Joint Computation Offloading and Resource Allocation in Mobile-Edge Cloud Computing: A Two-Layer Game Approach

Mobile-Edge Cloud Computing (MECC) plays a crucial role in balancing low-latency services at the edge with the computational capabilities of cloud data centers (DCs). However, many existing studies focus on single-provider settings or limit their analysis to interactions between mobile devices (MDs) and edge servers (ESs), often overlooking the competition that occurs among ESs from different providers. This article introduces an innovative two-layer game framework that captures independent self-interested competition among MDs and ESs, providing a more accurate reflection of multi-vendor environments. Additionally, the framework explores the influence of cloud-edge collaboration on ES competition, offering new insights into these dynamics. The proposed model extends previous research by developing algorithms that optimize task offloading and resource allocation strategies for both MDs and ESs, ensuring the convergence to Nash equilibrium in both layers. Simulation results demonstrate the potential of the framework to improve resource efficiency and system responsiveness in multi-provider MECC environments.

I. Introduction

Mobile Edge Computing (MEC) has become a foundational pillar in modern computing, bringing computational resources closer to end-users. This proximity allows mobile devices (MDs) such as smartphones, PDAs, and wearables to overcome inherent limitations in processing power, communication bandwidth, storage, and battery life [1], [2], [3]. By leveraging MEC, MDs are now capable of delivering a wide array of advanced services, including multiplayer online gaming, high-definition image processing, and intelligent personal assistants [4]. The proliferation of MEC has not only accelerated the evolution of mobile applications but has also significantly transformed social interaction, commerce, and entertainment.