Traffic aware cyclic sleep-based power consumption model for a passive optical network

Butt R. A., FAHEEM M., Anwar M., Mohammadani K. H., Idrus S. M.

INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS, cilt.35, sa.4, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 35 Sayı: 4
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1002/jnm.2996
  • Dergi Adı: INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, INSPEC, Metadex, zbMATH, DIALNET, Civil Engineering Abstracts
  • Anahtar Kelimeler: energy efficiency, XGPON, DTMC, green optical networks, DYNAMIC BANDWIDTH ALLOCATION, EFFICIENT
  • Abdullah Gül Üniversitesi Adresli: Evet

Özet

For a network, a power consumption model is an important tool to test the performance of a network process for different traffic loads. In a Passive optical network (PON), the optical network unit (ONU) is responsible for the major power consumption of PON. Both IEEE and ITU have standardized a cyclic sleep process (CSP) for ONU energy conservation. In next-generation PON; TWDM and XGS PON, the ONU power contribution has increased further due to higher number of ONUs and ONU being tunable. Therefore, an accurate power consumption model of the CSP process for energy efficiency studies under different traffic conditions is of prime importance. The existing CSP power consumption models do not depict the CSP process accurately especially the inactivity of the ONU in the asleep and sleep aware states are not taken into account which reduce the accuracy of the model. The proposed inactivity aware model (IAM) overcomes these gaps and very accurately models the CSP process, as evident from the results, which are better than earlier model results and quite close to earlier published simulation results. The model is also validated through a simulation-based study and the simulation results are observed to be very close to the model results with only a 5% deviation.