Impact of Fuzzy Offset Time on Delay and Burst Loss Ratio for Optical Burst Switching Networks
Ibrahim Khider Eltahir1, Laila A. Wahab Abdullah Naji2, Hadeil Haydar Ahmed Elsheikh3
1Laila A. Wahab Abdullah Naji, Department of Communication Engineering, Faculty of Engineering and Architecture, Bahri University, Khartoum, Sudan.
2Dr. Ibrahim Khider Eltahir, Department of Electronics Engineering, College of Engineering, Sudan University of Science and Technology, Khartoum, Sudan.
3Hadeil Haydar Ahmed Elsheikh, Department of Electronics Engineering, College of Engineering, Sudan University, of Science and Technology, Khartoum Sudan.
Manuscript received on 30 January 2023 | Revised Manuscript received on 03 February 2023 | Manuscript Accepted on 15 February 2023 | Manuscript published on 28 February 2023 | PP: 52-60 | Volume-12 Issue-3, February 2023 | Retrieval Number: 100.1/ijeat.C40260212323 | DOI: 10.35940/ijeat.C4026.0212323
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Optical burst switching (OBS) is an optical switching technology; it uses an optical fiber’s high bandwidth potential to transfer huge amounts of data in the form of huge packets, which are more commonly referred to as bursts. High burst loss brought on by numerous burst contentions is a significant problem in OBS. An intelligent fuzzy offset time algorithm (FOT) algorithm is suggested to overcome this problem. This study proposed Intelligent Fuzzy Offset Time (FOT) algorithms that adjust offset time (OT) in accordance with network and traffic conditions. The fuzzy input for FOT is made up of three parameters: burst size, distance, and time that burst spent in queuing. The suggested algorithm is assessed versus the Intelligent OT algorithms using the Five defuzzification techniques (Centroid (CM00), Bisector (BM04), largest of maximum (LM02), smallest of maximum (SM03), and mean of maximum (MM01) when Maximum (M) accumulation technique is used, when using Algebraic Sum (S) aggregation methods (Centroid (CS00), Bisector (BS04), largest of maximum (LS02), smallest of maximum (SS03), and mean of maximum (MS01). Simulation results have shown that FOT LM02, FOT LS02, FOT SM03 and FOT LS02 have effects on reducing BLR (burst loss ratio) and E2E (End-2-End) delayed respectively when compared to other defuzzification techniques algorithms. FOT LM02 and FOT SM03 can be used to intelligently adjust the offset parameter using the incoming traffic load and the three parameters.
Keywords: FOT, OBS Networks, Fuzzy Logic, average burst E2E delay, BLR
Scope of the Article: Fuzzy Logic