Edge computing based incentivizing mechanism for mobile blockchain in IOT
Liya Xu, Mingzhu Ge, Weili Wu

TL;DR
This paper introduces an incentivizing mechanism using edge computing and game theory to enhance mobile blockchain mining in IoT, improving profit and resource sharing among mobile devices and edge servers.
Contribution
It proposes a novel two-stage Stackelberg game model for incentivizing mobile devices in edge-assisted blockchain mining, optimizing rewards and resource allocation.
Findings
The scheme achieves a unique Nash Equilibrium.
It outperforms the MDG scheme in profit under same total computing power.
Simulation results demonstrate increased profit for edge servers.
Abstract
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…
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Taxonomy
TopicsBlockchain Technology Applications and Security · IoT and Edge/Fog Computing · Retinal Imaging and Analysis
