Energy Internet (EI) is aimed at sustainable computing by integrating various energy forms into a highly flexible grid similar to the Internet. The network subsystems of EI connect different components to enable real-time monitoring, controlling, and management. In this paper, the spectrum allocation problem of the cognitive radio network for EI in a smart city is investigated. The network spectrum allocation with both heterogeneous primary operators and secondary users is formulated as the combinatorial auction problem and then is converted to a subset selection problem on a weighted bipartite graph. We propose a hybrid algorithm to solve the problem. Firstly, the proposed algorithm uses a constructive procedure based on the Kuhn-Munkres algorithm to obtain an initial solution. Then, a local search is used to improve the solution quality. In addition, the truthfulness of the auction is guaranteed by adopting a “Vickrey-like” mechanism. Simulation results show that the performance of the proposed algorithm is better than existing greedy algorithms in terms of the social welfare, seller revenue, buyer satisfaction ratio, and winning buyer ratio.

中文翻译：

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基于加权二部图的智能城市能源互联网混合频谱组合拍卖机制

能源互联网（EI）旨在通过将各种能源形式集成到类似于Internet的高度灵活的网格中来实现可持续计算。EI的网络子系统连接不同的组件，以实现实时监视，控制和管理。本文研究了智能城市中用于EI的认知无线电网络的频谱分配问题。将具有异构主要运营商和次要用户的网络频谱分配公式化为组合拍卖问题，然后将其转换为加权二部图上的子集选择问题。我们提出了一种混合算法来解决这个问题。首先，提出的算法使用基于Kuhn-Munkres算法的构造过程来获得初始解。然后，使用本地搜索来提高解决方案质量。此外，通过采用“类似维克瑞”机制来保证拍卖的真实性。仿真结果表明，该算法在社会福利，卖方收益，买方满意率和买方获胜率等方面均优于现有的贪婪算法。