Energy Efficient Performance Evaluation of XG-PON for Sustainable Green Communication Infrastructure

Zin, A. M.; Idrus, Sevia Mahdaliza; Ismail, N. A.; Ramli, Arnidza; Butt, Rizwan Aslam

doi:10.23919/piers.2018.8598106

Cited by 3 publications

(6 citation statements)

References 7 publications

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“…In reducing the energy consumption in PON, sleep mode, adaptive link rate (ALR), and hybrid mechanisms were proposed in [22]. Among these methods, sleep mode is widely accepted technique due to its simple operation, only turning off various unused components in ONU when there is no traffic on the link [1]. As a result, the determination of ONU sleep/asleep duration is extensively researched.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For a queueing system, the sleep/vacation interval depends on the number of frames and the frame arrival rate. Thus, our analysis firstly performs a simulation framework in the OMNeT++ software to monitor the frame arrivals at the ONU within 1 sec timeframe [1]. Assuming fixed reservation interval in XG-PON because all packet headers are transmitted within the upstream and downstream payload; and vacation intervals are varied, thus ( 1) and ( 2) can be used to determine the TAS for XG-PON [6].…”

Section: Theoretical Analysismentioning

confidence: 99%

“…However, none of the related work using ML considers the XG-PON practical network environment parameters. Thus, we continue the CSM improvement scheme by utilizing an XG-PON simulation test-bed in [1]. We employ the ANN to find the optimal TAS for energy savings because ANN can learn how to react to the network inputs through the learning process [32], [33].…”

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confidence: 99%

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Determination of optimized sleep interval for 10 gigabit-passive optical network using learning intelligence

Zin

Idrus

Ismail

et al. 2022

IJECE

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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.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Theoretical Analysismentioning

confidence: 99%

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Determination of optimized sleep interval for 10 gigabit-passive optical network using learning intelligence

Zin

Idrus

Ismail

et al. 2022

IJECE

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“…Assuming a continued annual relative growth ranging from 5.6 to 6.9 %, ICT's relative contribution would exceed 14 % of the 2016-level worldwide global greenhouse gas emissions (GHGE) by 2040 [11]. A present phenomenon is energy efficiency during sleep cycles and bandwidth allocation for ONUs in Institute of Electrical and Electronics Engineers (IEEE) or International Telecommunication Union (ITU) PONs [12][13][14].…”

Section: Related Workmentioning

confidence: 99%

Efficiency Tests of DBA Algorithms in XG-PON

et al. 2019

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Sophisticated dynamic bandwidth allocation (DBA) algorithms can dramatically improve or worsen throughput and delay in whole networks. It is very important to choose the right DBA algorithm. Our work tests static assignment and three DBA algorithms, namely GigaPON Access Network DBA, Hybrid Reporting Allocation, and modified Max–Min Fair. All tests were made on our simulator of ten-gigabit passive optical network DBA specially developed for testing DBA algorithms. The tests verify delay of each optical network unit and amount of waste with bandwidth. This paper describes how the used DBA algorithms work and the processes involved in DBA algorithms.

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“…On the contrary, the elements of the passive network do not require any power supply and, thanks to their low purchase price, are used primarily as a so-called last mile solution to connect end users. They are also common in networks combining metallic and optical lines, which are created by the gradual replacement of metallic lines [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

MongoDB Database as Storage for GPON Frames

Holík

Horváth

Oujezský

et al. 2020

Sensors

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This work is focused on creating an open-source software-based solution for monitoring traffic transmitted through gigabit passive optical network. In this case, the data are captured by the field-programmable gate array (FPGA) card and reassembled using parsing software from a passive optical network built on the International Telecommunication Unit telecommunication section (ITU-T) G.984 gigabit-capable passive optical network GPON recommendation. Then, the captured frames are converted by suitable software into GPON frames, which will be further processed for analysis. Due to the high transfer rate of GPON recommendations, the work describes the issue of writing to the Mongo database system. In order to achieve the best possible results and minimal loss of transmitted frames, a series of tests were performed. The proposed test scenarios are based on different database writing approaches and are implemented in the Python and C# programming languages. Based on our results, it has been shown that the high processing speed is too high for Python processing. Critical operations must be implemented in the C# programming language. Due to rapid application development, Python can only be used for noncritical time-consuming data processing operations.

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Energy Efficient Performance Evaluation of XG-PON for Sustainable Green Communication Infrastructure

Cited by 3 publications

References 7 publications

Determination of optimized sleep interval for 10 gigabit-passive optical network using learning intelligence

Determination of optimized sleep interval for 10 gigabit-passive optical network using learning intelligence

Efficiency Tests of DBA Algorithms in XG-PON

MongoDB Database as Storage for GPON Frames

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