Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks
The Quality of Service (QoS) requirements for 5G are very strict in terms of latency of Fifth Generation (5G) traffic. 5G fronthaul networks between the baseband unit and remote radio heads are planned to use Next Generation - Passive Optical Networks 2 (NG-PON2) to carry their traffic. However, the...
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| Format: | Article |
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Elsevier Inc
2023
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| _version_ | 1811132269441581056 |
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| author | AlSheibi, Abdullah Zaini Mohd. Supa’at, Abu Sahmah |
| author_facet | AlSheibi, Abdullah Zaini Mohd. Supa’at, Abu Sahmah |
| author_sort | AlSheibi, Abdullah Zaini |
| collection | ePrints |
| description | The Quality of Service (QoS) requirements for 5G are very strict in terms of latency of Fifth Generation (5G) traffic. 5G fronthaul networks between the baseband unit and remote radio heads are planned to use Next Generation - Passive Optical Networks 2 (NG-PON2) to carry their traffic. However, these Time Wavelength Division Multiplexing (TWDM) PON based networks also provide service to other traffic such as residential and corporate users. Therefore, it is crucial to provide QoS guarantees to 5G traffic. The main issue includes allocating transmission over multiple wavelengths while maintaining QoS. Although using all the available wavelengths all the time may seem to be the simple solution, each active wavelength increases the cost of operation. To solve these issues, this paper proposes a technique using fuzzy logic to dynamically allocate wavelength and bandwidth for 5G fronthaul networks. Two types of traffic, i.e., 5G traffic and normal traffic are considered while the problem of Dynamic Wavelength and Bandwidth Allocation (DWBA) is formulated as a queueing theory problem using penalties and a cost function. Penalties are assigned for waiting packets as well as each active wavelength. Then, modeling the number of active wavelengths, the number of packets in the system, the total cost, and the traffic intensity as input fuzzy variables while modeling the change in the number of active wavelengths as the fuzzy output variable. The Mamdani implication is used for the fuzzy inference engine and the height method is used for defuzzification of the output variable. Simulations in MATLAB show that the proposed technique can maintain the latency of 5G traffic lower than the defined threshold while also significantly reducing the number of active wavelengths. A comparison with the existing state-of-the-art techniques shows that the proposed technique results in an improvement of at least 46% and 29% in terms of the average number of active wavelengths and the average latency for 5G traffic, respectively. |
| first_indexed | 2024-09-24T00:00:38Z |
| format | Article |
| id | utm.eprints-106098 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-09-24T00:00:38Z |
| publishDate | 2023 |
| publisher | Elsevier Inc |
| record_format | dspace |
| spelling | utm.eprints-1060982024-06-06T08:27:55Z http://eprints.utm.my/106098/ Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks AlSheibi, Abdullah Zaini Mohd. Supa’at, Abu Sahmah TK Electrical engineering. Electronics Nuclear engineering The Quality of Service (QoS) requirements for 5G are very strict in terms of latency of Fifth Generation (5G) traffic. 5G fronthaul networks between the baseband unit and remote radio heads are planned to use Next Generation - Passive Optical Networks 2 (NG-PON2) to carry their traffic. However, these Time Wavelength Division Multiplexing (TWDM) PON based networks also provide service to other traffic such as residential and corporate users. Therefore, it is crucial to provide QoS guarantees to 5G traffic. The main issue includes allocating transmission over multiple wavelengths while maintaining QoS. Although using all the available wavelengths all the time may seem to be the simple solution, each active wavelength increases the cost of operation. To solve these issues, this paper proposes a technique using fuzzy logic to dynamically allocate wavelength and bandwidth for 5G fronthaul networks. Two types of traffic, i.e., 5G traffic and normal traffic are considered while the problem of Dynamic Wavelength and Bandwidth Allocation (DWBA) is formulated as a queueing theory problem using penalties and a cost function. Penalties are assigned for waiting packets as well as each active wavelength. Then, modeling the number of active wavelengths, the number of packets in the system, the total cost, and the traffic intensity as input fuzzy variables while modeling the change in the number of active wavelengths as the fuzzy output variable. The Mamdani implication is used for the fuzzy inference engine and the height method is used for defuzzification of the output variable. Simulations in MATLAB show that the proposed technique can maintain the latency of 5G traffic lower than the defined threshold while also significantly reducing the number of active wavelengths. A comparison with the existing state-of-the-art techniques shows that the proposed technique results in an improvement of at least 46% and 29% in terms of the average number of active wavelengths and the average latency for 5G traffic, respectively. Elsevier Inc 2023-10 Article PeerReviewed AlSheibi, Abdullah Zaini and Mohd. Supa’at, Abu Sahmah (2023) Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks. Optical Fiber Technology, 80 (NA). NA. ISSN 1068-5200 http://dx.doi.org/10.1016/j.yofte.2023.103413 DOI:10.1016/j.yofte.2023.103413 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering AlSheibi, Abdullah Zaini Mohd. Supa’at, Abu Sahmah Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks |
| title | Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks |
| title_full | Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks |
| title_fullStr | Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks |
| title_full_unstemmed | Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks |
| title_short | Fuzzy logic based dynamic wavelength and bandwidth allocation for 5G front haul networks |
| title_sort | fuzzy logic based dynamic wavelength and bandwidth allocation for 5g front haul networks |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| work_keys_str_mv | AT alsheibiabdullahzaini fuzzylogicbaseddynamicwavelengthandbandwidthallocationfor5gfronthaulnetworks AT mohdsupaatabusahmah fuzzylogicbaseddynamicwavelengthandbandwidthallocationfor5gfronthaulnetworks |