期刊
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
卷 7, 期 1, 页码 55-64出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TETCI.2022.3145694
关键词
Servers; Task analysis; Games; Computational modeling; Processor scheduling; Delays; 5G mobile communication; Mobile Computing; game theory; edge computing; scheduling
This paper presents a game theory-based distributed edge computing server task scheduling model that balances link quality and computing resource requirements, provides differentiated services for different priority users, accurately predicts link quality using a time series prediction algorithm, and achieves Nash equilibrium quickly through an acceleration scheme.
Task scheduling on edge computing servers is a critical concern affecting user experience. Current scheduling methods attain an overall appealing performance through centralized control. Nevertheless, forcing users to act based on a centralized control is impractical. Hence, this work suggests a game theory-based distributed edge computing server task scheduling model. The proposed method comprehensively considers the mobile device-server link quality and the server's computing resource allocation and balances link quality and computing resources requirements when selecting edge computing servers. Furthermore, we develop a time series prediction algorithm based on IndRNN and LSTM to accurately predict link quality. Once Nash equilibrium is reached quickly through our proposed acceleration scheme, the proposed model provides various QoS for different priority users. The experimental results highlight that the developed solution provides differentiated services while optimizing computing resource scheduling and ensuring an approximate Nash equilibrium in polynomial time.
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