On the quality of service of next generation green networks. Issue 1 (18th July 2021)

• Record Type: Journal Article
• Authors: Al‐Nedawe, Basman M.; Alhumaima, Raad S.; Ali, Wisam Hasan
• Is Part Of: IET networks. Volume 11:Issue 1(2022)
• Page Start: 1
• Page End: 12
• Publication Date: 2021-07-18
• Subjects: energy conservation -- channel capacity -- quality of service -- next generation networks -- telecommunication power management; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/ntw2.12030
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract: Green technology will emerge in the coming generation and offer power saving and environment‐friendly communication networks. This study discusses the trade‐offs that are concurrent with enabling the green evolution. In addition to the well‐known network's quality of service metrics such as channel capacity, energy efficiency and spectral efficiency, this study mathematically evaluates new green‐correlated metrics, defined by economic efficiency, environmental efficiency and cost efficiency. The latter are based on new suggested parameters/factors that are necessary to be counted in the future green architectures, such as CO2 savings, deployment cost, initial cost, required area, job offerings, capital expenses, operational expenses and maintenance. Not to mention the standard network parameters, represented by transmitted power, received power, consumed power, bandwidth and delay. This study also shows that green‐oriented networks may have a relatively high initial cost but may cost less in cloud networks. Hence, directly shifting traditional networks to green networks requires investigation. The proposed models can assist network providers and investors to judge upon when and where the green energy source can be utilised. Moreover, these models support the designing and planning of futuristic networks based on knowing the interrelationship amongst the evaluated metrics and their influencing factors.