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)...

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Bibliographic Details
Published in:IEEE transactions on cloud computing Vol. 13; no. 1; pp. 411 - 428
Main Authors: He, Zhenli, Guo, Ying, Zhai, Xiaolong, Zhao, Mingxiong, Zhou, Wei, Li, Keqin
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.01.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Cloud computing
Collaboration
Competition
Computation offloading
Computational modeling
Dynamic scheduling
Edge computing
game theory
Games
Heuristic algorithms
Mathematical models
Mobile computing
mobile-edge cloud computing
nash equilibrium
Resource allocation
Resource management
Servers
Vehicle dynamics
ISSN:2168-7161, 2372-0018
Online Access:Get full text
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Summary: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.
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ISSN:2168-7161
2372-0018
DOI:10.1109/TCC.2025.3538090