@article{mamushiane_5g_2022,
	title = {{5G} {Network} {Slice} {Resource} {Overbooking}: {An} {Opportunity} for {Telcos} to {Boost} their {Revenue}},
	abstract = {The global impact of COVID-19 has been unprecedented, with over-the-top (OTT) services consumption growing at a staggering rate. While OTT does consume revenue-generating data, OTT services are gradually substituting the traditional primary sources of revenue, voice and SMS services, with “freemium-based” alternatives such as WhatsApp and Telegram. This has driven telcos to reconsider their strategies and revenue sources. We believe that 5G network slicing (a type of 5G infrastructure sharing) is a potential solution that telcos could adopt to boost their revenue. In particular, this paper introduces the concept of network slice resource overbooking. We consider leveraging machine learning (ML) to maximise network resource utilisation which translates to maximum revenue gains for telcos. The concept of overbooking is unique and novel in network slicing. To realise this objective, we intend to build a mathematical model of the overbooking strategy, and integrate the model into a resource orchestration platform for evaluation on an emulated 3GPP (Release 16) compliant 5G testbed.},
	language = {en},
	author = {Mamushiane, Lusani and Mwangama, Joyce and Lysko, Albert and Kobo, Hlabishi},
	year = {2022},
}

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