A Stackelberg Game-Based Dynamic Resource Allocation in Edge Federated 5G Network

• Published in: IEEE access Vol. 10; pp. 10460 - 10471
• Main Authors: Ahmed, Jargis, Razzaque, Md. Abdur, Rahman, Md. Mustafizur, Alqahtani, Salman A., Hassan, Mohammad Mehedi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; 5G network; Algorithms; Cloud computing; Edge computing; Edge federation; Game theory; Games; Matching; Mobile computing; mobile edge computing; Mobile handsets; Performance evaluation; Resource allocation; Resource management; Servers; Stackelberg game; Task analysis; utility maximization; Wireless networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3144960

Mobile Edge Computing (MEC) plays key role for providing fast-response and high interactivity in the emerging 5G network. Edge service providers (ESP) are responsible for serving edge users or IoT devices running latency-critical applications. An MEC server provides faster response to ESPs but has limited computation resources, hence, it can be overloaded due to extensive resource demand. Thus, federation of multiple MEC servers offers an opportunity for dynamic resource allocation in a distributed manner. The federation objective is to maximize the usage of underutilized edge resources and reduction of service provision time simultaneously. As all the ESPs and MECs act autonomously, it is quite impossible for all the individuals to achieve optimal behavior simultaneously. In this paper, we develop a Stackelberg Game (<inline-formula> <tex-math notation="LaTeX">SBG </tex-math></inline-formula>) based dynamic resource allocation method to reach the expected performance. The <inline-formula> <tex-math notation="LaTeX">SBG </tex-math></inline-formula> analyzes the pricing of MECs and the resource-purchasing problem of ESPs. We also develop a many-to-many matching algorithm for resource sharing among the MECs and a one-to-many matching algorithm for that between an MEC server and ESPs. The results from an extensive performance evaluation demonstrate effectiveness of the proposed system in increasing utilities for MECs and ESPs, reducing the turnaround time of application tasks, and ensuring fair resource distribution compared to state-of-the-art works.