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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Arnidza Ramli
Universiti Teknologi Malaysia
Computer Science & IT Electrical & Electronics Engineering

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Determination of optimized sleep interval for 10 gigabit-passive optical network using learning intelligence Affida M. Zin; Sevia Mahdaliza Idrus; Nur Asfahani Ismail; Arnidza Ramli; Fadila Mohd Atan
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2663-2671

Abstract

The overall aim of this project is to investigate the application of a machine learning method in finding the optimized length of asleep time interval (TAS) in a cyclic sleep mechanism (CSM). Since past decade, the implementations of CSM in the optical network unit (ONU) to reduce the energy consumption in 10 gigabit-passive optical network (XG-PON) were extensively researched. However, the newest era sees the emergence of various network traffic with stringent demands that require further improvements on the TAS selection. Since conventional methods utilize complex algorithm, this paper presents the employment of an artificial neural network (ANN) to facilitate ONU to determine the optimized TAS values using learning from past experiences. Prior to simulation, theoretical analysis was done using the M/G/1 queueing system. The ANN was than trained and tested for the XG-PON network for optimal TAS decisions. Results have shown that towards higher network load, a decreasing TAS trend was observed from both methods. A wider TAS range was recorded from the ANN network as compared to the theoretical values. Therefore, these findings will benefit the network operators to have a flexibility measure in determining the optimal TAS values at current network conditions.
Self-configuration and self-optimization process with taguchi method in hybrid optical wireless network Adam Wong Yoon Khang; Arnidza Ramli; Shamsul J. Elias; J. Pusppanathan; Jamil Abedalrahim Jamil Alsayaydeh; Fatin Hamimi Mustafa; Win Adiyansyah Indra; Johar Akbar Mohamat Gani
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp870-878

Abstract

In this paper, an alternative improvement is proposed which is the adaptive wireless access networks-based optical backhaul convergence that will greatly promote to use the existing resource of MANET (mobile ad hoc network). However, these characteristics itself acts as a drawback to the MANET applications such as the random distribution of nodes and continuously changing topology. MiNiTab statistical software was used to model the effect of the parameter variation to predict the field quality through the design of experiments while OMNeT++ network simulation was created to visualize the effect of QoS performance study in response with varying speed scenario. The result shows that the proposed ESCMDR scheme can obtain robustness and outperformed compared to the non-Taguchi previous study when it is used in random waypoint mobility model in any speed of sources. The work is based on packet delivery ratio (PDR) and packet loss Probability (PLP) metric under the varying speed scenario. It results in better QoS network PDR of 28.9% improvement, with 83.56% improvement on average PLP. The paper shows that the MANET QoS performance constrained can be addressed with the self-configured data rate of integrated optimization with taguchi method on AODV-UU (Adhoc On demand distance vector-uppsala university) routing technique.
Co-Authors Adam Wong Yoon Khang Affida M. Zin Fadila Mohd Atan Fatin Hamimi Mustafa J. Pusppanathan Jamil Abedalrahim Jamil Alsayaydeh Johar Akbar Mohamat Gani Nur Asfahani Ismail Sevia Mahdaliza Idrus Shamsul J. Elias Win Adiyansyah Indra