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A Game Theoretic Approach for D2D Assisted Uncoded Caching in IoT Networks

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Vydáno v:Future Internet vol. 17, no. 9 (2025), p. 423-447
Hlavní autor: Ren Jiajie
Další autoři: Guo, Chang
Vydáno:
MDPI AG
Témata:
Iterative algorithms
Game theory
Utility theory
Caching
Integer programming
Costs
Optimization
Equilibrium
Probability
Maximization
Algorithms
Utility functions
Internet of Things
Heterogeneity
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Abstrakt:Content caching and exchange through device-to-device (D2D) communications can offload data from the centralized base station and improve the quality of users’ experience. However, existing studies often overlook the selfish nature of user equipment (UE) and the heterogeneity of content preferences, which limits their practical applicability. In this paper, we propose a novel incentive-driven uncoded caching framework modeled as a Stackelberg game between a base station (BS) and cache-enabled UEs. The BS acts as the leader by determining the unit incentive reward, while UEs jointly optimize their caching strategies as followers. The particular challenge in our formulation is that the uncoded caching decisions make the UEs’ total utility maximization problem into a non-convex integer programming problem. To address this, we map the UEs’ total utility maximization problem into a potential sub-game and design a potential game-based distributed caching (PGDC) algorithm that guarantees convergence to the optimal joint caching strategy. Building on this, we further develop a dynamic iterative algorithm to derive the Stackelberg equilibrium by jointly optimizing the BS’s cost and the total utility of UEs. The simulation results confirm the existence of the Stackelberg Equilibrium and demonstrate that the proposed PGDC algorithm significantly outperforms benchmark caching schemes.
ISSN:1999-5903
DOI:10.3390/fi17090423
Zdroj:ABI/INFORM Global