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Joint D2D Collaboration and Task Offloading for Edge Computing: A Mean Field Graph Approach
用于边缘计算的联合D2D协作和任务卸载:一种平均场图方法
エッジコンピューティングのための結合D2D協調とタスク・オフローディング:平均場グラフアプローチ
변두리 계산 에 사용 되 는 연합 D2D 협업 과 작업 마 운 트 해제:평균 필드 맵 방법
Colaboración conjunta D2D y desinstalación de tareas para la computación de borde: un método gráfico de campo Medio
Collaboration D2D conjointe et déchargement des tâches pour l'Edge Computing : une approche de graphe de champ moyen
совместная работа D2D и разгрузка задач для вычисления границ: метод средней карты поля
Xiong Wang 王雄 ¹, Jiancheng Ye ², John C.S. Lui 呂自成 ¹
¹ The Chinese University of Hong Kong
香港中文大学
² Network Technology Lab and Hong Kong Research Center, Huawei Technologies Co., Ltd.
华为技术有限公司 网络技术实验室 香港研发中心
2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS), 26 August 2021
Abstract

Mobile edge computing (MEC) facilitates computation offloading to edge server, as well as task processing via device-to-device (D2D) collaboration. Existing works mainly focus on centralized network-assisted offloading solutions, which are unscalable to scenarios involving collaboration among massive users. In this paper, we propose a joint framework of decentralized D2D collaboration and efficient task offloading for a large-population MEC system. Specifically, we utilize the power of two choices for D2D collaboration, which enables users to beneficially assist each other in a decentralized manner.

Due to short-range D2D communication and user movements, we formulate a mean field model on a finite-degree and dynamic graph to analyze the state evolution of D2D collaboration. We derive the existence, uniqueness and convergence of the state stationary point so as to provide a tractable collaboration performance. Complementing this D2D collaboration, we further build a Stackelberg game to model users’ task offloading, where edge server is the leader to determine a service price, while users are followers to make offloading decisions. By embedding the Stackelberg game into Lyapunov optimization, we develop an online offloading and pricing scheme, which could optimize server’s service utility and users’ system cost simultaneously. Extensive evaluations show that our D2D collaboration can mitigate users’ workloads by 73.8% and task offloading can achieve high energy efficiency.
2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS)_1
2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS)_2
2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS)_3
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