Efficient and Fair Multi-Resource Allocation in Dynamic Fog Radio Access Network Slicing

Thaha Mohammed, Behrouz Jedari Ghourichaei, Mario Di Francesco

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
217 Downloads (Pure)

Abstract

Future wireless networks should meet heterogeneous service requirements of diverse applications, including interactive multimedia, augmented reality, and autonomous driving. The fog radio access network (Fog-RAN) is a novel architecture that enables efficient and flexible allocation of network resources to end users. However, guaranteeing application-specific service requirements while maximizing resource utilization is an open challenge in Fog-RANs. This article proposes a multi-resource Fog-RAN slicing scheme that maximizes network resource utilization and satisfies important economic properties: Pareto optimality, envy-freeness, and sharing incentive. The proposed solution considers both heterogeneous resources (i.e., bandwidth, storage and computing) and the different service levels defined in 5G networks. Accordingly, a two-level resource scheduling mechanism is devised to jointly allocate Fog-RAN resources to slices in two stages: a broker allocates resources to slices at fog nodes over a given time window; a slice hypervisor then allocates slice-specific resources at each fog node to users with a much shorter time scale. An extensive evaluation based on real-world datasets demonstrates that the proposed solution significantly increases the monetary gain of service providers, namely, by 32% to 60% compared to the state of the art, including dynamic hierarchical resource allocation and dynamic slicing with proportional allocation.
Original languageEnglish
Pages (from-to)24600-24614
Number of pages15
JournalIEEE Internet of Things Journal
Volume9
Issue number24
Early online date20 Jul 2022
DOIs
Publication statusPublished - 15 Dec 2022
MoE publication typeA1 Journal article-refereed

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