Competing Miners: A Synergetic Solution for Combining Blockchain and Edge Computing in Unmanned Aerial Vehicle Networks

Edge computing (EC) is very useful and particularly promising for many practical unmanned aerial vehicle (UAV) applications. Integrating the blockchain to this technology strengthens privacy protection and data integrity and also prevents data from being easily leaked. However, the required operations in the blockchain are computationally heavy because a blockchain requires devices to solve a complicated proof-of-work (PoW) puzzle to add new data (i.e., a block) to the blockchain. Solving a PoW requires substantial amounts of time and energy, which are big concerns for UAVs. In this article, we suggest a synergetic solution to address this issue based on multiple competing miners in a blockchain. Specifically, we present two novel frameworks for combining the blockchain and EC to effectively overcome several critical limitations when applying the blockchain to UAV and EC tasks, respectively. The goal of both of these proposed frameworks is to reduce both the time spent on mining and the energy consumption for the EC. We first look at the fundamentals of the blockchain with competing miners. Then, our proposed frameworks are described with experimental results, through which important insights are drawn. We finally discuss application scenarios for our proposed frameworks, the related technical challenges, and future research directions.

Automated summary

Edge computing is highly promising for UAV applications, and integrating blockchain technology can enhance privacy protection and data integrity. However, the computational demands of blockchain pose challenges for UAVs. This article proposes a synergetic solution using competing miners in a blockchain, presenting two novel frameworks that effectively address critical limitations. The goal is to reduce mining time and energy consumption for edge computing. The article covers the fundamentals of blockchain with competing miners, describes the proposed frameworks with experimental results, and discusses application scenarios, technical challenges, and future research directions.