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A Game-Based Incentive-Driven Offloading Framework for Dispersed Computing

计算机科学 计算卸载 继电器 斯塔克伯格竞赛 分布式计算 计算机网络 边缘计算 不可用 服务器 资源配置 计算 服务(商务) GSM演进的增强数据速率 工程类 电信 功率(物理) 物理 数学 经济 数理经济学 算法 量子力学 经济 可靠性工程
作者
Hongjia Wu,Jiangtian Nie,Zehui Xiong,Zixing Cai,Tongqing Zhou,Chau Yuen,Dusit Niyato
出处
期刊:IEEE Transactions on Communications [Institute of Electrical and Electronics Engineers]
卷期号:71 (7): 4034-4049 被引量:3
标识
DOI:10.1109/tcomm.2023.3266833
摘要

The popularization of smart Internet of Things (IoT) devices has facilitated the development of fog/edge computing. However, these infrastructure-based service paradigms may fail to complete tasks successfully due to computation and communication overload, or damage in challenging scenarios such as disasters or traffic jams. Noticing that a crowd of devices with considerable idle resources could be available, we investigate the problems of addressing the computation and communication unavailability with peer assistance in this work. To this end, we propose a dispersed service framework for resource-exhausted scenarios that adaptively offloads users’ data to available network computation points. However, the users may not be able to achieve the offloading due to geographical hindrances. Consequently, the relay is introduced as a bridge for data offloading between the users and the network computation points. Furthermore, a game-based incentive-driven offloading mechanism is designed by analyzing and balancing the cost and gain factors of three main entities (users, relays, and network computation points). Considering the interactions among the entities, a two-level Stackelberg game is established for efficiently allocating potential computation resource, as well as balancing the utility conflicts due to the data offloading. Given the hierarchical interaction structure, the upper level game involves network computation points as followers and the relay as a leader, while the lower level game includes the relay as a follower and users as leaders. Moreover, to facilitate applicability in large-scale scenarios with multiple relays, we decompose multiple relays into multiple single relay problems using a tripartite matching strategy that assigns appropriate relays to users and network computation points. The simulation results demonstrate the effectiveness of the proposed game-based incentive-driven mechanism and show that it outperforms the baselines in terms of the overall utilities of the involved entities and the average energy consumption of users.

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