More recently, there has been a growing interest in the blockchain technique for emerging multi-access edge computing (MEC) applications in relation to security and privacy, considering the benefits of using it in edge computing. In some blockchain-enabled MEC using the best-known consensus algorithm proof-of-work (PoW), the computational efforts increase dramatically with the number of transactions, since a large amount of computational tasks should be conducted by miners with the limited computing resources in edge devices. Hence, improving the computational performance as an important but challenging issue in the design of blockchain system for MEC applications, has attracted intensive attention within last years. To further improve the performance of PoW algorithm, we present a novel implementation mechanism in this paper. Here, motivated by proof-of-deep-learning (PoDL) method in which the deep learning algorithm is used to maintain blockchain, through the design of a two-stage model to achieving computational tasks in PoDL-based blockchain systems, a novel computational-efficient consensus mechanism, named separate-proof-of-deep-learning (S-PoDL), is accordingly proposed. Thus, an energy-efficient blockchain-enabled MEC could be developed with our proposed S-PoDL, which arranges miners to carry out a two-stage-based computation on the basis of accounting_queue technique, while presenting the achieved models as proofs in MEC network. The comparative experiments are conducted between S-PoDL and PoDL, and the experimental results verify the feasibility and efficiency of our consensus mechanism S-PoDL for some blockchain-enabled MEC applications in relation to PoW-based cryptocurrencies, while effectively reducing computing burden of edge devices.

最近，考虑到在边缘计算中使用它的好处，人们对于与安全性和隐私相关的新兴多访问边缘计算（MEC）应用程序的区块链技术越来越感兴趣。在一些使用最知名的共识算法工作量证明（PoW）的启用区块链的MEC中，计算工作量随着交易数量的增加而急剧增加，因为矿工应使用有限的计算资源来执行大量的计算任务在边缘设备中。因此，提高计算性能是MEC应用程序区块链系统设计中一个重要但具有挑战性的问题，近年来引起了广泛的关注。为了进一步提高PoW算法的性能，本文提出了一种新颖的实现机制。这里，受深度学习证明（PoDL）方法的启发，该方法采用深度学习算法来维护区块链，通过两阶段模型的设计来实现基于PoDL的区块链系统中的计算任务，这是一种新颖的计算效率高的算法相应地，提出了一种共识机制，称为深度学习分离证明（S-PoDL）。因此，可以使用我们提出的S-PoDL开发高能效的区块链MEC，该S-PoDL安排矿工基于以下步骤进行基于两阶段的计算：因此提出。因此，可以使用我们提出的S-PoDL开发高能效的区块链MEC，该S-PoDL安排矿工基于以下步骤进行基于两阶段的计算：因此提出。因此，可以使用我们提出的S-PoDL开发高能效的区块链MEC，该S-PoDL安排矿工基于以下步骤进行基于两阶段的计算：accounting_queue技术，同时在MEC网络中展示所实现的模型作为证明。在S-PoDL和PoDL之间进行了对比实验，实验结果证明了我们的共识机制S-PoDL对于某些与基于PoW的加密货币相关的启用区块链的MEC应用程序的可行性和效率，同时有效地减少了边缘的计算负担设备。