorithm in Ad Hoc Networks

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Cited by 3 publications
(7 citation statements)
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“…The ARIMA (p, d, q) model incorporates a collection of models, such as autoregressive model AR (p), moving average model MA (q), autoregressive moving average model ARMA (p, q), and nonstationary integrated autoregressive moving average model ARIMA (p, d, q) with “d” time. This work exploits the use of ARIMA (p, d, q) model with the nonstationary sequences of time series, where “d” as the smoother time difference of node speed values . The following subsections present its aptness to the MANETs in the mobility prediction scenario.…”
Section: Proposed Speed Prediction Methodologymentioning
confidence: 99%
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“…The ARIMA (p, d, q) model incorporates a collection of models, such as autoregressive model AR (p), moving average model MA (q), autoregressive moving average model ARMA (p, q), and nonstationary integrated autoregressive moving average model ARIMA (p, d, q) with “d” time. This work exploits the use of ARIMA (p, d, q) model with the nonstationary sequences of time series, where “d” as the smoother time difference of node speed values . The following subsections present its aptness to the MANETs in the mobility prediction scenario.…”
Section: Proposed Speed Prediction Methodologymentioning
confidence: 99%
“…This part of the paper presents various existing research works dealing with the future resources of the nodes. There are few existing models for predicting the node mobility, path length, reliability, delay, and energy of the nodes . As per the paper, the prediction of mobility of the node provides the effective routing in MANETs.…”
Section: Related Workmentioning
confidence: 99%
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“…discovering the shortest path among nodes by distance and delay [3][4][5][6][7][8][9][10]. In such shortest paths, the possibility of path breakup is higher; it can occur quickly because of node's mobility speed.…”
Section: Fmpm: Futuristic Mobility Prediction Model For Mobile Adhoc mentioning
confidence: 99%
“…This works exploit the use ARIMA (p, d, q) model with the non-stationary sequences of a time series; where d is the smoother time difference of node speed values. Its aptness for MANET presented in the following subsections [6,7].…”
Section: Proposed Arima Modelmentioning
confidence: 99%