Matching with contract-based resource trading in UAV-assisted MEC system

Yuanfa Lu, Ziqiong Lin, Wenjie Zhang, Yifeng Zheng, Jingmin Yang
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Abstract

Multi-access edge computing (MEC), as a computing model that provides services on the user side, can effectively solve the problems of high delay and resource shortage in traditional cloud computing when processing massive data. However, existing edge computing resources are still limited, and difficult to provide services to users in inaccessible remote areas. Considering that unmanned aerial vehicle (UAV) has the advantages of easy deployment, high flexibility and low cost, a UAV-assisted MEC hierarchical computation offloading framework is proposed. Firstly, contract theory is used to solve the information asymmetry problem between the platform and the UAV, and the UAV is encouraged to provide computing services. By analyzing the attributes and conditions of feasible contracts, the optimal contract is designed using the Lagrange multiplier method. Secondly, by constructing the preference set between UAV and mobile user (MU), a mobile user and unmanned aerial vehicle bilateral matching (MUBM) algorithm is proposed to establish the connection between user tasks and UAV computing resources. Finally, the feasibility and effectiveness of the contract were verified through experiments. The experimental results also prove the stability of the MUBM.

Abstract Image

无人机辅助 MEC 系统中基于合同的资源交易匹配
多接入边缘计算(MEC)作为一种在用户侧提供服务的计算模式,可以有效解决传统云计算在处理海量数据时存在的高延迟和资源短缺问题。然而,现有的边缘计算资源仍然有限,难以为交通不便的偏远地区用户提供服务。考虑到无人机(UAV)具有部署方便、灵活性高、成本低等优点,本文提出了无人机辅助 MEC 分层计算卸载框架。首先,利用契约理论解决平台与无人机之间的信息不对称问题,鼓励无人机提供计算服务。通过分析可行合约的属性和条件,利用拉格朗日乘法设计出最优合约。其次,通过构建无人机与移动用户(MU)之间的偏好集,提出移动用户与无人机双边匹配(MUBM)算法,建立用户任务与无人机计算资源之间的联系。最后,通过实验验证了合同的可行性和有效性。实验结果也证明了 MUBM 的稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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