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Cloud/Edge Computing Service Management in Blockchain Networks: Multi-Leader Multi-Follower Game-Based ADMM for Pricing

机译:区块链网络中的云/边缘计算服务管理:基于多领导的多追随者游戏的定价admm

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The mining process in public blockchains with the Nakamoto consensus protocol requires solving a computational puzzle, i.e., proof-of-work, which is resource expensive to implement in lightweight devices with limited computing resources and energy. Thus, renting mining service from cloud providers becomes a reasonable solution, which is called cloud mining. This enables users who want to mine, i.e., miners, to purchase and lease an amount of hashing power from the cloud/edge providers without any hassle of managing the infrastructure. In this paper, we study the interactions among the cloud/edge providers and miners in blockchain using a multi-leader multi-follower game-theoretic approach, in order to support proof-of-work based blockchains application. Due to the inherent complexity of the formulated game, we employ the Alternating Direction Method of Multipliers (ADMM) algorithm to investigate the optimum solution. Utilizing the decomposition characteristics and fast convergence of ADMM, we obtain the optimum results in a distributed manner. Simulation results demonstrate that with the proposed solutions, the optimization of the utilities of miners and the profits of providers can be jointly achieved.
机译:具有Nakamoto共识协议的公共区块中的挖掘过程需要解决计算难题,即工作验证,这是在具有有限的计算资源和能量的轻量级设备中实现昂贵的资源。因此,从云提供商租用挖掘服务成为一个合理的解决方案,称为云挖掘。这使得想要我的用户,即矿工,从云/边缘提供商购买和租赁一定量的散列电源,而无需管理基础架构的任何麻烦。在本文中,我们使用多领导多跟随游戏理论方法研究区块链中云/边缘提供商和矿工之间的互动,以支持基于验证的基于障碍的区块链应用。由于配制游戏的固有复杂性,我们采用了乘法器(ADMM)算法的交替方向方法来研究最佳解决方案。利用ADMM的分解特性和快速收敛,我们以分布式方式获得最佳结果。仿真结果表明,通过拟议的解决方案,可以共同实现矿工公用事业的优化和提供者的利润。

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