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Edge computing based incentivizing mechanism for mobile blockchain in IOT
arXiv - CS - Computer Science and Game Theory Pub Date : 2020-06-16 , DOI: arxiv-2006.08915
Liya Xu, Mingzhu Ge, Weili Wu

Mining in the blockchain requires high computing power to solve the hash puzzle for example proof-of-work puzzle. It takes high cost to achieve the calculation of this problem in devices of IOT, especially the mobile devices of IOT. It consequently restricts the application of blockchain in mobile environment. However, edge computing can be utilized to solve the problem for insufficient computing power of mobile devices in IOT. Edge servers can recruit many mobile devices to contribute computing power together to mining and share the reward of mining with these recruited mobile devices. In this paper, we propose an incentivizing mechanism based on edge computing for mobile blockchain. We design a two-stage Stackelberg Game to jointly optimize the reward of edge servers and recruited mobile devices. The edge server as the leader sets the expected fee for the recruited mobile devices in Stage I. The mobile device as a follower provides its computing power to mine according to the expected fee in Stage. It proves that this game can obtain a uniqueness Nash Equilibrium solution under the same or different expected fee. In the simulation experiment, we obtain a result curve of the profit for the edge server with the different ratio between the computing power from the edge server and mobile devices. In addition, the proposed scheme has been compared with the MDG scheme for the profit of the edge server. The experimental results show that the profit of the proposed scheme is more than that of the MDG scheme under the same total computing power.

中文翻译:

基于边缘计算的物联网移动区块链激励机制

在区块链中挖矿需要高计算能力来解决哈希难题,例如工作量证明难题。在物联网设备,尤其是物联网的移动设备中实现这个问题的计算需要很高的成本。因此限制了区块链在移动环境中的应用。然而,边缘计算可以用来解决物联网中移动设备计算能力不足的问题。边缘服务器可以招募许多移动设备,共同为挖矿贡献计算能力,并与这些招募的移动设备分享挖矿的回报。在本文中,我们提出了一种基于边缘计算的移动区块链激励机制。我们设计了一个两阶段的 Stackelberg 博弈来共同优化边缘服务器和招募的移动设备的奖励。作为领导者的边缘服务器为第一阶段招募的移动设备设置预期费用。作为跟随者的移动设备根据阶段的预期费用提供其计算能力进行挖矿。证明了该博弈在相同或不同的期望费用下都能获得唯一性的纳什均衡解。在仿真实验中,我们得到了边缘服务器和移动设备的计算能力之间不同比例的边缘服务器的利润结果曲线。此外,为了边缘服务器的盈利,提出的方案已经与MDG方案进行了比较。实验结果表明,在总算力相同的情况下,所提方案的收益大于MDG方案。作为跟随者的移动设备根据 Stage 中的预期费用提供其计算能力进行挖矿。证明了该博弈在相同或不同的期望费用下都能获得唯一性的纳什均衡解。在仿真实验中,我们得到了边缘服务器和移动设备的计算能力之间不同比例的边缘服务器的利润结果曲线。此外,为了边缘服务器的盈利,提出的方案已经与MDG方案进行了比较。实验结果表明,在总算力相同的情况下,所提方案的收益大于MDG方案。作为跟随者的移动设备根据 Stage 中的预期费用提供其计算能力进行挖矿。证明了该博弈在相同或不同的期望费用下都能获得唯一性的纳什均衡解。在仿真实验中,我们得到了边缘服务器和移动设备的计算能力之间不同比例的边缘服务器的利润结果曲线。此外,为了边缘服务器的盈利,提出的方案已经与MDG方案进行了比较。实验结果表明,在总算力相同的情况下,所提方案的收益大于MDG方案。我们得到边缘服务器和移动设备的计算能力之间不同比例的边缘服务器的利润结果曲线。此外,为了边缘服务器的盈利,提出的方案已经与MDG方案进行了比较。实验结果表明,在总算力相同的情况下,所提方案的收益大于MDG方案。我们得到边缘服务器和移动设备的计算能力之间不同比例的边缘服务器的利润结果曲线。此外,为了边缘服务器的盈利,提出的方案已经与MDG方案进行了比较。实验结果表明,在总算力相同的情况下,所提方案的收益大于MDG方案。
更新日期:2020-07-02
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