Profit-Aware Proactive Slicing Resource Provisioning with Traffic Uncertainty in Multi-Tenant FlexE-over-WDM Networks
Guo, Qize; Ming, Zhao; Yu, Hao; Chen, Yan; Taleb, Tarik (2024-08-20)
IEEE
20.08.2024
Q. Guo, Z. Ming, H. Yu, Y. Chen and T. Taleb, "Profit-Aware Proactive Slicing Resource Provisioning with Traffic Uncertainty in Multi-Tenant FlexE-over-WDM Networks," ICC 2024 - IEEE International Conference on Communications, Denver, CO, USA, 2024, pp. 3059-3064, doi: 10.1109/ICC51166.2024.10622595
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© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202410026148
https://urn.fi/URN:NBN:fi:oulu-202410026148
Tiivistelmä
Abstract
Addressing the pressing requirement for dynamic and intelligent allocation of slicing resources, the dynamic provisioning of resources based on traffic predictions has emerged. Although this method favours proactive scheduling of network slices, more complexities are introduced by the prediction uncertainty. In addition, because multi-tenant networks are always changing in terms of technology and business model, profit-aware network slicing is becoming an important topic of study in the field of resource provision. This paper focuses on profit-aware slicing resource provisioning amid traffic uncertainty in multi-tenancy flexible Ethernet over wavelength division multiplexing networks. Specifically, we develop a profit model for multi-tenant network slicing, accounting for the impact of network prediction uncertainty, and formulate the problem as maximizing the profit of users primarily. To solve this problem, we propose a profit-aware resource provisioning approach that first checks if the slice requests are made by pruning algorithms and then determines the service relationship between slices and tenants by matching games. Simulation results demonstrate the superiority of the proposed algorithm over benchmarks in terms of user profit, total benefit, and denial ratio of service.
Addressing the pressing requirement for dynamic and intelligent allocation of slicing resources, the dynamic provisioning of resources based on traffic predictions has emerged. Although this method favours proactive scheduling of network slices, more complexities are introduced by the prediction uncertainty. In addition, because multi-tenant networks are always changing in terms of technology and business model, profit-aware network slicing is becoming an important topic of study in the field of resource provision. This paper focuses on profit-aware slicing resource provisioning amid traffic uncertainty in multi-tenancy flexible Ethernet over wavelength division multiplexing networks. Specifically, we develop a profit model for multi-tenant network slicing, accounting for the impact of network prediction uncertainty, and formulate the problem as maximizing the profit of users primarily. To solve this problem, we propose a profit-aware resource provisioning approach that first checks if the slice requests are made by pruning algorithms and then determines the service relationship between slices and tenants by matching games. Simulation results demonstrate the superiority of the proposed algorithm over benchmarks in terms of user profit, total benefit, and denial ratio of service.
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