Lightweight blockchain framework using enhanced master-slave blockchain paradigm: Fair rewarding mechanism using reward accuracy model

Blockchains have become the prominent technology for logging records within a secured plat-form. However, the biggest challenge in existing blockchain technologies is unnecessary wastage of resources, such as electricity, due to network traffic and inefficient reward mechanisms during the blockchain mining process. To overcome this, we introduce a lightweight blockchain framework to reduce the cost of computationally intensive mining processes and network traffic while fairly rewarding concurrent miners. The proposed framework divides the traditional blockchain into two layers: master node(s) and slave agents (SAs). We develop mechanisms to (i) compute the reward accuracy of successful miners considering the significant factors of time taken to identify a number used only once (nonce) and their reward success rate history, (ii) ensure the reliability of new transactions with an equivalent proof of work consensus, (iii) handle SAs who identify a nonce value at the same time as other SAs while rewarding successful miners fairly, (iv) analyze the fairness of the reward accuracy model by catering to a successful miner who failed to receive a success reward to compensate for costs spent on the mining process and network traffic, and (v) reduce electricity usage and scalability problems during the integration of the blockchain and the Internet of Things (IoT) by subdividing the blockchain into separate shards. We find that a lower weight percentage of the time taken to identify a nonce has a more significant effect on reward accuracy than does a higher weight percentage. Further, our results show that the time taken to identify a nonce has a higher dependence on reward accuracy than on the effect of the reward success rate history. We compare our algorithm with the existing algo-rithms and found the same algorithm complexity O(N) in the Bitcoin and Ethereum blockchains. We determine the break-even point to compensate for the cost of the mining process and network traffic. Consequently, we enable the possibility of compensation for a successful blockchain miner who failed to be granted a reward. This motivates miners to verify and validate new transactions before a new transaction is added to the blockchain. We also adopt an adversary model to obtain the fraction of participating master nodes and SAs that must be compromised by the adversaries to compromise our Master–Slave blockchain (MSB). In this study, we use an electronic healthcare system to illustrate how the proposed MSB works. However, our MSB could be applied in many fields, including the IoT, supply chain management, energy, and commodity transactions.