Fisher Market Model based Resource Allocation for 5G Network Slicing

TL;DR

This paper introduces a resource allocation scheme for 5G network slicing based on the Fisher-market model, aiming to optimize resource use, fairness, and SLA protection through a decentralized, privacy-preserving learning algorithm.

Contribution

It formulates a convex optimization problem for market equilibrium in 5G slicing and develops a decentralized algorithm for resource allocation and pricing.

Findings

Achieves efficient resource utilization and fairness in 5G slices.

Outperforms social optimal and static proportional schemes in simulations.

Ensures SLA protection and adapts to dynamic load conditions.

Abstract

Network slicing (NS) is a key technology in 5G networks that enables the customization and efficient sharing of network resources to support the diverse requirements of nextgeneration services. This paper proposes a resource allocation scheme for NS based on the Fisher-market model and the Trading-post mechanism. The scheme aims to achieve efficient resource utilization while ensuring multi-level fairness, dynamic load conditions, and the protection of service level agreements (SLAs) for slice tenants. In the proposed scheme, each service provider (SP) is allocated a budget representing its infrastructure share or purchasing power in the market. SPs acquire different resources by spending their budgets to offer services to different classes of users, classified based on their service needs and priorities. The scheme assumes that SPs employ the $\alpha$-fairness criteria to deliver services to their subscribers. The resource allocation problem is formulated as a convex optimization problem to find a market equilibrium (ME) solution that provides allocation and resource pricing. A privacy-preserving learning algorithm is developed to enable SPs to reach the ME in a decentralized manner. The performance of the proposed scheme is evaluated through theoretical analysis and extensive numerical simulations, comparing it with the Social Optimal and Static Proportional sharing schemes.