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The emergence of computing power networks has improved the flexibility of resource scheduling. Considering the current trading scenario of computing power and network resources, most resources are no longer subject to change after being allocated to users until the end of the lease. However, this practice often leads to idle resources during resource usage. To optimize resource allocation, a trading mechanism is needed to encourage users to sell their idle resources. The Myerson auction mechanism precisely aims to maximize the seller's benefits. Therefore, we propose a resource allocation scheme based on the Myerson auction. In the scenario of the same user bidding distribution, we first combine the Myerson auction with Hyperledger Fabric by introducing a reserved price, which creates conditions for the application of blockchain in auction scenarios. Regarding different user bidding distributions, we propose a Myerson auction network model based on clustering algorithms, which makes the auction adaptable to more complex scenarios. The experimental findings show that the revenue generated by the auction model in both scenarios is significantly higher than that of the traditional sealed bid second-price auction, and can approach the expected revenue in the real Myerson auction scenario. [ABSTRACT FROM AUTHOR]

In wireless communication networks, the stock of spectrum, computing, storage and other resources at the edge was limited. The traditional decentralized and exclusive resource allocation resulted in weak resource reuse capability and low utilization rate. At the same time, it was difficult to ensure the fairness of resource sharing in the traditional resource scheduling process due to the lack of trust between the owners. First, a double auction model of computing and wireless communication resource joint management based on blockchain was proposed. In the model, a resource market was established, in which resource buyers and sellers allocated resources through double auctions. Secondly, blockchain was used to store the resource information of buyers and sellers to solve the mutual trust problem of all parties in the network. Finally, the experimental simulation was carried out to verify that the proposed model effectively improved the system performance and resource utilization efficiency. [ABSTRACT FROM AUTHOR]

Basic services for power business were provided by the power multimodel network providers. However, because the power multimodal network is usually complex and changeable, the service of power business is often unstable. This problem can be solved by a suitable network resource optimization method. Therefore, how to design a network resource optimization method that seeks a compromise between multiple performance indicators that achieve the normal operation of power multimode networks is still extremely challenging. An optimal allocation method of power multimodal network resources based on NSGA-II was proposed by this paper. Firstly, the power multimodal network-resource model is established, and the problems existing in the resource optimization process are analyzed. Secondly, preprocessing technology and indirect coding technology are applied to NSGA-II, which solves the coding problem and convergence problem of the application of genetic algorithm to the optimization of network resource allocation. Finally, the simulation results show that, compared with the control algorithm, this method has further optimized the various indicators of the resource allocation of the power multimodal network, and the performance has been improved by more than 6%. [ABSTRACT FROM AUTHOR]