Bargaining Game-Based Resource Management for Pervasive Edge Computing Infrastructure

Abstract

The explosive growth of Internet of things (IoT) devices has promoted the prosperity of virtual reality applications, which can be realized by service offloading with the assistance of pervasive edge computing (PEC) platforms. However, owing to the limited computational and communication resources of PEC systems, it is necessary to design a novel resource management algorithm. In this study, we adopt cooperative bargaining theory to design our PEC resource allocation scheme. According to the concept of unification bargaining solution, different bargaining ideas are reciprocally combined to provide a fairefficient solution. By coordinating network agents, we can leverage mutual consensus and approximate a well-balanced system performance among conflicting requirements. It is essential to explore the relevant trade-off between efficiency and fairness. To effectively share the PEC resources, the main novelty of our approach is its adaptability and flexibility to respond dynamic PEC system environments. Finally, extensive simulations are carried out, and the numerical results demonstrate that our unified bargaining method can obtain desirable features while maximizing the offloading service performance by comparing the existing state-of-the-art PEC control protocols.