hrcak mascot   Srce   HID

Acta graphica : znanstveni časopis za tiskarstvo i grafičke komunikacije, Vol. 29 No. 2, 2018.

Izvorni znanstveni članak
https://doi.org/10.25027/agj2017.28.v29i2.136

FMPM: Futuristic Mobility Prediction Model for Mobile Adhoc Networks Using Auto-Regressive Integrated Moving Average

Theerthagiri Prasannavenkatesan   ORCID icon orcid.org/0000-0003-3420-598X ; Adhiyamaan College of Engineering Hosur Anna University Chennai, India
T Menakadevi ; Adhiyamaan College of Engineering Hosur Anna University Chennai, India

Puni tekst: engleski, pdf (1 MB) str. 7-17 preuzimanja: 35* citiraj
APA 6th Edition
Prasannavenkatesan, T. i Menakadevi, T. (2018). FMPM: Futuristic Mobility Prediction Model for Mobile Adhoc Networks Using Auto-Regressive Integrated Moving Average. Acta graphica, 29 (2), 7-17. https://doi.org/10.25027/agj2017.28.v29i2.136
MLA 8th Edition
Prasannavenkatesan, Theerthagiri i T Menakadevi. "FMPM: Futuristic Mobility Prediction Model for Mobile Adhoc Networks Using Auto-Regressive Integrated Moving Average." Acta graphica, vol. 29, br. 2, 2018, str. 7-17. https://doi.org/10.25027/agj2017.28.v29i2.136. Citirano 24.05.2019.
Chicago 17th Edition
Prasannavenkatesan, Theerthagiri i T Menakadevi. "FMPM: Futuristic Mobility Prediction Model for Mobile Adhoc Networks Using Auto-Regressive Integrated Moving Average." Acta graphica 29, br. 2 (2018): 7-17. https://doi.org/10.25027/agj2017.28.v29i2.136
Harvard
Prasannavenkatesan, T., i Menakadevi, T. (2018). 'FMPM: Futuristic Mobility Prediction Model for Mobile Adhoc Networks Using Auto-Regressive Integrated Moving Average', Acta graphica, 29(2), str. 7-17. doi: https://doi.org/10.25027/agj2017.28.v29i2.136
Vancouver
Prasannavenkatesan T, Menakadevi T. FMPM: Futuristic Mobility Prediction Model for Mobile Adhoc Networks Using Auto-Regressive Integrated Moving Average. Acta graphica [Internet]. 2018 [pristupljeno 24.05.2019.];29(2):7-17. doi: https://doi.org/10.25027/agj2017.28.v29i2.136
IEEE
T. Prasannavenkatesan i T. Menakadevi, "FMPM: Futuristic Mobility Prediction Model for Mobile Adhoc Networks Using Auto-Regressive Integrated Moving Average", Acta graphica, vol.29, br. 2, str. 7-17, 2018. [Online]. doi: https://doi.org/10.25027/agj2017.28.v29i2.136

Sažetak
The mobility of the node plays a crucial role in the route discovery process for Mobile Ad hoc networks (MANET). The high-speed node affects the routing process by packet relaying, packet delivery. This paper proposes a mobility prediction model FMPM using Auto-Regressive Integrated Moving Average (ARIMA) method to estimate the futuristic speed values of the nodes in MANET. It uses the autocorrelations of previous data by time series forecasting approach. The ARIMA model applied to mobile nodes for predicting its future speeds in the network. This mobility prediction supports the route discovery process to select the moderate mobility nodes for the reliable routing in the network. The nodes are trained by ARIMA model using neural network time-series tool of Matlab. Roughly, it trains each node with ten iterations. Simulation results show that the forecasted values almost match with the simulated node speed values. Performance analysis of the predicted mobility values exhibits the improved results compared to existing works on performance metrics such as mean square error, covariance, and computation overhead. The proposed FMPM produces more perfection in the speed prediction of a mobile node with a maximum of 80-100 % throughout the time series and has the lowest error values as 0.1085. But, the neural based prediction has the lowest MSE as 0.852. Therefore, the ARIMA prediction has approximately 0.75 reduced error values.

Ključne riječi
ARIMA; Mobility prediction; MANET; Auto-regression; Random waypoint model

Hrčak ID: 215685

URI
https://hrcak.srce.hr/215685

Posjeta: 75 *